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2020 – today
- 2024
[j65]Amogh Hiremath
, Vidya Sankar Viswanathan, Kaustav Bera, Rakesh Shiradkar, Lei Yuan, Keith Armitage, Robert Gilkeson, Mengyao Ji, Pingfu Fu, Amit Gupta, Cheng Lu, Anant Madabhushi:
Deep learning reveals lung shape differences on baseline chest CT between mild and severe COVID-19: A multi-site retrospective study. Comput. Biol. Medicine 177: 108643 (2024)- [j64]Zelin Zhang, Sara ArabYarmohammadi, Patrick Leo, Howard Meyerson, Leland Metheny, Jun Xu, Anant Madabhushi:
Automatic myeloblast segmentation in acute myeloid leukemia images based on adversarial feature learning. Comput. Methods Programs Biomed. 243: 107852 (2024) - [j63]Dmitry Cherezov, Vidya Sankar Viswanathan, Pingfu Fu, Amit Gupta, Anant Madabhushi:
Rank acquisition impact on radiomics estimation (AсquIRE) in chest CT imaging: A retrospective multi-site, multi-use-case study. Comput. Methods Programs Biomed. 244: 107990 (2024) - [j62]Cedric Walker, Tasneem Talawalla, Robert Toth, Akhil Ambekar, Kien Rea, Oswin Chamian, Fan Fan, Sabina Berezowska, Sven Rottenberg, Anant Madabhushi, Marie Maillard, Laura Barisoni, Hugo Mark Horlings, Andrew Janowczyk:
PatchSorter: a high throughput deep learning digital pathology tool for object labeling. npj Digit. Medicine 7(1) (2024) - 2023
- [j61]Yufei Zhou, Can Fahrettin Koyuncu, Cheng Lu, Rainer Grobholz, Ian Katz, Anant Madabhushi, Andrew Janowczyk:
Multi-site cross-organ calibrated deep learning (MuSClD): Automated diagnosis of non-melanoma skin cancer. Medical Image Anal. 84: 102702 (2023) - [j60]Sudeshna Sil Kar, Hasan Cetin, Joseph Abraham, Sunil K. Srivastava, Jon Whitney, Anant Madabhushi, Justis P. Ehlers:
Novel Fractal-Based Sub-RPE Compartment OCT Radiomics Biomarkers Are Associated With Subfoveal Geographic Atrophy in Dry AMD. IEEE Trans. Biomed. Eng. 70(10): 2914-2921 (2023) - [c168]Rohan Dhamdhere, Gourav Modanwal, Mohamed H. E. Makhlouf, Neda Shafiabadi Hassani, Satvika Bharadwaj, Pingfu Fu, Ioannis Milioglou, Mahboob Rahman, Sadeer Al-Kindi, Anant Madabhushi:
STAR-Echo: A Novel Biomarker for Prognosis of MACE in Chronic Kidney Disease Patients Using Spatiotemporal Analysis and Transformer-Based Radiomics Models. MICCAI (6) 2023: 284-294 - [c167]Sara ArabYarmohammadi, Germán Corredor, Yufei Zhou, Miguel López de Rodas, Kurt A. Schalper, Anant Madabhushi:
Triangular Analysis of Geographical Interplay of Lymphocytes (TriAnGIL): Predicting Immunotherapy Response in Lung Cancer. MICCAI (6) 2023: 797-807 - [c166]Dmitry Cherezov, Vidya Sankar Viswanathan, Amit Gupta, Anant Madabhushi:
Resolving impact of technical and biological variability on the convolutional neural networks: evaluating chest x-ray scans. Image Processing 2023 - [e21]Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu E. Salcudean, James Duncan, Tanveer F. Syeda-Mahmood, Russell H. Taylor:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 - 26th International Conference, Vancouver, BC, Canada, October 8-12, 2023, Proceedings, Part I. Lecture Notes in Computer Science 14220, Springer 2023, ISBN 978-3-031-43906-3 [contents] - [e20]Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu E. Salcudean, James Duncan, Tanveer F. Syeda-Mahmood, Russell H. Taylor:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 - 26th International Conference, Vancouver, BC, Canada, October 8-12, 2023, Proceedings, Part II. Lecture Notes in Computer Science 14221, Springer 2023, ISBN 978-3-031-43894-3 [contents] - [e19]Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu E. Salcudean, James Duncan, Tanveer F. Syeda-Mahmood, Russell H. Taylor:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 - 26th International Conference, Vancouver, BC, Canada, October 8-12, 2023, Proceedings, Part III. Lecture Notes in Computer Science 14222, Springer 2023, ISBN 978-3-031-43897-4 [contents] - [e18]Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu E. Salcudean, James Duncan, Tanveer F. Syeda-Mahmood, Russell H. Taylor:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 - 26th International Conference, Vancouver, BC, Canada, October 8-12, 2023, Proceedings, Part IV. Lecture Notes in Computer Science 14223, Springer 2023, ISBN 978-3-031-43900-1 [contents] - [e17]Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu E. Salcudean, James Duncan, Tanveer F. Syeda-Mahmood, Russell H. Taylor:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 - 26th International Conference, Vancouver, BC, Canada, October 8-12, 2023, Proceedings, Part V. Lecture Notes in Computer Science 14224, Springer 2023, ISBN 978-3-031-43903-2 [contents] - [e16]Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu E. Salcudean, James Duncan, Tanveer F. Syeda-Mahmood, Russell H. Taylor:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 - 26th International Conference, Vancouver, BC, Canada, October 8-12, 2023, Proceedings, Part VI. Lecture Notes in Computer Science 14225, Springer 2023, ISBN 978-3-031-43986-5 [contents] - [e15]Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu E. Salcudean, James Duncan, Tanveer F. Syeda-Mahmood, Russell H. Taylor:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 - 26th International Conference, Vancouver, BC, Canada, October 8-12, 2023, Proceedings, Part VII. Lecture Notes in Computer Science 14226, Springer 2023, ISBN 978-3-031-43989-6 [contents] - [e14]Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu E. Salcudean, James Duncan, Tanveer F. Syeda-Mahmood, Russell H. Taylor:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 - 26th International Conference, Vancouver, BC, Canada, October 8-12, 2023, Proceedings, Part VIII. Lecture Notes in Computer Science 14227, Springer 2023, ISBN 978-3-031-43992-6 [contents] - [e13]Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu E. Salcudean, James Duncan, Tanveer F. Syeda-Mahmood, Russell H. Taylor:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 - 26th International Conference, Vancouver, BC, Canada, October 8-12, 2023, Proceedings, Part IX. Lecture Notes in Computer Science 14228, Springer 2023, ISBN 978-3-031-43995-7 [contents] - [e12]Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu E. Salcudean, James Duncan, Tanveer F. Syeda-Mahmood, Russell H. Taylor:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 - 26th International Conference, Vancouver, BC, Canada, October 8-12, 2023, Proceedings, Part X. Lecture Notes in Computer Science 14229, Springer 2023, ISBN 978-3-031-43998-8 [contents] - [i10]Chuang Zhu, Shengjie Liu, Feng Xu, Zekuan Yu, Arpit Aggarwal, Germán Corredor, Anant Madabhushi, Qixun Qu, Hongwei Fan, Fangda Li, Yueheng Li, Xianchao Guan, Yongbing Zhang, Vivek Kumar Singh, Farhan Akram, Md. Mostafa Kamal Sarker, Zhongyue Shi, Mulan Jin:
Breast Cancer Immunohistochemical Image Generation: a Benchmark Dataset and Challenge Review. CoRR abs/2305.03546 (2023) - [i9]Cedric Walker, Tasneem Talawalla, Robert Toth, Akhil Ambekar, Kien Rea, Oswin Chamian, Fan Fan, Sabina Berezowska, Sven Rottenberg, Anant Madabhushi, Marie Maillard, Laura Barisoni, Hugo Mark Horlings, Andrew Janowczyk:
PatchSorter: A High Throughput Deep Learning Digital Pathology Tool for Object Labeling. CoRR abs/2307.07528 (2023) - [i8]Fan Fan, Georgia Martinez, Thomas DeSilvio, John Shin, Yijiang Chen, Bangchen Wang, Takaya Ozeki, Maxime W. Lafarge, Viktor H. Koelzer, Laura Barisoni, Anant Madabhushi, Satish E. Viswanath, Andrew Janowczyk:
CohortFinder: an open-source tool for data-driven partitioning of biomedical image cohorts to yield robust machine learning models. CoRR abs/2307.08673 (2023) - 2022
- [j59]Jiawei Xie, Xiaohong Pu, Jian He, Yudong Qiu, Cheng Lu, Wei Gao, Xiangxue Wang, Haoda Lu, Jiong Shi, Yuemei Xu, Anant Madabhushi, Xiangshan Fan, Jun Chen, Jun Xu:
Survival prediction on intrahepatic cholangiocarcinoma with histomorphological analysis on the whole slide images. Comput. Biol. Medicine 146: 105520 (2022) - [j58]Jacob T. Antunes, Marwa Ismail, Imran Hossain, Zhoumengdi Wang, Prateek Prasanna, Anant Madabhushi, Pallavi Tiwari, Satish E. Viswanath:
RADIomic Spatial TexturAl Descriptor (RADISTAT): Quantifying Spatial Organization of Imaging Heterogeneity Associated With Tumor Response to Treatment. IEEE J. Biomed. Health Informatics 26(6): 2627-2636 (2022) - [j57]Marwa Ismail, Prateek Prasanna, Kaustav Bera, Volodymyr Statsevych, Virginia B. Hill, Gagandeep Singh, Sasan Partovi, Niha G. Beig, Sean D. McGarry, Peter S. LaViolette, Manmeet Ahluwalia, Anant Madabhushi, Pallavi Tiwari:
Radiomic Deformation and Textural Heterogeneity (R-DepTH) Descriptor to Characterize Tumor Field Effect: Application to Survival Prediction in Glioblastoma. IEEE Trans. Medical Imaging 41(7): 1764-1777 (2022) - [c165]Ansh Roge, Amogh Hiremath, Michael Sobota, Sree Harsha Tirumani, Leonardo Kayat Bittencourt, Justin Ream, Ryan Ward, Halimat Olaniyan, Sadhna Verma, Andrei S. Purysko, Anant Madabhushi, Rakesh Shiradkar:
Evaluating the sensitivity of deep learning to inter-reader variations in lesion delineations on bi-parametric MRI in identifying clinically significant prostate cancer. Computer-Aided Diagnosis 2022 - [i7]Nathaniel Braman, Prateek Prasanna, Kaustav Bera, Mehdi Alilou, Mohammadhadi Khorrami, Patrick Leo, Maryam Etesami, Manasa Vulchi, Paulette Turk, Amit Gupta, Prantesh Jain, Pingfu Fu, Nathan Pennell, Vamsidhar Velcheti, Jame Abraham, Donna Plecha, Anant Madabhushi:
Novel Radiomic Measurements of Tumor- Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers. CoRR abs/2210.02273 (2022) - 2021
- [j56]Thomas Atta-Fosu, Michael LaBarbera, Soumya Ghose, Paul Schoenhagen, Walid Saliba, Patrick J. Tchou, Bruce D. Lindsay, Milind Y. Desai, Deborah Kwon, Mina K. Chung, Anant Madabhushi:
A new machine learning approach for predicting likelihood of recurrence following ablation for atrial fibrillation from CT. BMC Medical Imaging 21(1): 45 (2021) - [j55]Cheng Lu, Can Fahrettin Koyuncu, Germán Corredor, Prateek Prasanna, Patrick Leo, Xiangxue Wang, Andrew Janowczyk, Kaustav Bera, James Lewis, Vamsidhar Velcheti, Anant Madabhushi:
Feature-driven local cell graph (FLocK): New computational pathology-based descriptors for prognosis of lung cancer and HPV status of oropharyngeal cancers. Medical Image Anal. 68: 101903 (2021) - [j54]Jun Xu, Haoda Lu, Haixin Li, Chaoyang Yan, Xiangxue Wang, Min Zang, Dirk G. de Rooij, Anant Madabhushi, Eugene Yujun Xu:
Computerized spermatogenesis staging (CSS) of mouse testis sections via quantitative histomorphological analysis. Medical Image Anal. 70: 101835 (2021) - [j53]Anant Madabhushi, Constantino Carlos Reyes-Aldasoro:
Special issue on computational pathology: An overview. Medical Image Anal. 73: 102151 (2021) - [j52]S. Kevin Zhou, Hayit Greenspan, Christos Davatzikos, James S. Duncan, Bram van Ginneken, Anant Madabhushi, Jerry L. Prince, Daniel Rueckert, Ronald M. Summers:
A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies With Progress Highlights, and Future Promises. Proc. IEEE 109(5): 820-838 (2021) - [j51]Azam Moosavi, Natalia Figueiredo, Prateek Prasanna, Sunil K. Srivastava, Sumit Sharma, Anant Madabhushi, Justis P. Ehlers:
Imaging Features of Vessels and Leakage Patterns Predict Extended Interval Aflibercept Dosing Using Ultra-Widefield Angiography in Retinal Vascular Disease: Findings From the PERMEATE Study. IEEE Trans. Biomed. Eng. 68(6): 1777-1786 (2021) - [j50]Amogh Hiremath, Kaustav Bera, Lei Yuan, Pranjal Vaidya, Mehdi Alilou, Jennifer Furin, Keith Armitage, Robert Gilkeson, Mengyao Ji, Pingfu Fu, Amit Gupta, Cheng Lu, Anant Madabhushi:
Integrated Clinical and CT Based Artificial Intelligence Nomogram for Predicting Severity and Need for Ventilator Support in COVID-19 Patients: A Multi-Site Study. IEEE J. Biomed. Health Informatics 25(11): 4110-4118 (2021) - [c164]Amogh Hiremath, Lei Yuan, Rakesh Shiradkar, Kaustav Bera, Vidya Sankar Viswanathan, Pranjal Vaidya, Jennifer Furin, Keith Armitage, Robert Gilkeson, Mengyao Ji, Pingfu Fu, Amit Gupta, Cheng Lu, Anant Madabhushi:
LuMiRa: An Integrated Lung Deformation Atlas and 3D-CNN Model of Infiltrates for COVID-19 Prognosis. MICCAI (7) 2021: 367-377 - [c163]Amir Reza Sadri, Sepideh Azarianpour Esfahani, Prathyush Chirra, Jacob Antunes, Pavithran Pattiam Giriprakash, Patrick Leo, Anant Madabhushi, Satish E. Viswanath:
SPARTA: An Integrated Stability, Discriminability, and Sparsity Based Radiomic Feature Selection Approach. MICCAI (3) 2021: 445-455 - [e11]Tanveer F. Syeda-Mahmood, Xiang Li, Anant Madabhushi, Hayit Greenspan, Quanzheng Li, Richard M. Leahy, Bin Dong, Hongzhi Wang:
Multimodal Learning for Clinical Decision Support - 11th International Workshop, ML-CDS 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings. Lecture Notes in Computer Science 13050, Springer 2021, ISBN 978-3-030-89846-5 [contents] - [i6]Marwa Ismail, Prateek Prasanna, Kaustav Bera, Volodymyr Statsevych, Virginia B. Hill, Gagandeep Singh, Sasan Partovi, Niha G. Beig, Sean D. McGarry, Peter S. LaViolette, Manmeet Ahluwalia, Anant Madabhushi, Pallavi Tiwari:
Radiomic Deformation and Textural Heterogeneity (R-DepTH) Descriptor to characterize Tumor Field Effect: Application to Survival Prediction in Glioblastoma. CoRR abs/2103.07423 (2021) - 2020
- [j49]Chaoyang Yan, Kazuaki Nakane, Xiangxue Wang, Yao Fu, Haoda Lu, Xiangshan Fan, Michael D. Feldman, Anant Madabhushi, Jun Xu:
Automated gleason grading on prostate biopsy slides by statistical representations of homology profile. Comput. Methods Programs Biomed. 194: 105528 (2020) - [j48]Marwa Ismail, Virginia B. Hill, Volodymyr Statsevych, Evan Mason, Ramon Correa, Prateek Prasanna, Gagandeep Singh, Kaustav Bera, Rajat Thawani, Manmeet Ahluwalia, Anant Madabhushi, Pallavi Tiwari:
Can Tumor Location on Pre-treatment MRI Predict Likelihood of Pseudo-Progression vs. Tumor Recurrence in Glioblastoma? - A Feasibility Study. Frontiers Comput. Neurosci. 14: 563439 (2020) - [c162]Amogh Hiremath, Rakesh Shiradkar, Nathaniel Braman, Prateek Prasanna, Ardeshir R. Rastinehad, Andrei S. Purysko, Anant Madabhushi:
A combination of intra- and peri-tumoral deep features from prostate bi-parametric MRI can distinguish clinically significant and insignificant prostate cancer. Computer-Aided Diagnosis 2020 - [c161]Amrish Selvam, Jacob Antunes, Kaustav Bera, Asya Ofshteyn, Justin T. Brady, Katherine Bingmer, Kenneth Friedman, Sharon L. Stein, Rajmohan Paspulati, Andrei S. Purysko, Matthew Kalady, Anant Madabhushi, Satish E. Viswanath:
Multi-site evaluation of stable radiomic features for more accurate evaluation of pathologic downstaging on MRI after chemoradiation for rectal cancers. Computer-Aided Diagnosis 2020 - [c160]Rakesh Shiradkar, Ruyuan Zuo, Amr Mahran, Lee Ponsky, Sree Harsha Tirumani, Anant Madabhushi:
Radiomic features derived from periprostatic fat on pre-surgical T2w MRI predict extraprostatic extension of prostate cancer identified on post-surgical pathology: preliminary results. Computer-Aided Diagnosis 2020 - [c159]Sepideh Azarianpour, Germán Corredor, Kaustav Bera, Patrick Leo, Nathaniel Braman, Pingfu Fu, Haider Mahdi, Anant Madabhushi:
Computer extracted features related to the spatial arrangement of tumor-infiltrating lymphocytes predict overall survival in epithelial ovarian cancer receiving adjuvant chemotherapy. Digital Pathology 2020: 113200Q - [c158]Can Fahrettin Koyuncu, Andrew Janowczyk, Cheng Lu, Patrick Leo, Mehdi Alilou, Adam K. Glaser, Nicholas P. Reder, Jonathan T. C. Liu, Anant Madabhushi:
Three-dimensional histo-morphometric features from light sheet microscopy images result in improved discrimination of benign from malignant glands in prostate cancer. Digital Pathology 2020: 113200G - [c157]Shayan Monabbati, Patrick Leo, Kaustav Bera, Behtash G. Nezami, Claire W. Michael, Aparna Harbhajanka, Anant Madabhushi:
Texture features distinguish benign cell clusters from adenocarcinomas on bile duct brushing cytology images. Digital Pathology 2020: 113200I - [c156]Ruiwen Ding, Prateek Prasanna, Germán Corredor, Cheng Lu, Priya Velu, Khoi Le, Patrick Leo, Niha G. Beig, Vamsidhar Velcheti, David L. Rimm, Kurt A. Schalper, Anant Madabhushi:
Compactness measures of tumor infiltrating lymphocytes in lung adenocarcinoma are associated with overall patient survival and immune scores. Digital Pathology 2020: 1132003 - [c155]Sara ArabYarmohammadi, Zelin Zhang, Patrick Leo, Marjan Firouznia, Andrew Janowczyk, Haojia Li, Nathaniel M. Braman, Kaustav Bera, Behtash G. Nezami, Howard Meyerson, Jun Xu, Leland Metheny, Anant Madabhushi:
Computationally derived cytological image markers for predicting risk of relapse in acute myeloid leukemia patients following bone marrow transplantation. Digital Pathology 2020: 1132004 - [e10]Tanveer F. Syeda-Mahmood, Klaus Drechsler, Hayit Greenspan, Anant Madabhushi, Alexandros Karargyris, Marius George Linguraru, Cristina Oyarzun Laura, Raj Shekhar, Stefan Wesarg, Miguel Ángel González Ballester, Marius Erdt:
Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures - 10th International Workshop, ML-CDS 2020, and 9th International Workshop, CLIP 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4-8, 2020, Proceedings. Lecture Notes in Computer Science 12445, Springer 2020, ISBN 978-3-030-60945-0 [contents] - [i5]Nathaniel Braman, Mohammed El Adoui, Manasa Vulchi, Paulette Turk, Maryam Etesami, Pingfu Fu, Kaustav Bera, Stylianos Drisis, Vinay Varadan, Donna Plecha, Mohammed Benjelloun, Jame Abraham, Anant Madabhushi:
Deep learning-based prediction of response to HER2-targeted neoadjuvant chemotherapy from pre-treatment dynamic breast MRI: A multi-institutional validation study. CoRR abs/2001.08570 (2020) - [i4]Amir Reza Sadri, Andrew Janowczyk, Ren Zou, Ruchika Verma, Jacob Antunes, Anant Madabhushi, Pallavi Tiwari, Satish E. Viswanath:
MRQy: An Open-Source Tool for Quality Control of MR Imaging Data. CoRR abs/2004.04871 (2020) - [i3]Marwa Ismail, Virginia B. Hill, Volodymyr Statsevych, Evan Mason, Ramon Correa, Prateek Prasanna, Gagandeep Singh, Kaustav Bera, Rajat Thawani, Anant Madabhushi, Manmeet Ahluwalia, Pallavi Tiwari:
Can tumor location on pre-treatment MRI predict likelihood of pseudo-progression versus tumor recurrence in Glioblastoma? A feasibility study. CoRR abs/2006.09483 (2020) - [i2]S. Kevin Zhou, Hayit Greenspan, Christos Davatzikos, James S. Duncan, Bram van Ginneken, Anant Madabhushi, Jerry L. Prince, Daniel Rueckert, Ronald M. Summers:
A review of deep learning in medical imaging: Image traits, technology trends, case studies with progress highlights, and future promises. CoRR abs/2008.09104 (2020)
2010 – 2019
- 2019
- [j47]Satish Viswanath, Prathyush Chirra, Michael Yim, Neil M. Rofsky, Andrei S. Purysko, Mark A. Rosen, B. Nicolas Bloch, Anant Madabhushi:
Comparing radiomic classifiers and classifier ensembles for detection of peripheral zone prostate tumors on T2-weighted MRI: a multi-site study. BMC Medical Imaging 19(1): 22:1-22:12 (2019) - [c154]Jun Xu, Chengfei Cai, Yangshu Zhou, Bo Yao, Geyang Xu, Xiangxue Wang, Ke Zhao, Anant Madabhushi, Zaiyi Liu, Li Liang:
Multi-tissue Partitioning for Whole Slide Images of Colorectal Cancer Histopathology Images with Deeptissue Net. ECDP 2019: 100-108 - [c153]Jun Xu, Haoda Lu, Haixin Li, Xiangxue Wang, Anant Madabhushi, Yujun Xu:
Histopathological Image Analysis on Mouse Testes for Automated Staging of Mouse Seminiferous Tubule. ECDP 2019: 117-124 - [c152]Prateek Prasanna, Justis Ehlers, Vishal Bobba, Natalia Figueredo, Cheng Lu, Sumit Sharma, Sunil Srivastava, Anant Madabhushi:
Spatial arrangement of leakage patterns in diabetic macular edema is associated with tolerance of aflibercept treatment interval length: preliminary findings. Biomedical Applications in Molecular, Structural, and Functional Imaging 2019: 1095311 - [c151]Prateek Prasanna, Justis Ehlers, Nathaniel Braman, Natalia Figueredo, Vishal Bobba, Sumit Sharma, Sunil Srivastava, Anant Madabhushi:
Morphology of vascular network in eyes with diabetic macular edema varies based on tolerance of aflibercept treatment interval length: preliminary findings. Biomedical Applications in Molecular, Structural, and Functional Imaging 2019: 1095312 - [c150]Mohammadhadi Khorrami, Mehdi Alilou, Prateek Prasanna, Pradnya Patil, Pirya Velu, Kaustav Bera, Pingfu Fu, Vamsidhar Velcheti, Anant Madabhushi:
A combination of intra- and peritumoral features on baseline CT scans is associated with overall survival in non-small cell lung cancer patients treated with immune checkpoint inhibitors: a multi-agent multi-site study. Computer-Aided Diagnosis 2019: 109500R - [c149]Ruchika Verma, Ramon Correa, Virginia B. Hill, Niha G. Beig, Abdelkader Mahammedi, Anant Madabhushi, Pallavi Tiwari:
Radiomics of the lesion habitat on pre-treatment MRI predicts response to chemo-radiation therapy in Glioblastoma. Computer-Aided Diagnosis 2019: 109500B - [c148]Mehdi Alilou, Pranjal Vaidya, Mohammadhadi Khorrami, Alexia Zagouras, Pradnya Patil, Kaustav Bera, Pingfu Fu, Vamsidhar Velcheti, Anant Madabhushi:
Quantitative vessel tortuosity radiomics on baseline non-contrast lung CT predict response to immunotherapy and are prognostic of overall survival. Computer-Aided Diagnosis 2019: 109501F - [c147]Niha G. Beig, Prateek Prasanna, Virginia B. Hill, Ruchika Verma, Vinay Varadan, Anant Madabhushi, Pallavi Tiwari:
Radiogenomic characterization of response to chemo-radiation therapy in glioblastoma is associated with PI3K/AKT/mTOR and apoptosis signaling pathways. Computer-Aided Diagnosis 2019: 109501B - [c146]Sukanya Iyer, Marwa Ismail, Benita Tamrazi, Ashley Margol, Ruchika Verma, Ramon Correa, Prateek Prasanna, Niha G. Beig, Kaustav Bera, Volodymyr Statsevych, Alexander R. Judkins, Anant Madabhushi, Pallavi Tiwari:
Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI. Computer-Aided Diagnosis 2019: 109501E - [c145]Lin Li, Rakesh Shiradkar, Ahmad Algohary, Patrick Leo, Cristina Magi-Galluzzi, Eric Klein, Andrei S. Purysko, Anant Madabhushi:
Radiomic features derived from pre-operative multi-parametric MRI of prostate cancer are associated with Decipher risk score. Computer-Aided Diagnosis 2019: 109503Y - [c144]Jeffrey E. Eben, Nathaniel Braman, Anant Madabhushi:
Response Estimation Through Spatially Oriented Neural Network and Texture Ensemble (RESONATE). MICCAI (4) 2019: 602-610 - [c143]Jacob Antunes, Zhouping Wei, Charlems Álvarez Jimenez, Eduardo Romero, Marwa Ismail, Anant Madabhushi, Pallavi Tiwari, Satish E. Viswanath:
STructural Rectal Atlas Deformation (StRAD) Features for Characterizing Intra- and Peri-wall Chemoradiation Response on MRI. MICCAI (4) 2019: 611-619 - [c142]Cristian Barrera, Germán Corredor, Xiangxue Wang, Kurt A. Schalper, David L. Rimm, Vamsidhar Velcheti, Anant Madabhushi, Edgar Eduardo Romero Castro:
Phenotyping tumor infiltrating lymphocytes (PhenoTIL) on H&E tissue images: predicting recurrence in lung cancer. Digital Pathology 2019: 1095607 - [c141]Siddhartha Nanda, Jacob T. Antunes, Amrish Selvam, Kaustav Bera, Justin T. Brady, Jayakrishna Gollamudi, Kenneth Friedman, Joseph E. Willis, Conor P. Delaney, Raj M. Paspulati, Anant Madabhushi, Satish E. Viswanath:
Integrating radiomic features from T2-weighted and contrast-enhanced MRI to evaluate pathologic rectal tumor regression after chemoradiation. Image-Guided Procedures 2019: 109512R - [c140]Michael C. Yim, Zhouping Wei, Jacob Antunes, Neil K. R. Sehgal, Kaustav Bera, Justin T. Brady, Kenneth Friedman, Joseph E. Willis, Andrei S. Purysko, Raj M. Paspulati, Anant Madabhushi, Satish E. Viswanath:
Radiomic characterization of perirectal fat on MRI enables accurate assessment of tumor regression and lymph node metastasis in rectal cancers after chemoradiation. Image-Guided Procedures 2019: 109512A - [e9]Kenji Suzuki, Mauricio Reyes, Tanveer F. Syeda-Mahmood, Ben Glocker, Roland Wiest, Yaniv Gur, Hayit Greenspan, Anant Madabhushi:
Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support - Second International Workshop, iMIMIC 2019, and 9th International Workshop, ML-CDS 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings. Lecture Notes in Computer Science 11797, Springer 2019, ISBN 978-3-030-33849-7 [contents] - 2018
- [j46]Andrew Janowczyk, Scott Doyle, Hannah Gilmore, Anant Madabhushi:
A resolution adaptive deep hierarchical (RADHicaL) learning scheme applied to nuclear segmentation of digital pathology images. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 6(3): 270-276 (2018) - [c139]Prathyush Chirra, Patrick Leo, Michael Yim, B. Nicolas Bloch, Ardeshir R. Rastinehad, Andrei S. Purysko, Mark Rosen, Anant Madabhushi, Satish Viswanath:
Empirical evaluation of cross-site reproducibility in radiomic features for characterizing prostate MRI. Computer-Aided Diagnosis 2018: 105750B - [c138]Kavya Ravichandran, Nathaniel Braman, Andrew Janowczyk, Anant Madabhushi:
A deep learning classifier for prediction of pathological complete response to neoadjuvant chemotherapy from baseline breast DCE-MRI. Computer-Aided Diagnosis 2018: 105750C - [c137]Cheng Lu, Xiangxue Wang, Prateek Prasanna, Germán Corredor, Geoffrey Sedor, Kaustav Bera, Vamsidhar Velcheti, Anant Madabhushi:
Feature Driven Local Cell Graph (FeDeG): Predicting Overall Survival in Early Stage Lung Cancer. MICCAI (2) 2018: 407-416 - [c136]Nathaniel Braman, Prateek Prasanna, Mehdi Alilou, Niha G. Beig, Anant Madabhushi:
Vascular Network Organization via Hough Transform (VaNgOGH): A Novel Radiomic Biomarker for Diagnosis and Treatment Response. MICCAI (2) 2018: 803-811 - [c135]Germán Corredor, Xiangxue Wang, Cheng Lu, Vamsidhar Velcheti, Eduardo Romero, Anant Madabhushi:
A watershed and feature-based approach for automated detection of lymphocytes on lung cancer images. Digital Pathology 2018: 105810R - [c134]Patrick Leo, Eswar Shankar, Robin Elliott, Andrew Janowczyk, Anant Madabhushi, Sanjay Gupta:
Combination of nuclear NF-κB/p65 localization and gland morphological features from surgical specimens appears to be predictive of early biochemical recurrence in prostate cancer patients. Digital Pathology 2018: 105810D - [c133]Pranjal Vaidya, Xiangxue Wang, Kaustav Bera, Arjun Khunger, Humberto Choi, Pradnya Patil, Vamsidhar Velcheti, Anant Madabhushi:
RaPtomics: integrating radiomic and pathomic features for predicting recurrence in early stage lung cancer. Digital Pathology 2018: 105810M - [e8]Danail Stoyanov, Zeike Taylor, Gustavo Carneiro, Tanveer F. Syeda-Mahmood, Anne L. Martel, Lena Maier-Hein, João Manuel R. S. Tavares, Andrew P. Bradley, João Paulo Papa, Vasileios Belagiannis, Jacinto C. Nascimento, Zhi Lu, Sailesh Conjeti, Mehdi Moradi, Hayit Greenspan, Anant Madabhushi:
Deep Learning in Medical Image Analysis - and - Multimodal Learning for Clinical Decision Support - 4th International Workshop, DLMIA 2018, and 8th International Workshop, ML-CDS 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings. Lecture Notes in Computer Science 11045, Springer 2018, ISBN 978-3-030-00888-8 [contents] - 2017
- [j45]Satish Viswanath, Pallavi Tiwari, George Lee, Anant Madabhushi:
Dimensionality reduction-based fusion approaches for imaging and non-imaging biomedical data: concepts, workflow, and use-cases. BMC Medical Imaging 17(1): 2:1-2:17 (2017) - [j44]Andrew Janowczyk, Ajay Basavanhally, Anant Madabhushi:
Stain Normalization using Sparse AutoEncoders (StaNoSA): Application to digital pathology. Comput. Medical Imaging Graph. 57: 50-61 (2017) - [c132]Niha G. Beig, Jay Patel, Prateek Prasanna, Sasan Partovi, Vinay Varadan, Anant Madabhushi, Pallavi Tiwari:
Radiogenomic analysis of hypoxia pathway reveals computerized MRI descriptors predictive of overall survival in glioblastoma. Computer-Aided Diagnosis 2017: 101341U - [c131]Soumya Ghose, Rakesh Shiradkar, Mirabela Rusu, Jhimli Mitra, Rajat Thawani, Michael D. Feldman, Amar Gupta, Andrei S. Purysko, Lee Ponsky, Anant Madabhushi:
Field Effect Induced Organ Distension (FOrge) Features Predicting Biochemical Recurrence from Pre-treatment Prostate MRI. MICCAI (2) 2017: 442-449 - [c130]Prateek Prasanna, Jhimli Mitra, Niha G. Beig, Sasan Partovi, Gagandeep Singh, Marco Pinho, Anant Madabhushi, Pallavi Tiwari:
Radiographic-Deformation and Textural Heterogeneity (r-DepTH): An Integrated Descriptor for Brain Tumor Prognosis. MICCAI (2) 2017: 459-467 - [c129]Jacob Antunes, Prateek Prasanna, Anant Madabhushi, Pallavi Tiwari, Satish Viswanath:
RADIomic Spatial TexturAl descripTor (RADISTAT): Characterizing Intra-tumoral Heterogeneity for Response and Outcome Prediction. MICCAI (2) 2017: 468-476 - [c128]Mehdi Alilou, Mahdi Orooji, Anant Madabhushi:
Intra-perinodular Textural Transition (Ipris): A 3D Descriptor for Nodule Diagnosis on Lung CT. MICCAI (3) 2017: 647-655 - [c127]Paula Toro, Germán Corredor, Xiangxue Wang, Viviana Arias, Vamsidhar Velcheti, Anant Madabhushi, Eduardo Romero:
Quantifying expert diagnosis variability when grading tumor-infiltrating lymphocytes. SIPAIM 2017: 1057202 - [c126]Juan D. García-Arteaga, Germán Corredor, Xiangxue Wang, Vamsidhar Velcheti, Anant Madabhushi, Eduardo Romero:
A lymphocyte spatial distribution graph-based method for automated classification of recurrence risk on lung cancer images. SIPAIM 2017: 1057203 - [p1]Jeffrey J. Nirschl, Andrew Janowczyk, Eliot G. Peyster, Renee Frank, Kenneth B. Margulies, Michael D. Feldman, Anant Madabhushi:
Deep Learning Tissue Segmentation in Cardiac Histopathology Images. Deep Learning for Medical Image Analysis 2017: 179-195 - [e7]M. Jorge Cardoso, Tal Arbel, Gustavo Carneiro, Tanveer F. Syeda-Mahmood, João Manuel R. S. Tavares, Mehdi Moradi, Andrew P. Bradley, Hayit Greenspan, João Paulo Papa, Anant Madabhushi, Jacinto C. Nascimento, Jaime S. Cardoso, Vasileios Belagiannis, Zhi Lu:
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support - Third International Workshop, DLMIA 2017, and 7th International Workshop, ML-CDS 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, 2017, Proceedings. Lecture Notes in Computer Science 10553, Springer 2017, ISBN 978-3-319-67557-2 [contents] - 2016
- [j43]Jun Xu, Xiaofei Luo, Guanhao Wang, Hannah Gilmore, Anant Madabhushi:
A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions in histopathological images. Neurocomputing 191: 214-223 (2016) - [j42]Anant Madabhushi, George Lee:
Image analysis and machine learning in digital pathology: Challenges and opportunities. Medical Image Anal. 33: 170-175 (2016) - [j41]Shoshana B. Ginsburg, George Lee, Sahirzeeshan Ali, Anant Madabhushi:
Feature Importance in Nonlinear Embeddings (FINE): Applications in Digital Pathology. IEEE Trans. Medical Imaging 35(1): 76-88 (2016) - [j40]Jun Xu, Lei Xiang, Qingshan Liu, Hannah Gilmore, Jianzhong Wu, Jinghai Tang, Anant Madabhushi:
Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images. IEEE Trans. Medical Imaging 35(1): 119-130 (2016) - [c125]Patrick Leo, George Lee, Anant Madabhushi:
Evaluating stability of histomorphometric features across scanner and staining variations: predicting biochemical recurrence from prostate cancer whole slide images. Digital Pathology 2016: 97910I - [c124]David Romo-Bucheli, Andrew Janowczyk, Eduardo Romero, Hannah Gilmore, Anant Madabhushi:
Automated tubule nuclei quantification and correlation with oncotype DX risk categories in ER+ breast cancer whole slide images. Digital Pathology 2016: 979106 - [c123]Lin Li, Mirabela Rusu, Satish Viswanath, Gregory Penzias, Shivani Pahwa, Jay Gollamudi, Anant Madabhushi:
Multi-modality registration via multi-scale textural and spectral embedding representations. Image Processing 2016: 978446 - [e6]Metin N. Gurcan, Anant Madabhushi:
Medical Imaging 2016: Digital Pathology, San Diego, California, United States, 27 February - 3 March 2016. SPIE Proceedings 9791, SPIE 2016, ISBN 9781510600263 [contents] - 2015
- [j39]Sahirzeeshan Ali, Robert Veltri, Jonathan I. Epstein, Christhunesa Christudass, Anant Madabhushi:
Selective invocation of shape priors for deformable segmentation and morphologic classification of prostate cancer tissue microarrays. Comput. Medical Imaging Graph. 41: 3-13 (2015) - [j38]Jun Xu, Lei Xiang, Guanhao Wang, Shridar Ganesan, Michael D. Feldman, Natalie N. C. Shih, Hannah Gilmore, Anant Madabhushi:
Sparse Non-negative Matrix Factorization (SNMF) based color unmixing for breast histopathological image analysis. Comput. Medical Imaging Graph. 46: 20-29 (2015) - [j37]Mitko Veta, Paul J. van Diest, Stefan M. Willems, Haibo Wang, Anant Madabhushi, Angel Cruz-Roa, Fabio A. González, Anders Boesen Lindbo Larsen, Jacob S. Vestergaard, Anders B. Dahl, Dan C. Ciresan, Jürgen Schmidhuber, Alessandro Giusti, Luca Maria Gambardella, Faik Boray Tek, Thomas Walter, Ching-Wei Wang, Satoshi Kondo, Bogdan J. Matuszewski, Frédéric Precioso, Violet Snell, Josef Kittler, Teófilo Emídio de Campos, Adnan Mujahid Khan, Nasir M. Rajpoot, Evdokia Arkoumani, Miangela M. Lacle, Max A. Viergever, Josien P. W. Pluim:
Assessment of algorithms for mitosis detection in breast cancer histopathology images. Medical Image Anal. 20(1): 237-248 (2015) - [j36]George Lee, Asha Singanamalli, Haibo Wang, Michael D. Feldman, Stephen R. Master, Natalie N. C. Shih, Elaine Spangler, Timothy R. Rebbeck, John Tomaszewski, Anant Madabhushi:
Supervised Multi-View Canonical Correlation Analysis (sMVCCA): Integrating Histologic and Proteomic Features for Predicting Recurrent Prostate Cancer. IEEE Trans. Medical Imaging 34(1): 284-297 (2015) - [c122]Sebastian Otálora, Angel Cruz-Roa, John Edison Arevalo Ovalle, Manfredo Atzori, Anant Madabhushi, Alexander R. Judkins, Fabio A. González, Henning Müller, Adrien Depeursinge:
Combining Unsupervised Feature Learning and Riesz Wavelets for Histopathology Image Representation: Application to Identifying Anaplastic Medulloblastoma. MICCAI (1) 2015: 581-588 - [e5]Metin N. Gurcan, Anant Madabhushi:
Medical Imaging 2015: Digital Pathology, Orlando, Florida, United States, 21-26 February 2015. SPIE Proceedings 9420, SPIE 2015, ISBN 9781628415100 [contents] - 2014
- [j35]Robert Toth, Bryan J. Traughber, Rodney J. Ellis, John Kurhanewicz, Anant Madabhushi:
A domain constrained deformable (DoCD) model for co-registration of pre- and post-radiated prostate MRI. Neurocomputing 144: 3-12 (2014) - [j34]Satish Viswanath, Robert Toth, Mirabela Rusu, Dan Sperling, Herbert Lepor, Jurgen J. Fütterer, Anant Madabhushi:
Identifying quantitative in vivo multi-parametric MRI features for treatment related changes after laser interstitial thermal therapy of prostate cancer. Neurocomputing 144: 13-23 (2014) - [j33]Tao Wan, B. Nicolas Bloch, Shabbar Danish, Anant Madabhushi:
A learning based fiducial-driven registration scheme for evaluating laser ablation changes in neurological disorders. Neurocomputing 144: 24-37 (2014) - [j32]Geert Litjens, Robert Toth, Wendy J. M. van de Ven, Caroline Hoeks, Sjoerd Kerkstra, Bram van Ginneken, Graham Vincent, Gwenaël Guillard, Neil Birbeck, Jindang Zhang, Robin Strand, Filip Malmberg, Yangming Ou, Christos Davatzikos, Matthias Kirschner, Florian Jung, Jing Yuan, Wu Qiu, Qinquan Gao, Philip J. Edwards, Bianca Maan, Ferdinand van der Heijden, Soumya Ghose, Jhimli Mitra, Jason Dowling, Dean C. Barratt, Henkjan J. Huisman, Anant Madabhushi:
Evaluation of prostate segmentation algorithms for MRI: The PROMISE12 challenge. Medical Image Anal. 18(2): 359-373 (2014) - [c121]Pallavi Tiwari, Prateek Prasanna, Lisa Rogers, Leo Wolansky, Chaitra Badve, Andrew Sloan, Mark Cohen, Anant Madabhushi:
Texture descriptors to distinguish radiation necrosis from recurrent brain tumors on multi-parametric MRI. Computer-Aided Diagnosis 2014: 90352B - [c120]Shoshana B. Ginsburg, Mirabela Rusu, John Kurhanewicz, Anant Madabhushi:
Computer extracted texture features on T2w MRI to predict biochemical recurrence following radiation therapy for prostate cancer. Computer-Aided Diagnosis 2014: 903509 - [c119]Geert J. S. Litjens, R. Elliott, Natalie Shih, Michael D. Feldman, Jelle O. Barentsz, Christina A. Hulsbergen van de Kaa, Iringo Kovacs, Henkjan J. Huisman, Anant Madabhushi:
Distinguishing prostate cancer from benign confounders via a cascaded classifier on multi-parametric MRI. Computer-Aided Diagnosis 2014: 903512 - [c118]Mirabela Rusu, John Kurhanewicz, Ashutosh Tewari, Anant Madabhushi:
A prostate MRI atlas of biochemical failures following cancer treatment. Computer-Aided Diagnosis 2014: 903513 - [c117]Prateek Prasanna, Pallavi Tiwari, Anant Madabhushi:
Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): Distinguishing Tumor Confounders and Molecular Subtypes on MRI. MICCAI (3) 2014: 73-80 - [c116]Haibo Wang, Asha Singanamalli, Shoshana Ginsburg, Anant Madabhushi:
Selecting Features with Group-Sparse Nonnegative Supervised Canonical Correlation Analysis: Multimodal Prostate Cancer Prognosis. MICCAI (3) 2014: 385-392 - [c115]Haibo Wang, Angel Cruz-Roa, Ajay Basavanhally, Hannah Gilmore, Natalie Shih, Mike Feldman, John Tomaszewski, Fabio A. González, Anant Madabhushi:
Cascaded ensemble of convolutional neural networks and handcrafted features for mitosis detection. Digital Pathology 2014: 90410B - [c114]Angel Cruz-Roa, Ajay Basavanhally, Fabio A. González, Hannah Gilmore, Michael D. Feldman, Shridar Ganesan, Natalie Shih, John Tomaszewski, Anant Madabhushi:
Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks. Digital Pathology 2014: 904103 - [c113]Geert Litjens, Henkjan J. Huisman, R. Elliott, Natalie Shih, Michael D. Feldman, Satish Viswanath, Jurgen J. Fütterer, J. Bomers, Anant Madabhushi:
Distinguishing benign confounding treatment changes from residual prostate cancer on MRI following laser ablation. Image-Guided Procedures 2014: 90361D - [c112]Pallavi Tiwari, Shabbar Danish, Anant Madabhushi:
Identifying MRI markers to evaluate early treatment-related changes post-laser ablation for cancer pain management. Image-Guided Procedures 2014: 90362L - [c111]Eileen Hwuang, Mirabela Rusu, Sudha Karthigeyan, Shannon Agner, Rachel Sparks, Natalie Shih, John E. Tomaszeweski, Mark Rosen, Michael D. Feldman, Anant Madabhushi:
Spectral embedding-based registration (SERg) for multimodal fusion of prostate histology and MRI. Image Processing 2014: 90343P - [c110]Mahdi Orooji, Rachel Sparks, B. Nicolas Bloch, Ernest J. Feleppa, Dean C. Barratt, Anant Madabhushi:
Spatially aware expectation maximization (SpAEM): application to prostate TRUS segmentation. Image Processing 2014: 90343Y - [e4]Metin N. Gurcan, Anant Madabhushi:
Medical Imaging 2014: Digital Pathology, San Diego, California, United States, 15-20 February 2014. SPIE Proceedings 9041, SPIE 2014, ISBN 9780819498342 [contents] - [i1]Mitko Veta, Paul J. van Diest, Stefan M. Willems, Haibo Wang, Anant Madabhushi, Angel Cruz-Roa, Fabio A. González, Anders Boesen Lindbo Larsen, Jacob S. Vestergaard, Anders B. Dahl, Dan C. Ciresan, Jürgen Schmidhuber, Alessandro Giusti, Luca Maria Gambardella, Faik Boray Tek, Thomas Walter, Ching-Wei Wang, Satoshi Kondo, Bogdan J. Matuszewski, Frédéric Precioso, Violet Snell, Josef Kittler, Teófilo Emídio de Campos, Adnan Mujahid Khan, Nasir M. Rajpoot, Evdokia Arkoumani, Miangela M. Lacle, Max A. Viergever, Josien P. W. Pluim:
Assessment of algorithms for mitosis detection in breast cancer histopathology images. CoRR abs/1411.5825 (2014) - 2013
- [j31]Robert Toth, Justin Ribault, John Gentile, Dan Sperling, Anant Madabhushi:
Simultaneous segmentation of prostatic zones using Active Appearance Models with multiple coupled levelsets. Comput. Vis. Image Underst. 117(9): 1051-1060 (2013) - [j30]Rachel Sparks, Anant Madabhushi:
Statistical shape model for manifold regularization: Gleason grading of prostate histology. Comput. Vis. Image Underst. 117(9): 1138-1146 (2013) - [j29]Pallavi Tiwari, John Kurhanewicz, Anant Madabhushi:
Multi-kernel graph embedding for detection, Gleason grading of prostate cancer via MRI/MRS. Medical Image Anal. 17(2): 219-235 (2013) - [j28]Rachel Sparks, Anant Madabhushi:
Explicit shape descriptors: Novel morphologic features for histopathology classification. Medical Image Anal. 17(8): 997-1009 (2013) - [j27]Ajay Basavanhally, Shridar Ganesan, Michael D. Feldman, Natalie Shih, Carolyn Mies, John Tomaszewski, Anant Madabhushi:
Multi-Field-of-View Framework for Distinguishing Tumor Grade in ER+ Breast Cancer From Entire Histopathology Slides. IEEE Trans. Biomed. Eng. 60(8): 2089-2099 (2013) - [c109]Eileen Hwuang, Shabbar Danish, Mirabela Rusu, Rachel Sparks, Robert Toth, Anant Madabhushi:
Anisotropic smoothing regularization (AnSR) in Thirion's Demons registration evaluates brain MRI tissue changes post-laser ablation. EMBC 2013: 4006-4009 - [c108]George Lee, Rachel Sparks, Sahirzeeshan Ali, Anant Madabhushi, Michael D. Feldman, Stephen R. Master, Natalie Shih, John Tomaszewski:
Co-occurring gland tensors in localized cluster graphs: Quantitative histomorphometry for predicting biochemical recurrence for intermediate grade prostate cancer. ISBI 2013: 113-116 - [c107]Haibo Wang, Satish Viswanath, Anant Madabhushi:
Discriminatively weighted multi-scale Local Binary Patterns: Applications in prostate cancer diagnosis on T2W MRI. ISBI 2013: 398-401 - [c106]Tao Wan, B. Nicolas Bloch, Shabbar Danish, Anant Madabhushi:
Learning based fiducial driven registration (LEFIR): Evaluating laser ablation changes for neurological applications. ISBI 2013: 1428-1431 - [c105]Shoshana B. Ginsburg, B. Nicolas Bloch, Neil M. Rofsky, Elizabeth M. Genega, Robert E. Lenkinski, Anant Madabhushi:
Iterative multiple reference tissue method for estimating pharmacokinetic parameters on prostate DCE MRI. Computer-Aided Diagnosis 2013: 86701J - [c104]Shoshana Ginsburg, Sahirzeeshan Ali, George Lee, Ajay Basavanhally, Anant Madabhushi:
Variable Importance in Nonlinear Kernels (VINK): Classification of Digitized Histopathology. MICCAI (2) 2013: 238-245 - [c103]George Lee, Sahirzeeshan Ali, Robert Veltri, Jonathan I. Epstein, Christhunesa Christudass, Anant Madabhushi:
Cell Orientation Entropy (COrE): Predicting Biochemical Recurrence from Prostate Cancer Tissue Microarrays. MICCAI (3) 2013: 396-403 - [c102]Angel Alfonso Cruz-Roa, John Edison Arevalo Ovalle, Anant Madabhushi, Fabio Augusto González Osorio:
A Deep Learning Architecture for Image Representation, Visual Interpretability and Automated Basal-Cell Carcinoma Cancer Detection. MICCAI (2) 2013: 403-410 - [c101]Sahirzeeshan Ali, James Lewis, Anant Madabhushi:
Spatially Aware Cell Cluster(SpACCl) Graphs: Predicting Outcome in Oropharyngeal p16+ Tumors. MICCAI (1) 2013: 412-419 - [c100]Sahirzeeshan Ali, Robert Veltri, Jonathan A. Epstein, Christhunesa Christudass, Anant Madabhushi:
Cell cluster graph for prediction of biochemical recurrence in prostate cancer patients from tissue microarrays. Digital Pathology 2013: 86760H - [c99]Ajay Basavanhally, Anant Madabhushi:
EM-based segmentation-driven color standardization of digitized histopathology. Digital Pathology 2013: 86760G - [c98]Srivathsan Babu Prabu, Robert Toth, Anant Madabhushi:
A statistical deformation model (SDM) based regularizer for non-rigid image registration: application to registration of multimodal prostate MRI and histology. Digital Pathology 2013: 86760C - [c97]Asha Singanamalli, Rachel Sparks, Mirabela Rusu, Natalie Shih, Amy Ziober, John Tomaszewski, Mark Rosen, Michael D. Feldman, Anant Madabhushi:
Identifying in vivo DCE MRI parameters correlated with ex vivo quantitative microvessel architecture: A radiohistomorphometric approach. Digital Pathology 2013: 867604 - [c96]Rachel Sparks, B. Nicolas Bloch, Ernest J. Feleppa, Dean C. Barratt, Anant Madabhushi:
Fully automated prostate magnetic resonance imaging and transrectal ultrasound fusion via a probabilistic registration metric. Image-Guided Procedures 2013: 86710A - [c95]Pallavi Tiwari, Shabbar Danish, Stephen Wong, Anant Madabhushi:
Quantitative evaluation of multi-parametric MR imaging marker changes post-laser interstitial ablation therapy (LITT) for epilepsy. Image-Guided Procedures 2013: 86711Y - [c94]Satish Viswanath, Robert Toth, Mirabela Rusu, Dan Sperling, Herbert Lepor, Jurgen J. Fütterer, Anant Madabhushi:
Quantitative evaluation of treatment related changes on multi-parametric MRI after laser interstitial thermal therapy of prostate cancer. Image-Guided Procedures 2013: 86711F - [c93]Mirabela Rusu, B. Nicolas Bloch, C. Carl Jaffe, Neil Rofsky, Elizabeth Genega, Ernest J. Feleppa, Robert E. Lenkinski, Anant Madabhushi:
Statistical 3D prostate imaging atlas construction via anatomically constrained registration. Image Processing 2013: 866913 - [c92]Haibo Wang, Mirabela Rusu, Thea Golden, Andrew J. Gow, Anant Madabhushi:
Mouse lung volume reconstruction from efficient groupwise registration of individual histological slices with natural gradient. Image Processing 2013: 866914 - [c91]Tao Wan, B. Nicolas Bloch, Shabbar Danish, Anant Madabhushi:
A novel point-based nonrigid image registration scheme based on learning optimal landmark configurations. Image Processing 2013: 866934 - [c90]Prateek Prasanna, Shubham Jain, Neelakshi Bhagat, Anant Madabhushi:
Decision support system for detection of diabetic retinopathy using smartphones. PervasiveHealth 2013: 176-179 - [e3]Metin N. Gurcan, Anant Madabhushi:
Medical Imaging 2013: Digital Pathology, Lake Buena Vista (Orlando Area), Florida, United States, 9-14 February 2013. SPIE Proceedings 8676, SPIE 2013, ISBN 9780819494504 [contents] - 2012
- [j26]Satish Viswanath, Anant Madabhushi:
Consensus embedding: theory, algorithms and application to segmentation and classification of biomedical data. BMC Bioinform. 13: 26 (2012) - [j25]Scott Doyle, Michael D. Feldman, Natalie Shih, John Tomaszewski, Anant Madabhushi:
Cascaded discrimination of normal, abnormal, and confounder classes in histopathology: Gleason grading of prostate cancer. BMC Bioinform. 13: 282 (2012) - [j24]James Monaco, Anant Madabhushi:
Class-specific weighting for Markov random field estimation: Application to medical image segmentation. Medical Image Anal. 16(8): 1477-1489 (2012) - [j23]Sergio Cerutti, Anant Madabhushi, Shishir K. Shah, Ki H. Chon:
Editorial: TBME Letters Special Section on Multiscale Biomedical Signal and Image Modeling and Analysis. IEEE Trans. Biomed. Eng. 59(1): 4-7 (2012) - [j22]Scott Doyle, Michael D. Feldman, John Tomaszewski, Anant Madabhushi:
A Boosted Bayesian Multiresolution Classifier for Prostate Cancer Detection From Digitized Needle Biopsies. IEEE Trans. Biomed. Eng. 59(5): 1205-1218 (2012) - [j21]Andrew Janowczyk, Sharat Chandran, Rajendra Singh, Dimitra Sasaroli, George Coukos, Michael D. Feldman, Anant Madabhushi:
High-Throughput Biomarker Segmentation on Ovarian Cancer Tissue Microarrays via Hierarchical Normalized Cuts. IEEE Trans. Biomed. Eng. 59(5): 1240-1252 (2012) - [j20]Sahirzeeshan Ali, Anant Madabhushi:
An Integrated Region-, Boundary-, Shape-Based Active Contour for Multiple Object Overlap Resolution in Histological Imagery. IEEE Trans. Medical Imaging 31(7): 1448-1460 (2012) - [j19]Robert Toth, Anant Madabhushi:
Multifeature Landmark-Free Active Appearance Models: Application to Prostate MRI Segmentation. IEEE Trans. Medical Imaging 31(8): 1638-1650 (2012) - [c89]James Monaco, Philipp W. Raess, Ronak Chawla, Adam Bagg, Mitchell Weiss, John Choi, Anant Madabhushi:
Image segmentation with implicit color standardization using cascaded EM: Detection of myelodysplastic syndromes. ISBI 2012: 740-743 - [c88]Rachel Sparks, Anant Madabhushi:
Gleason grading of prostate histology utilizing manifold regularization via statistical shape model of manifolds. Computer-Aided Diagnosis 2012: 83151J - [c87]Robert Toth, Jonathan Chappelow, Christoph Vetter, Oliver Kutter, Christoph Russ, Michael D. Feldman, John Tomaszewski, Natalie Shih, Anant Madabhushi:
Incorporating the whole-mount prostate histology reconstruction program Histostitcher into the extensible imaging platform (XIP) framework. Computer-Aided Diagnosis 2012: 83151K - [c86]Angel Cruz-Roa, Fabio A. González, Joseph Galaro, Alexander R. Judkins, David Ellison, Jennifer Baccon, Anant Madabhushi, Eduardo Romero:
A Visual Latent Semantic Approach for Automatic Analysis and Interpretation of Anaplastic Medulloblastoma Virtual Slides. MICCAI (1) 2012: 157-164 - [c85]James Monaco, J. Hipp, D. Lucas, S. Smith, Ulysses J. Balis, Anant Madabhushi:
Image Segmentation with Implicit Color Standardization Using Spatially Constrained Expectation Maximization: Detection of Nuclei. MICCAI (1) 2012: 365-372 - 2011
- [j18]Scott Doyle, James Monaco, Michael D. Feldman, John Tomaszewski, Anant Madabhushi:
An Active Learning Based Classification Strategy for the Minority Class Problem: Application to Histopathology Annotation. BMC Bioinform. 12: 424 (2011) - [j17]Abhishek Golugula, George Lee, Stephen R. Master, Michael D. Feldman, John Tomaszewski, David W. Speicher, Anant Madabhushi:
Supervised Regularized Canonical Correlation Analysis: integrating histologic and proteomic measurements for predicting biochemical recurrence following prostate surgery. BMC Bioinform. 12: 483 (2011) - [j16]Anant Madabhushi, Shannon Agner, Ajay Basavanhally, Scott Doyle, George Lee:
Computer-aided prognosis: Predicting patient and disease outcome via quantitative fusion of multi-scale, multi-modal data. Comput. Medical Imaging Graph. 35(7-8): 506-514 (2011) - [j15]Jonathan Chappelow, John Tomaszewski, Michael D. Feldman, Natalie Shih, Anant Madabhushi:
HistoStitcher©: An interactive program for accurate and rapid reconstruction of digitized whole histological sections from tissue fragments. Comput. Medical Imaging Graph. 35(7-8): 557-567 (2011) - [j14]Gaoyu Xiao, B. Nicolas Bloch, Jonathan Chappelow, Elizabeth Genega, Neil Rofsky, Robert E. Lenkinski, John Tomaszewski, Michael D. Feldman, Mark Rosen, Anant Madabhushi:
Determining histology-MRI slice correspondences for defining MRI-based disease signatures of prostate cancer. Comput. Medical Imaging Graph. 35(7-8): 568-578 (2011) - [j13]Shannon Agner, Salil Soman, Edward Libfeld, Margie McDonald, Kathleen Thomas, Sarah Englander, Mark A. Rosen, Deanna Chin, John L. Nosher, Anant Madabhushi:
Textural Kinetics: A Novel Dynamic Contrast-Enhanced (DCE)-MRI Feature for Breast Lesion Classification. J. Digit. Imaging 24(3): 446-463 (2011) - [j12]Robert Toth, Pallavi Tiwari, Mark Rosen, Galen Reed, John Kurhanewicz, Arjun Kalyanpur, Sona Pungavkar, Anant Madabhushi:
A magnetic resonance spectroscopy driven initialization scheme for active shape model based prostate segmentation. Medical Image Anal. 15(2): 214-225 (2011) - [j11]Jun Xu, Andrew Janowczyk, Sharat Chandran, Anant Madabhushi:
A high-throughput active contour scheme for segmentation of histopathological imagery. Medical Image Anal. 15(6): 851-862 (2011) - [j10]James Monaco, Anant Madabhushi:
Weighted Maximum Posterior Marginals for Random Fields Using an Ensemble of Conditional Densities From Multiple Markov Chain Monte Carlo Simulations. IEEE Trans. Medical Imaging 30(7): 1353-1364 (2011) - [c84]Abhishek Golugula, George Lee, Anant Madabhushi:
Evaluating feature selection strategies for high dimensional, small sample size datasets. EMBC 2011: 949-952 - [c83]Elaine Yu, James P. Monaco, John Tomaszewski, Natalie Shih, Michael D. Feldman, Anant Madabhushi:
Detection of prostate cancer on histopathology using color fractals and Probabilistic Pairwise Markov models. EMBC 2011: 3427-3430 - [c82]Joseph Galaro, Alexander R. Judkins, David Ellison, Jennifer Baccon, Anant Madabhushi:
An integrated texton and bag of words classifier for identifying anaplastic medulloblastomas. EMBC 2011: 3443-3446 - [c81]Daniel Palumbo, Brian Yee, Patrick O'Dea, Shane Leedy, Satish Viswanath, Anant Madabhushi:
Interplay between bias field correction, intensity standardization, and noise filtering for T2-weighted MRI. EMBC 2011: 5080-5083 - [c80]Pratik Patel, Jonathan Chappelow, John Tomaszewski, Michael D. Feldman, Mark Rosen, Natalie Shih, Anant Madabhushi:
Spatially weighted mutual information (SWMI) for registration of digitally reconstructed ex vivo whole mount histology and in vivo prostate MRI. EMBC 2011: 6269-6272 - [c79]Abhishek Golugula, George Lee, Stephen R. Master, Michael D. Feldman, John E. Tomaszewski, Anant Madabhushi:
Supervised regularized canonical correlation analysis: Integrating histologic and proteomic data for predicting biochemical failures. EMBC 2011: 6434-6437 - [c78]Ajay Basavanhally, Shridar Ganesan, Natalie Shih, Carolyn Mies, Michael D. Feldman, John Tomaszewski, Anant Madabhushi:
A boosted classifier for integrating multiple fields of view: Breast cancer grading in histopathology. ISBI 2011: 125-128 - [c77]Pallavi Tiwari, Satish Viswanath, George Lee, Anant Madabhushi:
Multi-modal data fusion schemes for integrated classification of imaging and non-imaging biomedical data. ISBI 2011: 165-168 - [c76]Sahirzeeshan Ali, Anant Madabhushi:
Active Contour for Overlap Resolution using Watershed BASED initialization (ACOReW): Applications to histopathology. ISBI 2011: 614-617 - [c75]Scott Doyle, Michael D. Feldman, John Tomaszewski, Natalie Shih, Anant Madabhushi:
Cascaded multi-class pairwise classifier (CascaMPa) for normal, cancerous, and cancer confounder classes in prostate histology. ISBI 2011: 715-718 - [c74]Rachel Sparks, Anant Madabhushi:
Out-of-sample extrapolation using semi-supervised manifold learning (OSE-SSL): Content-based image retrieval for prostate histology grading. ISBI 2011: 734-737 - [c73]Robert Toth, Rachel Sparks, Anant Madabhushi:
Medial axis based statistical shape model (MASSM): Applications to 3D prostate segmentation on MRI. ISBI 2011: 1463-1466 - [c72]Akshay Sridhar, Scott Doyle, Anant Madabhushi:
Boosted Spectral Embedding (BoSE): Applications to content-based image retrieval of histopathology. ISBI 2011: 1897-1900 - [c71]Satish Viswanath, Pallavi Tiwari, Jonathan Chappelow, Robert Toth, John Kurhanewicz, Anant Madabhushi:
CADOnc ©: An integrated toolkit for evaluating radiation therapy related changes in the prostate using multiparametric MRI. ISBI 2011: 2095-2098 - [c70]Satish Viswanath, B. Nicolas Bloch, Jonathan Chappelow, Pratik Patel, Neil Rofsky, Robert E. Lenkinski, Elizabeth Genega, Anant Madabhushi:
Enhanced multi-protocol analysis via intelligent supervised embedding (EMPrAvISE): detecting prostate cancer on multi-parametric MRI. Computer-Aided Diagnosis 2011: 79630U - [c69]Satish Viswanath, Daniel Palumbo, Jonathan Chappelow, Pratik Patel, B. Nicolas Bloch, Neil Rofsky, Robert E. Lenkinski, Elizabeth Genega, Anant Madabhushi:
Empirical evaluation of bias field correction algorithms for computer-aided detection of prostate cancer on T2w MRI. Computer-Aided Diagnosis 2011: 79630V - [c68]Shannon Agner, Jun Xu, Mark Rosen, Sudha Karthigeyan, Sarah Englander, Anant Madabhushi:
Spectral embedding based active contour (SEAC): application to breast lesion segmentation on DCE-MRI. Computer-Aided Diagnosis 2011: 796305 - [c67]Ajay Basavanhally, Elaine Yu, Jun Xu, Shridar Ganesan, Michael D. Feldman, John Tomaszewski, Anant Madabhushi:
Incorporating domain knowledge for tubule detection in breast histopathology using O'Callaghan neighborhoods. Computer-Aided Diagnosis 2011: 796310 - [c66]Najeeb Chowdhury, Jonathan Chappelow, Robert Toth, Sung Kim, Stephen Hahn, Neha Vapiwala, Haibo Lin, Stefan Both, Anant Madabhushi:
Linked statistical shape models for multi-modal segmentation: application to prostate CT-MR segmentation in radiotherapy planning. Computer-Aided Diagnosis 2011: 796314 - [c65]Gaoyu Xiao, Anant Madabhushi:
Aggregated Distance Metric Learning (ADM) for Image Classification in Presence of Limited Training Data. MICCAI (3) 2011: 33-40 - [c64]Pallavi Tiwari, Satish Viswanath, John Kurhanewicz, Anant Madabhushi:
Weighted Combination of Multi-Parametric MR Imaging Markers for Evaluating Radiation Therapy Related Changes in the Prostate. Prostate Cancer Imaging 2011: 80-91 - [c63]Shoshana Ginsburg, Pallavi Tiwari, John Kurhanewicz, Anant Madabhushi:
Variable Ranking with PCA: Finding Multiparametric MR Imaging Markers for Prostate Cancer Diagnosis and Grading. Prostate Cancer Imaging 2011: 146-157 - [c62]Sahirzeeshan Ali, Robert Veltri, Jonathan I. Epstein, Christhunesa Christudass, Anant Madabhushi:
Adaptive Energy Selective Active Contour with Shape Priors for Nuclear Segmentation and Gleason Grading of Prostate Cancer. MICCAI (1) 2011: 661-669 - [c61]Rachel Sparks, Anant Madabhushi:
Content-based image retrieval utilizing explicit shape descriptors: applications to breast MRI and prostate histopathology. Image Processing 2011: 79621I - [c60]Sahirzeeshan Ali, Anant Madabhushi:
Segmenting multiple overlapping objects via a hybrid active contour model incorporating shape priors: applications to digital pathology. Image Processing 2011: 79622W - [c59]Andrew Janowczyk, Sharat Chandran, Michael D. Feldman, Anant Madabhushi:
Local morphologic scale: application to segmenting tumor infiltrating lymphocytes in ovarian cancer TMAs. Image Processing 2011: 79622N - [c58]Robert Toth, Julie Bulman, Amish D. Patel, B. Nicolas Bloch, Elizabeth Genega, Neil Rofsky, Robert E. Lenkinski, Anant Madabhushi:
Integrating an adaptive region-based appearance model with a landmark-free statistical shape model: application to prostate MRI segmentation. Image Processing 2011: 79622V - [e2]Anant Madabhushi, Jason Dowling, Henkjan J. Huisman, Dean C. Barratt:
Prostate Cancer Imaging. Image Analysis and Image-Guided Interventions - International Workshop, Held in Conjunction with MICCAI 2011, Toronto, Canada, September 22, 2011. Proceedings. Lecture Notes in Computer Science 6963, Springer 2011, ISBN 978-3-642-23943-4 [contents] - 2010
- [j9]James Monaco, John Tomaszewski, Michael D. Feldman, Ian S. Hagemann, Mehdi Moradi, Parvin Mousavi, Alexander Boag, Chris Davidson, Purang Abolmaesumi, Anant Madabhushi:
High-throughput detection of prostate cancer in histological sections using probabilistic pairwise Markov models. Medical Image Anal. 14(4): 617-629 (2010) - [j8]Ajay Basavanhally, Shridar Ganesan, Shannon Agner, James Monaco, Michael D. Feldman, John Tomaszewski, Gyan Bhanot, Anant Madabhushi:
Computerized Image-Based Detection and Grading of Lymphocytic Infiltration in HER2+ Breast Cancer Histopathology. IEEE Trans. Biomed. Eng. 57(3): 642-653 (2010) - [j7]Hussain Fatakdawala, Jun Xu, Ajay Basavanhally, Gyan Bhanot, Shridar Ganesan, Michael D. Feldman, John Tomaszewski, Anant Madabhushi:
Expectation-Maximization-Driven Geodesic Active Contour With Overlap Resolution (EMaGACOR): Application to Lymphocyte Segmentation on Breast Cancer Histopathology. IEEE Trans. Biomed. Eng. 57(7): 1676-1689 (2010) - [c57]Metin N. Gurcan, Anant Madabhushi, Nasir M. Rajpoot:
Pattern Recognition in Histopathological Images: An ICPR 2010 Contest. ICPR Contests 2010: 226-234 - [c56]Ajay Basavanhally, Scott Doyle, Anant Madabhushi:
Predicting classifier performance with a small training set: applications to computer-aided diagnosis and prognosis. ISBI 2010: 229-232 - [c55]Jonathan Chappelow, Anant Madabhushi:
Multi-attribute combined mutual information (MACMI): an image registration framework for leveraging multiple data channels. ISBI 2010: 376-379 - [c54]Rachel Sparks, Robert Toth, Jonathan Chappelow, Gaoyu Xiao, Anant Madabhushi:
An integrated framework for analyzing three-dimensional shape differences: evaluating prostate morphometry. ISBI 2010: 1081-1084 - [c53]Scott Doyle, James Monaco, Anant Madabhushi, Stefan Lindholm, Patric Ljung, Lance Ladic, John Tomaszewski, Michael D. Feldman:
Evaluation of effects of jpeg2000 compression on a computer-aided detection system for prostate cancer on digitized histopathology. ISBI 2010: 1313-1316 - [c52]Anant Madabhushi, Ajay Basavanhally, Scott Doyle, Shannon Agner, George Lee:
Computer-aided prognosis: predicting patient and disease outcome via multi-modal image analysis. ISBI 2010: 1415-1418 - [c51]Jun Xu, Rachel Sparks, Andrew Janowczyk, John E. Tomaszewski, Michael D. Feldman, Anant Madabhushi:
High-Throughput Prostate Cancer Gland Detection, Segmentation, and Classification from Digitized Needle Core Biopsies. Prostate Cancer Imaging 2010: 77-88 - [c50]Jun Xu, James Monaco, Anant Madabhushi:
Markov Random Field driven Region-Based Active Contour Model (MaRACel): Application to Medical Image Segmentation. MICCAI (3) 2010: 197-204 - [c49]Rachel Sparks, Anant Madabhushi:
Novel Morphometric Based Classification via Diffeomorphic Based Shape Representation Using Manifold Learning. MICCAI (3) 2010: 658-665 - [c48]Pallavi Tiwari, John Kurhanewicz, Mark Rosen, Anant Madabhushi:
Semi Supervised Multi Kernel (SeSMiK) Graph Embedding: Identifying Aggressive Prostate Cancer via Magnetic Resonance Imaging and Spectroscopy. MICCAI (3) 2010: 666-673 - [c47]Jonathan Chappelow, Stefan Both, Satish Viswanath, Stephen Hahn, Michael D. Feldman, Mark Rosen, John Tomaszewski, Neha Vapiwala, Pratik Patel, Anant Madabhushi:
Computer-assisted targeted therapy (CATT) for prostate radiotherapy planning by fusion of CT and MRI. Image-Guided Procedures 2010: 76252C - [c46]Jun Xu, Andrew Janowczyk, Sharat Chandran, Anant Madabhushi:
A weighted mean shift, normalized cuts initialized color gradient based geodesic active contour model: applications to histopathology image segmentation. Image Processing 2010: 76230Y - [c45]Gaoyu Xiao, B. Nicolas Bloch, Jonathan Chappelow, Elizabeth Genega, Neil Rofsky, Robert E. Lenkinski, Anant Madabhushi:
A structural-functional MRI-based disease atlas: application to computer-aided-diagnosis of prostate cancer. Image Processing 2010: 762303 - [c44]George Lee, Anant Madabhushi:
Semi-Supervised Graph Embedding Scheme with Active Learning (SSGEAL): Classifying High Dimensional Biomedical Data. PRIB 2010: 207-218 - [c43]Scott Doyle, Anant Madabhushi:
Consensus of Ambiguity: Theory and Application of Active Learning for Biomedical Image Analysis. PRIB 2010: 313-324 - [e1]Anant Madabhushi, Jason Dowling, Pingkun Yan, Aaron Fenster, Purang Abolmaesumi, Nobuhiko Hata:
Prostate Cancer Imaging. Computer-Aided Diagnosis, Prognosis, and Intervention - International Workshop, Held in Conjunction with MICCAI 2010, Beijing, China, September 24, 2010. Proceedings. Lecture Notes in Computer Science 6367, Springer 2010, ISBN 978-3-642-15988-6 [contents]
2000 – 2009
- 2009
- [c42]Hussain Fatakdawala, Ajay Basavanhally, Jun Xu, Gyan Bhanot, Shridar Ganesan, Michael D. Feldman, John Tomaszewski, Anant Madabhushi:
Expectation Maximization driven Geodesic Active Contour with Overlap Resolution (EMaGACOR): Application to Lymphocyte Segmentation on Breast Cancer Histopathology. BIBE 2009: 69-76 - [c41]Amod Jog, Aniruddha J. Joshi, Sharat Chandran, Anant Madabhushi:
Classifying Ayurvedic Pulse Signals Via Consensus Locally Linear Embedding. BIOSIGNALS 2009: 388-395 - [c40]George Lee, Scott Doyle, James Monaco, Michael D. Feldman, Stephen R. Master, John Tomaszewski, Anant Madabhushi:
A Knowledge Representation Framework for Integration, Classification of Multi-Scale Imaging and Non-Imaging Data: Preliminary Results in Predicting Prostate Cancer Recurrence by Fusing Mass Spectrometry and Histology. ISBI 2009: 77-80 - [c39]Ajay Basavanhally, Jun Xu, Shridar Ganesan, Anant Madabhushi:
Computer-Aided Prognosis of ER+ Breast Cancer Histopathology and Correlating Survival Outcome with Oncotype DX Assay. ISBI 2009: 851-854 - [c38]Shannon Agner, Jun Xu, Hussain Fatakdawala, Shridar Ganesan, Anant Madabhushi, Sarah Englander, Mark Rosen, Kathleen Thomas, Mitchell D. Schnall, Michael D. Feldman, John Tomaszewski:
Segmentation and Classification of Triple Negative Breast Cancers Using DCE-MRI. ISBI 2009: 1227-1230 - [c37]Jay Naik, Scott Doyle, Ajay Basavanhally, Shridar Ganesan, Michael D. Feldman, John E. Tomaszewski, Anant Madabhushi:
A boosted distance metric: application to content based image retrieval and classification of digitized histopathology. Computer-Aided Diagnosis 2009: 72603F - [c36]Satish Viswanath, B. Nicolas Bloch, Mark Rosen, Jonathan Chappelow, Robert Toth, Neil Rofsky, Robert E. Lenkinski, Elizabeth Genega, Arjun Kalyanpur, Anant Madabhushi:
Integrating structural and functional imaging for computer assisted detection of prostate cancer on multi-protocol in vivo 3 Tesla MRI. Computer-Aided Diagnosis 2009: 72603I - [c35]Andrew Janowczyk, Sharat Chandran, Rajendra Singh, Dimitra Sasaroli, George Coukos, Michael D. Feldman, Anant Madabhushi:
Hierarchical Normalized Cuts: Unsupervised Segmentation of Vascular Biomarkers from Ovarian Cancer Tissue Microarrays. MICCAI (1) 2009: 230-238 - [c34]Pallavi Tiwari, Mark Rosen, Galen Reed, John Kurhanewicz, Anant Madabhushi:
Spectral Embedding Based Probabilistic Boosting Tree (ScEPTre): Classifying High Dimensional Heterogeneous Biomedical Data. MICCAI (1) 2009: 844-851 - [c33]Jonathan Chappelow, B. Nicolas Bloch, Neil Rofsky, Elizabeth Genega, Robert E. Lenkinski, William DeWolf, Satish Viswanath, Anant Madabhushi:
COLLINARUS: collection of image-derived non-linear attributes for registration using splines. Image Processing 2009: 72592N - [c32]James Monaco, John E. Tomaszewski, Michael D. Feldman, Mehdi Moradi, Parvin Mousavi, Alexander Boag, Chris Davidson, Purang Abolmaesumi, Anant Madabhushi:
Probabilistic pairwise Markov models: application to prostate cancer detection. Image Processing 2009: 725903 - [c31]Robert Toth, Scott Doyle, Mark Rosen, Arjun Kalyanpur, Sona Pungavkar, B. Nicolas Bloch, Elizabeth Genega, Neil Rofsky, Robert E. Lenkinski, Anant Madabhushi:
WERITAS: weighted ensemble of regional image textures for ASM segmentation. Image Processing 2009: 725905 - 2008
- [j6]Andre D. A. Souza, Jayaram K. Udupa, Anant Madabhushi:
Image filtering via generalized scale. Medical Image Anal. 12(2): 87-98 (2008) - [j5]George Lee, Carlos Rodriguez, Anant Madabhushi:
Investigating the Efficacy of Nonlinear Dimensionality Reduction Schemes in Classifying Gene and Protein Expression Studies. IEEE ACM Trans. Comput. Biol. Bioinform. 5(3): 368-384 (2008) - [c30]Shivang Naik, Scott Doyle, Shannon Agner, Anant Madabhushi, Michael D. Feldman, John Tomaszewski:
Automated gland and nuclei segmentation for grading of prostate and breast cancer histopathology. ISBI 2008: 284-287 - [c29]Scott Doyle, Shannon Agner, Anant Madabhushi, Michael D. Feldman, John Tomaszewski:
Automated grading of breast cancer histopathology using spectral clusteringwith textural and architectural image features. ISBI 2008: 496-499 - [c28]Jonathan Chappelow, Satish Viswanath, James Monaco, Mark Rosen, John Tomaszewski, Michael D. Feldman, Anant Madabhushi:
Improving supervised classification accuracy using non-rigid multimodal image registration: detecting prostate cancer. Computer-Aided Diagnosis 2008: 69150V - [c27]Satish Viswanath, Mark Rosen, Anant Madabhushi:
A consensus embedding approach for segmentation of high resolution in vivo prostate magnetic resonance imagery. Computer-Aided Diagnosis 2008: 69150U - [c26]Shannon C. Agner, Salil Soman, Edward Libfeld, Margie McDonald, Mark A. Rosen, Mitchell D. Schnall, Deanna Chin, John L. Nosher, Anant Madabhushi:
Novel kinetic texture features for breast lesion classification on dynamic contrast enhanced (DCE) MRI. Computer-Aided Diagnosis 2008: 69152C - [c25]Satish Viswanath, Pallavi Tiwari, Mark Rosen, Anant Madabhushi:
A meta-classifier for detecting prostate cancer by quantitative integration of in vivo magnetic resonance spectroscopy and magnetic resonance imaging. Computer-Aided Diagnosis 2008: 69153D - [c24]Pallavi Tiwari, Mark Rosen, Anant Madabhushi:
Consensus-Locally Linear Embedding (C-LLE): Application to Prostate Cancer Detection on Magnetic Resonance Spectroscopy. MICCAI (2) 2008: 330-338 - [c23]Robert Toth, Jonathan Chappelow, Mark Rosen, Sona Pungavkar, Arjun Kalyanpur, Anant Madabhushi:
Multi-Attribute Non-initializing Texture Reconstruction Based Active Shape Model (MANTRA). MICCAI (1) 2008: 653-661 - [c22]Satish Viswanath, B. Nicolas Bloch, Elizabeth Genega, Neil Rofsky, Robert E. Lenkinski, Jonathan Chappelow, Robert Toth, Anant Madabhushi:
A Comprehensive Segmentation, Registration, and Cancer Detection Scheme on 3 Tesla In VivoProstate DCE-MRI. MICCAI (1) 2008: 662-669 - [c21]Robert Toth, Pallavi Tiwari, Mark Rosen, Arjun Kalyanpur, Sona Pungavkar, Anant Madabhushi:
A multi-modal prostate segmentation scheme by combining spectral clustering and active shape models. Image Processing 2008: 69144S - 2007
- [c20]Jonathan Chappelow, Anant Madabhushi, Mark Rosen, John E. Tomaszeweski, Michael D. Feldman:
A Combined Feature Ensemble Based Mutual Information Scheme for Robust Inter-Modal, Inter-Protocol Image Registration. ISBI 2007: 644-647 - [c19]Scott Doyle, Mark I. Hwang, Kinsuk Shah, Anant Madabhushi, Michael D. Feldman, John E. Tomaszeweski:
Automated Grading of Prostate Cancer Using Architectural and Textural Image Features. ISBI 2007: 1284-1287 - [c18]George Lee, Carlos Rodriguez, Anant Madabhushi:
An Empirical Comparison of Dimensionality Reduction Methods for Classifying Gene and Protein Expression Datasets. ISBRA 2007: 170-181 - [c17]Pallavi Tiwari, Anant Madabhushi, Mark Rosen:
A Hierarchical Unsupervised Spectral Clustering Scheme for Detection of Prostate Cancer from Magnetic Resonance Spectroscopy (MRS). MICCAI (2) 2007: 278-286 - [c16]Jonathan Chappelow, Anant Madabhushi, Mark Rosen, John E. Tomaszeweski, Michael D. Feldman:
Multimodal image registration of ex vivo 4 Tesla MRI with whole mount histology for prostate cancer detection. Image Processing 2007: 65121S - 2006
- [j4]Anant Madabhushi, Jayaram K. Udupa, Andre D. A. Souza:
Generalized scale: Theory, algorithms, and application to image inhomogeneity correction. Comput. Vis. Image Underst. 101(2): 100-121 (2006) - [c15]Anant Madabhushi, Jianbo Shi, Michael D. Feldman, Mark Rosen, John Tomaszewski:
Comparing Ensembles of Learners: Detecting Prostate Cancer from High Resolution MRI. CVAMIA 2006: 25-36 - [c14]Anant Madabhushi, Peng Yang, Mark Rosen, Susan Weinstein:
Distinguishing Lesions from Posterior Acoustic Shadowing in Breast Ultrasound via Non-Linear Dimensionality Reduction. EMBC 2006: 3070-3073 - [c13]Scott Doyle, Carlos Rodriguez, Anant Madabhushi, John E. Tomaszewski, Michael D. Feldman:
Detecting Prostatic Adenocarcinoma From Digitized Histology Using a Multi-Scale Hierarchical Classification Approach. EMBC 2006: 4759-4762 - [c12]Yunfeng Wu, Cong Wang, Sin Chun Ng, Anant Madabhushi, Yixin Zhong:
Breast Cancer Diagnosis Using Neural-Based Linear Fusion Strategies. ICONIP (3) 2006: 165-175 - [c11]Scott Doyle, Anant Madabhushi, Michael D. Feldman, John E. Tomaszeweski:
A Boosting Cascade for Automated Detection of Prostate Cancer from Digitized Histology. MICCAI (2) 2006: 504-511 - 2005
- [j3]Anant Madabhushi, Jayaram K. Udupa:
Interplay between intensity standardization and inhomogeneity correction in MR image processing. IEEE Trans. Medical Imaging 24(5): 561-576 (2005) - [j2]Anant Madabhushi, Michael D. Feldman, Dimitris N. Metaxas, John E. Tomaszeweski, Deborah Chute:
Automated detection of prostatic adenocarcinoma from high-resolution ex vivo MRI. IEEE Trans. Medical Imaging 24(12): 1611-1625 (2005) - [c10]Anant Madabhushi, Jianbo Shi, Mark Rosen, John E. Tomaszeweski, Michael D. Feldman:
Graph Embedding to Improve Supervised Classification and Novel Class Detection: Application to Prostate Cancer. MICCAI 2005: 729-737 - [c9]Anant Madabhushi, Jayaram K. Udupa:
New methods of MR image intensity standardization via generalized scale. Image Processing 2005 - [c8]Anant Madabhushi, Jayaram K. Udupa, Andre D. A. Souza:
Generalized ball-scale: theory, algorithms, and application to image inhomogeneity correction. Image Processing 2005 - [c7]Andre D. A. Souza, Jayaram K. Udupa, Anant Madabhushi:
Generalized scale-based image filtering. Image Processing 2005 - 2004
- [c6]Anant Madabhushi, Jayaram K. Udupa, Andre D. A. Souza:
Generalized scale: theory, algorithms, and application to image inhomogeneity correction. Image Processing 2004 - 2003
- [j1]Anant Madabhushi, Dimitris N. Metaxas:
Combining Low, High-Level and Empirical Domain Specific Knowledge for Automated Segmentation of Ultrasonic Breast Lesions. IEEE Trans. Medical Imaging 22(2): 155-169 (2003) - [c5]Anant Madabhushi, Michael D. Feldman, Dimitris N. Metaxas, Deborah Chute, John E. Tomaszeweski:
A Novel Stochastic Combination of 3D Texture Features for Automated Segmentation of Prostatic Adenocarcinoma from High Resolution MRI. MICCAI (1) 2003: 581-591 - [c4]Anant Madabhushi, Jayaram K. Udupa:
The interplay between intensity standardization and field inhomogeneity correction in MR image processing. Image Processing 2003 - 2002
- [c3]Anant Madabhushi, Dimitris N. Metaxas:
Automatic boundary extraction of ultrasonic breast lesions. ISBI 2002: 601-604 - [c2]Guo-Qing Wei, Anant Madabhushi, Jian Zhong Qian, John C. Engdahl:
Automatic quantification of liver-heart cross-talk for quality assessment in SPECT myocardial perfusion imaging. Image Processing 2002 - 2000
- [c1]Anant Madabhushi, J. K. Aggarwal:
Using Head Movement to Recognize Activity. ICPR 2000: 4698-4701
Coauthor Index
Nathaniel Braman
aka: Nathaniel M. Braman
aka: Nathaniel M. Braman
[j49] [c131] [p1] [j38] [j36] [c119] [c114] [c113] [c111] [j27] [c108] [c97] [j25] [j22] [j21] [c87] [j18] [j17] [j15] [j14] [c83] [c80] [c79] [c78] [c75] [c67] [c59] [j9] [j8] [j7] [c53] [c51] [c47] [c42] [c40] [c38] [c37] [c35] [c32] [c30] [c29] [c28] [c20] [c19] [c16] [c15] [c13] [c11] [j2] [c10] [c5]
Elizabeth Genega
aka: Elizabeth M. Genega
aka: Elizabeth M. Genega
Fabio A. González 0001
aka: Fabio Augusto González Osorio
aka: Fabio Augusto González Osorio
James Monaco
aka: James P. Monaco
aka: James P. Monaco
Neil Rofsky
aka: Neil M. Rofsky
aka: Neil M. Rofsky
Eduardo Romero 0001
aka: Edgar Eduardo Romero Castro
aka: Edgar Eduardo Romero Castro
Mark Rosen
aka: Mark A. Rosen
aka: Mark A. Rosen
Tim Salcudean
aka: Septimiu E. Salcudean
aka: Septimiu E. Salcudean
Natalie Shih
aka: Natalie N. C. Shih
aka: Natalie N. C. Shih
Satish Viswanath
aka: Satish E. Viswanath
aka: Satish E. Viswanath
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