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ORCID20. MICCAI 2017: Quebec City, QC, Canada
- Maxime Descoteaux, Lena Maier-Hein, Alfred M. Franz, Pierre Jannin, D. Louis Collins, Simon Duchesne
:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2017 - 20th International Conference, Quebec City, QC, Canada, September 11-13, 2017, Proceedings, Part III. Lecture Notes in Computer Science 10435, Springer 2017, ISBN 978-3-319-66178-0
Feature Extraction and Classification Techniques
- Mingxia Liu, Jun Zhang, Ehsan Adeli, Dinggang Shen:
Deep Multi-task Multi-channel Learning for Joint Classification and Regression of Brain Status. 3-11 - Pin Zhang, Bibo Shi, Charles D. Smith, Jundong Liu:
Nonlinear Feature Space Transformation to Improve the Prediction of MCI to AD Conversion. 12-20 - Nitin Kumar, Ajit V. Rajwade, Sharat Chandran, Suyash P. Awate:
Kernel Generalized-Gaussian Mixture Model for Robust Abnormality Detection. 21-29 - Christian Wachinger, Anna Rieckmann, Martin Reuter:
Latent Processes Governing Neuroanatomical Change in Aging and Dementia. 30-37 - Benjamín Gutiérrez, Loïc Peter, Tassilo Klein, Christian Wachinger:
A Multi-armed Bandit to Smartly Select a Training Set from Big Medical Data. 38-45 - Mingliang Wang, Xiaoke Hao, Jiashuang Huang, Kangcheng Wang, Xijia Xu, Daoqiang Zhang:
Multi-level Multi-task Structured Sparse Learning for Diagnosis of Schizophrenia Disease. 46-54 - Li Zhang, Dana Cobzas, Alan H. Wilman, Linglong Kong:
An Unbiased Penalty for Sparse Classification with Application to Neuroimaging Data. 55-63 - Yun Gu, Khushi Vyas, Jie Yang, Guang-Zhong Yang:
Unsupervised Feature Learning for Endomicroscopy Image Retrieval. 64-71 - Xiaofeng Zhu, Kim-Han Thung, Ehsan Adeli, Yu Zhang, Dinggang Shen:
Maximum Mean Discrepancy Based Multiple Kernel Learning for Incomplete Multimodality Neuroimaging Data. 72-80 - John Treilhard, Susanne Smolka, Lawrence H. Staib, Julius Chapiro, Ming De Lin, Georgy Shakirin, James S. Duncan:
Liver Tissue Classification in Patients with Hepatocellular Carcinoma by Fusing Structured and Rotationally Invariant Context Representation. 81-88 - Yawen Huang, Ling Shao, Alejandro F. Frangi:
DOTE: Dual cOnvolutional filTer lEarning for Super-Resolution and Cross-Modality Synthesis in MRI. 89-98 - Yang Song, Hang Chang, Heng Huang, Weidong Cai:
Supervised Intra-embedding of Fisher Vectors for Histopathology Image Classification. 99-106 - Xinwei Sun, Lingjing Hu, Yuan Yao, Yizhou Wang:
GSplit LBI: Taming the Procedural Bias in Neuroimaging for Disease Prediction. 107-115 - Gabriele Abbati, Stefan Bauer, Sebastian Winklhofer, Peter J. Schüffler, Ulrike Held, Jakob M. Burgstaller, Johann Steurer, Joachim M. Buhmann:
MRI-Based Surgical Planning for Lumbar Spinal Stenosis. 116-124 - Rui Li, Ping Wu, Igor Yakushev, Jian Wang, Sibylle Ilse Ziegler, Stefan Förster, Sung-Cheng Huang, Markus Schwaiger, Nassir Navab, Chuantao Zuo, Kuangyu Shi:
Pattern Visualization and Recognition Using Tensor Factorization for Early Differential Diagnosis of Parkinsonism. 125-133 - Sebastian J. Wirkert, Anant Suraj Vemuri, Hannes Götz Kenngott, Sara Moccia, Michael Götz, Benjamin F. B. Mayer, Klaus H. Maier-Hein, Daniel S. Elson, Lena Maier-Hein:
Physiological Parameter Estimation from Multispectral Images Unleashed. 134-141 - Mário João Fartaria, Alexis Roche, Reto Meuli, Cristina Granziera, Tobias Kober, Meritxell Bach Cuadra:
Segmentation of Cortical and Subcortical Multiple Sclerosis Lesions Based on Constrained Partial Volume Modeling. 142-149 - Konstantin Dmitriev, Arie E. Kaufman, Ammar A. Javed, Ralph H. Hruban, Elliot K. Fishman, Anne Marie Lennon, Joel H. Saltz:
Classification of Pancreatic Cysts in Computed Tomography Images Using a Random Forest and Convolutional Neural Network Ensemble. 150-158 - Dajiang Zhu, Brandalyn C. Riedel, Neda Jahanshad, Nynke A. Groenewold, Dan J. Stein, Ian H. Gotlib, Matthew D. Sacchet, Danai Dima, James H. Cole, Cynthia H. Y. Fu, Henrik Walter, Ilya M. Veer, Thomas Frodl, Lianne Schmaal, Dick J. Veltman, Paul M. Thompson:
Classification of Major Depressive Disorder via Multi-site Weighted LASSO Model. 159-167 - Hongzhi Wang, Mehdi Moradi, Yaniv Gur, Prasanth Prasanna, Tanveer F. Syeda-Mahmood:
A Multi-atlas Approach to Region of Interest Detection for Medical Image Classification. 168-176 - Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero Moreno, Ben Glocker, Daniel Rueckert:
Spectral Graph Convolutions for Population-Based Disease Prediction. 177-185 - Andrew Doyle, Doina Precup, Douglas L. Arnold, Tal Arbel:
Predicting Future Disease Activity and Treatment Responders for Multiple Sclerosis Patients Using a Bag-of-Lesions Brain Representation. 186-194 - Peng Cao, Xiaoli Liu, Jinzhu Yang, Dazhe Zhao, Osmar R. Zaïane:
Sparse Multi-kernel Based Multi-task Learning for Joint Prediction of Clinical Scores and Biomarker Identification in Alzheimer's Disease. 195-202
Machine Learning in Medical Image Computing
- Yingying Zhu, Minjeong Kim, Xiaofeng Zhu, Jin Yan, Daniel Kaufer, Guorong Wu:
Personalized Diagnosis for Alzheimer's Disease. 205-213 - Florian Dubost, Gerda Bortsova, Hieab Adams, Mohammad Arfan Ikram, Wiro J. Niessen, Meike W. Vernooij, Marleen de Bruijne:
GP-Unet: Lesion Detection from Weak Labels with a 3D Regression Network. 214-221 - Yuyin Zhou, Lingxi Xie, Elliot K. Fishman, Alan L. Yuille:
Deep Supervision for Pancreatic Cyst Segmentation in Abdominal CT Scans. 222-230 - Abhijit Guha Roy, Sailesh Conjeti, Debdoot Sheet, Amin Katouzian, Nassir Navab, Christian Wachinger:
Error Corrective Boosting for Learning Fully Convolutional Networks with Limited Data. 231-239 - Chenchu Xu, Lei Xu, Zhifan Gao, Shen Zhao, Heye Zhang, Yanping Zhang, Xiuquan Du, Shu Zhao, Dhanjoo N. Ghista, Shuo Li:
Direct Detection of Pixel-Level Myocardial Infarction Areas via a Deep-Learning Algorithm. 240-249 - Zongyuan Ge, Sergey Demyanov, Rajib Chakravorty, Adrian Bowling, Rahil Garnavi:
Skin Disease Recognition Using Deep Saliency Features and Multimodal Learning of Dermoscopy and Clinical Images. 250-258 - Cheng Bian, Ran Lee, Yi-Hong Chou, Jie-Zhi Cheng:
Boundary Regularized Convolutional Neural Network for Layer Parsing of Breast Anatomy in Automated Whole Breast Ultrasound. 259-266 - Zhe Wang, Yanxin Yin, Jianping Shi, Wei Fang, Hongsheng Li, Xiaogang Wang:
Zoom-in-Net: Deep Mining Lesions for Diabetic Retinopathy Detection. 267-275 - Wufeng Xue, Andrea Lum, Ashley Mercado, Mark Landis, James Warrington, Shuo Li:
Full Quantification of Left Ventricle via Deep Multitask Learning Network Respecting Intra- and Inter-Task Relatedness. 276-284 - Lucas Fidon, Wenqi Li, Luis C. García-Peraza-Herrera, Jinendra Ekanayake, Neil Kitchen, Sébastien Ourselin, Tom Vercauteren:
Scalable Multimodal Convolutional Networks for Brain Tumour Segmentation. 285-293 - Stefanos Apostolopoulos, Sandro De Zanet, Carlos Ciller, Sebastian Wolf, Raphael Sznitman:
Pathological OCT Retinal Layer Segmentation Using Branch Residual U-Shape Networks. 294-301 - Amir H. Abdi, Christina Luong, Teresa Tsang, John Jue, Ken Gin, Darwin Yeung, Dale Hawley, Robert Rohling, Purang Abolmaesumi:
Quality Assessment of Echocardiographic Cine Using Recurrent Neural Networks: Feasibility on Five Standard View Planes. 302-310 - Christoph Baur, Shadi Albarqouni, Nassir Navab:
Semi-supervised Deep Learning for Fully Convolutional Networks. 311-319 - Zizhao Zhang, Pingjun Chen, Manish Sapkota, Lin Yang:
TandemNet: Distilling Knowledge from Medical Images Using Diagnostic Reports as Optional Semantic References. 320-328 - Mattias P. Heinrich, Ozan Oktay:
BRIEFnet: Deep Pancreas Segmentation Using Binary Sparse Convolutions. 329-337 - Zhoubing Xu, Qiangui Huang, Jin Hyeong Park, Mingqing Chen, Daguang Xu, Dong Yang, David Liu, Shaohua Kevin Zhou:
Supervised Action Classifier: Approaching Landmark Detection as Image Partitioning. 338-346 - Thomas Joyce, Agisilaos Chartsias, Sotirios A. Tsaftaris:
Robust Multi-modal MR Image Synthesis. 347-355 - Gerda Bortsova, Gijs van Tulder, Florian Dubost, Tingying Peng, Nassir Navab, Aad van der Lugt, Daniel Bos, Marleen de Bruijne:
Segmentation of Intracranial Arterial Calcification with Deeply Supervised Residual Dropout Networks. 356-364 - Emran Mohammad Abu Anas, Saman Nouranian, Seyedeh Sara Mahdavi, Ingrid Spadinger, William J. Morris, Septimiu E. Salcudean, Parvin Mousavi, Purang Abolmaesumi:
Clinical Target-Volume Delineation in Prostate Brachytherapy Using Residual Neural Networks. 365-373 - Prabhat Garg, Elizabeth M. Davenport, Gowtham Murugesan, Benjamin C. Wagner, Christopher T. Whitlow, Joseph A. Maldjian, Albert Montillo:
Using Convolutional Neural Networks to Automatically Detect Eye-Blink Artifacts in Magnetoencephalography Without Resorting to Electrooculography. 374-381 - Dwarikanath Mahapatra, Behzad Bozorgtabar, Sajini Hewavitharanage, Rahil Garnavi:
Image Super Resolution Using Generative Adversarial Networks and Local Saliency Maps for Retinal Image Analysis. 382-390 - Davood Karimi, Dan Ruan:
Synergistic Combination of Learned and Hand-Crafted Features for Prostate Lesion Classification in Multiparametric Magnetic Resonance Imaging. 391-398 - Lin Yang, Yizhe Zhang, Jianxu Chen, Siyuan Zhang, Danny Z. Chen:
Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation. 399-407 - Yizhe Zhang, Lin Yang, Jianxu Chen, Maridel Fredericksen, David P. Hughes, Danny Z. Chen:
Deep Adversarial Networks for Biomedical Image Segmentation Utilizing Unannotated Images. 408-416 - Dong Nie, Roger Trullo, Jun Lian, Caroline Petitjean, Su Ruan, Qian Wang, Dinggang Shen:
Medical Image Synthesis with Context-Aware Generative Adversarial Networks. 417-425 - Xin Yang, Zhiwei Wang, Chaoyue Liu, Hung Le Minh, Jingyu Chen, Kwang-Ting (Tim) Cheng, Liang Wang:
Joint Detection and Diagnosis of Prostate Cancer in Multi-parametric MRI Based on Multimodal Convolutional Neural Networks. 426-434 - Rahul Duggal, Anubha Gupta, Ritu Gupta, Pramit Mallick:
SD-Layer: Stain Deconvolutional Layer for CNNs in Medical Microscopic Imaging. 435-443 - Shadi Albarqouni, Javad Fotouhi, Nassir Navab:
X-Ray In-Depth Decomposition: Revealing the Latent Structures. 444-452 - Hua Ma, Pierre Ambrosini, Theo van Walsum:
Fast Prospective Detection of Contrast Inflow in X-ray Angiograms with Convolutional Neural Network and Recurrent Neural Network. 453-461 - Dhritiman Das, Eduardo Coello, Rolf F. Schulte, Bjoern H. Menze:
Quantification of Metabolites in Magnetic Resonance Spectroscopic Imaging Using Machine Learning. 462-470 - Ken C. L. Wong, Alexandros Karargyris, Tanveer F. Syeda-Mahmood, Mehdi Moradi:
Building Disease Detection Algorithms with Very Small Numbers of Positive Samples. 471-479 - Youngjin Yoo, Lisa Y. W. Tang, Su-Hyun Kim, Ho Jin Kim, Lisa Eunyoung Lee, David K. B. Li, Shannon H. Kolind, Anthony Traboulsee, Roger C. Tam:
Hierarchical Multimodal Fusion of Deep-Learned Lesion and Tissue Integrity Features in Brain MRIs for Distinguishing Neuromyelitis Optica from Multiple Sclerosis. 480-488 - Atilla P. Kiraly, Clement Abi Nader, Ahmet Tuysuzoglu, Robert Grimm, Berthold Kiefer, Noha El-Zehiry, Ali Kamen:
Deep Convolutional Encoder-Decoders for Prostate Cancer Detection and Classification. 489-497 - Dong Yang, Tao Xiong, Daguang Xu, Shaohua Kevin Zhou, Zhoubing Xu, Mingqing Chen, Jin Hyeong Park, Sasa Grbic, Trac D. Tran, Sang Peter Chin, Dimitris N. Metaxas, Dorin Comaniciu:
Deep Image-to-Image Recurrent Network with Shape Basis Learning for Automatic Vertebra Labeling in Large-Scale 3D CT Volumes. 498-506 - Dong Yang, Daguang Xu, Shaohua Kevin Zhou, Bogdan Georgescu, Mingqing Chen, Sasa Grbic, Dimitris N. Metaxas, Dorin Comaniciu:
Automatic Liver Segmentation Using an Adversarial Image-to-Image Network. 507-515 - Mohsen Ghafoorian, Alireza Mehrtash, Tina Kapur, Nico Karssemeijer, Elena Marchiori, Mehran Pesteie, Charles R. G. Guttmann, Frank-Erik de Leeuw, Clare M. Tempany, Bram van Ginneken, Andriy Fedorov, Purang Abolmaesumi, Bram Platel, William M. Wells III:
Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation. 516-524 - Ling Dai, Bin Sheng, Qiang Wu, Huating Li, Xuhong Hou, Weiping Jia, Ruogu Fang:
Retinal Microaneurysm Detection Using Clinical Report Guided Multi-sieving CNN. 525-532 - Yehui Yang, Tao Li, Wensi Li, Haishan Wu, Wei Fan, Wensheng Zhang:
Lesion Detection and Grading of Diabetic Retinopathy via Two-Stages Deep Convolutional Neural Networks. 533-540 - Sailesh Conjeti, Abhijit Guha Roy, Amin Katouzian, Nassir Navab:
Hashing with Residual Networks for Image Retrieval. 541-549 - Sailesh Conjeti, Magdalini Paschali, Amin Katouzian, Nassir Navab:
Deep Multiple Instance Hashing for Scalable Medical Image Retrieval. 550-558 - Jia Ding, Aoxue Li, Zhiqiang Hu, Liwei Wang:
Accurate Pulmonary Nodule Detection in Computed Tomography Images Using Deep Convolutional Neural Networks. 559-567 - Xinyang Feng, Jie Yang, Andrew F. Laine, Elsa D. Angelini:
Discriminative Localization in CNNs for Weakly-Supervised Segmentation of Pulmonary Nodules. 568-576 - Yixuan Yuan, Max Q.-H. Meng, Wenjian Qin, Lei Xing:
Liver Lesion Detection Based on Two-Stage Saliency Model with Modified Sparse Autoencoder. 577-585 - Felix J. S. Bragman, Jamie R. McClelland, Joseph Jacob, John R. Hurst, David J. Hawkes:
Manifold Learning of COPD. 586-593 - Guy Amit, Omer Hadad, Sharon Alpert, Tal Tlusty, Yaniv Gur, Rami Ben-Ari, Sharbell Y. Hashoul:
Hybrid Mass Detection in Breast MRI Combining Unsupervised Saliency Analysis and Deep Learning. 594-602 - Wentao Zhu, Qi Lou, Yeeleng Scott Vang, Xiaohui Xie:
Deep Multi-instance Networks with Sparse Label Assignment for Whole Mammogram Classification. 603-611 - Mohammad Arafat Hussain, Alborz Amir-Khalili, Ghassan Hamarneh, Rafeef Abugharbieh:
Segmentation-Free Kidney Localization and Volume Estimation Using Aggregated Orthogonal Decision CNNs. 612-620 - Adam P. Harrison, Ziyue Xu, Kevin George, Le Lu, Ronald M. Summers, Daniel J. Mollura:
Progressive and Multi-path Holistically Nested Neural Networks for Pathological Lung Segmentation from CT Images. 621-629 - Qi Dou, Hao Chen, Yueming Jin, Huangjing Lin, Jing Qin, Pheng-Ann Heng:
Automated Pulmonary Nodule Detection via 3D ConvNets with Online Sample Filtering and Hybrid-Loss Residual Learning. 630-638 - Andrew Jesson, Nicolas Guizard, Sina Hamidi Ghalehjegh, Damien Goblot, Florian Soudan, Nicolas Chapados:
CASED: Curriculum Adaptive Sampling for Extreme Data Imbalance. 639-646 - Mehdi Alilou, Mahdi Orooji, Anant Madabhushi:
Intra-perinodular Textural Transition (Ipris): A 3D Descriptor for Nodule Diagnosis on Lung CT. 647-655 - Yutong Xie, Yong Xia, Jianpeng Zhang, David Dagan Feng, Michael J. Fulham, Weidong Cai:
Transferable Multi-model Ensemble for Benign-Malignant Lung Nodule Classification on Chest CT. 656-664 - Gabriel Maicas, Gustavo Carneiro, Andrew P. Bradley, Jacinto C. Nascimento, Ian D. Reid:
Deep Reinforcement Learning for Active Breast Lesion Detection from DCE-MRI. 665-673 - Jinzheng Cai, Le Lu, Yuanpu Xie, Fuyong Xing, Lin Yang:
Pancreas Segmentation in MRI Using Graph-Based Decision Fusion on Convolutional Neural Networks. 674-682 - Gregory Plumb, Lindsay Clark, Sterling C. Johnson, Vikas Singh:
Modeling Cognitive Trends in Preclinical Alzheimer's Disease (AD) via Distributions over Permutations. 683-691 - Yinghuan Shi, Wanqi Yang, Yang Gao, Dinggang Shen:
Does Manual Delineation only Provide the Side Information in CT Prostate Segmentation? 692-700
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