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2020 – today
- 2024
[i8]Gabriele Campanella, Eugene Fluder, Jennifer Zeng, Chad M. Vanderbilt, Thomas J. Fuchs:
Beyond Multiple Instance Learning: Full Resolution All-In-Memory End-To-End Pathology Slide Modeling. CoRR abs/2403.04865 (2024)- [i7]Gabriele Campanella, Shengjia Chen
, Ruchika Verma, Jennifer Zeng, Aryeh Stock, Matt Croken, Brandon Veremis, Abdulkadir Elmas, Kuan-Lin Huang, Ricky Kwan, Jane Houldsworth, Adam Schoenfeld, Chad M. Vanderbilt:
A Clinical Benchmark of Public Self-Supervised Pathology Foundation Models. CoRR abs/2407.06508 (2024) - [i6]Shengjia Chen, Gabriele Campanella, Abdulkadir Elmas, Aryeh Stock, Jennifer Zeng, Alexandros D. Polydorides, Adam Schoenfeld, Kuan-Lin Huang, Jane Houldsworth, Chad M. Vanderbilt, Thomas J. Fuchs:
Benchmarking Embedding Aggregation Methods in Computational Pathology: A Clinical Data Perspective. CoRR abs/2407.07841 (2024) - 2023
- [i5]Gabriele Campanella, Ricky Kwan, Eugene Fluder, Jennifer Zeng, Aryeh Stock, Brandon Veremis, Alexandros D. Polydorides, Cyrus Hedvat, Adam Schoenfeld, Chad M. Vanderbilt, Patricia H. Kovatch, Carlos Cordon-Cardo, Thomas J. Fuchs:
Computational Pathology at Health System Scale - Self-Supervised Foundation Models from Three Billion Images. CoRR abs/2310.07033 (2023) - 2022
- [i4]David Joon Ho, M. Herman Chui, Chad M. Vanderbilt, Ji Won Jung, Mark E. Robson, Chan-Sik Park, Jin Roh, Thomas J. Fuchs:
Deep Interactive Learning-based ovarian cancer segmentation of H&E-stained whole slide images to study morphological patterns of BRCA mutation. CoRR abs/2203.15015 (2022) - [i3]Gabriele Campanella, David Joon Ho, Ida Häggström, Anton S. Becker, Jason Chang, Chad M. Vanderbilt, Thomas J. Fuchs:
H&E-based Computational Biomarker Enables Universal EGFR Screening for Lung Adenocarcinoma. CoRR abs/2206.10573 (2022) - [i2]David Joon Ho, Narasimhan P. Agaram, Marc-Henri Jean, Stephanie D. Suser, Cynthia Chu, Chad M. Vanderbilt, Paul A. Meyers, Leonard H. Wexler, John H. Healey, Thomas J. Fuchs, Meera R. Hameed:
Deep Learning-Based Objective and Reproducible Osteosarcoma Chemotherapy Response Assessment and Outcome Prediction. CoRR abs/2208.04910 (2022) - 2021
- [j1]Peter J. Schüffler, Luke Geneslaw, Dig Vijay Kumar Yarlagadda, Matthew G. Hanna, Jennifer Samboy, Evangelos Stamelos, Chad M. Vanderbilt, John Philip, Marc-Henri Jean, Lorraine Corsale, Allyne Manzo, Neeraj H. G. Paramasivam, John S. Ziegler, Jianjiong Gao, Juan C. Perin, Young Suk Kim, Umeshkumar K. Bhanot, Michael H. A. Roehrl, Orly Ardon, Sarah Chiang, Dilip D. Giri, Carlie S. Sigel, Lee K. Tan, Melissa Murray, Christina Virgo, Christine England, Yukako Yagi, S. Joseph Sirintrapun, David S. Klimstra, Meera R. Hameed, Victor E. Reuter, Thomas J. Fuchs:
Integrated digital pathology at scale: A solution for clinical diagnostics and cancer research at a large academic medical center. J. Am. Medical Informatics Assoc. 28(9): 1874-1884 (2021) - [c4]Chao Feng, Chad M. Vanderbilt, Thomas J. Fuchs:
Nuc2Vec: Learning Representations of Nuclei in Histopathology Images with Contrastive Loss. MIDL 2021: 179-189 - 2020
- [c3]David Joon Ho, Narasimhan P. Agaram, Peter J. Schüffler, Chad M. Vanderbilt, Marc-Henri Jean, Meera R. Hameed, Thomas J. Fuchs:
Deep Interactive Learning: An Efficient Labeling Approach for Deep Learning-Based Osteosarcoma Treatment Response Assessment. MICCAI (5) 2020: 540-549 - [c2]Chensu Xie, Hassan Muhammad, Chad M. Vanderbilt, Raul Caso, Dig Vijay Kumar Yarlagadda, Gabriele Campanella, Thomas J. Fuchs:
Beyond Classification: Whole Slide Tissue Histopathology Analysis By End-To-End Part Learning. MIDL 2020: 843-856 - [i1]David Joon Ho, Narasimhan P. Agaram, Peter J. Schüffler, Chad M. Vanderbilt, Marc-Henri Jean, Meera R. Hameed, Thomas J. Fuchs:
Deep Interactive Learning: An Efficient Labeling Approach for Deep Learning-Based Osteosarcoma Treatment Response Assessment. CoRR abs/2007.01383 (2020)
2010 – 2019
- 2019
- [c1]Chensu Xie, Chad M. Vanderbilt, Anne Grabenstetter, Thomas J. Fuchs:
VOCA: Cell Nuclei Detection In Histopathology Images By Vector Oriented Confidence Accumulation. MIDL 2019: 527-539
Coauthor Index
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