Weakly Supervised Cell Nuclei Detection and Segmentation on Tissue Microarrays of Renal Clear Cell Carcinoma. - Thomas J. Fuchs; Tilman Lange; Peter J. Wild; Holger Moch; Joachim M. Buhmann (DAGM-Symposium, 2008)

Automatic and robust forearm segmentation using graph cuts. - Philipp Fürnstahl; Thomas J. Fuchs; Andreas Schweizer; Ladislav Nagy; Gábor Székely; Matthias Harders (ISBI, 2008)

Computational Pathology Analysis of Tissue Microarrays Predicts Survival of Renal Clear Cell Carcinoma Patients. - Thomas J. Fuchs; Peter J. Wild; Holger Moch; Joachim M. Buhmann (MICCAI (2), 2008)

Inter-active learning of randomized tree ensembles for object detection. - Thomas J. Fuchs; Joachim M. Buhmann (ICCV Workshops, 2009)

The Bayesian group-Lasso for analyzing contingency tables. - Sudhir Raman; Thomas J. Fuchs; Peter J. Wild; Edgar Dahl; Volker Roth 001 (ICML, 2009)

Randomized Tree Ensembles for Object Detection in Computational Pathology. - Thomas J. Fuchs; Johannes Haybaeck; Peter J. Wild; Mathias Heikenwalder; Holger Moch; Adriano Aguzzi; Joachim M. Buhmann (ISVC (1), 2009)

Graph-Based Pancreatic Islet Segmentation for Early Type 2 Diabetes Mellitus on Histopathological Tissue. - Xenofon E. Floros; Thomas J. Fuchs; Markus P. Rechsteiner; Giatgen Spinas; Holger Moch; Joachim M. Buhmann (MICCAI (1), 2009)

Guided review by frequent itemset mining: additional evidence for plaque detection. - Stefan C. Saur; Hatem Alkadhi; Lotus Desbiolles; Thomas J. Fuchs; Gábor Székely; Philippe C. Cattin (Int. J. Comput. Assist. Radiol. Surg., 2009)

Neuron geometry extraction by perceptual grouping in ssTEM images. - Verena Kaynig; Thomas J. Fuchs; Joachim M. Buhmann (CVPR, 2010)

Computational TMA Analysis and Cell Nucleus Classification of Renal Cell Carcinoma. - Peter J. Schüffler; Thomas J. Fuchs; Cheng Soon Ong; Volker Roth 001; Joachim M. Buhmann (DAGM-Symposium, 2010)

The Translation-invariant Wishart-Dirichlet Process for Clustering Distance Data. - Julia E. Vogt; Sandhya Prabhakaran; Thomas J. Fuchs; Volker Roth 001 (ICML, 2010)

Geometrical Consistent 3D Tracing of Neuronal Processes in ssTEM Data. - Verena Kaynig; Thomas J. Fuchs; Joachim M. Buhmann (MICCAI (2), 2010)

Infinite mixture-of-experts model for sparse survival regression with application to breast cancer. - Sudhir Raman; Thomas J. Fuchs; Peter J. Wild; Edgar Dahl; Joachim M. Buhmann; Volker Roth 001 (BMC Bioinform., 2010)

Computational pathology: Challenges and promises for tissue analysis. - Thomas J. Fuchs; Joachim M. Buhmann (Comput. Medical Imaging Graph., 2011)

Combined shape, appearance and silhouette for simultaneous manipulator and object tracking. - Paul Hebert; Nicolas Hudson; Jeremy Ma; Thomas Howard; Thomas J. Fuchs; Max Bajracharya; Joel W. Burdick (ICRA, 2012)

End-to-end dexterous manipulation with deliberate interactive estimation. - Nicolas Hudson; Thomas Howard; Jeremy Ma; Abhinandan Jain; Max Bajracharya; Steven Myint; Calvin Kuo; Larry H. Matthies; Paul Backes; Paul Hebert; Thomas J. Fuchs; Joel W. Burdick (ICRA, 2012)

Feature selection strategies for classifying high dimensional astronomical data sets. - Ciro Donalek; S. George Djorgovski; Ashish Mahabal; Matthew J. Graham; Andrew J. Drake; Arun Kumar A.; N. Sajeeth Philip; Thomas J. Fuchs; Michael J. Turmon; Michael Ting-Chang Yang; Giuseppe Longo (IEEE BigData, 2013)

Recognizing Humans in Motion: Trajectory-based Aerial Video Analysis. - Yumi Iwashita; Michael S. Ryoo; Thomas J. Fuchs; Curtis Padgett (BMVC, 2013)

Quickly Boosting Decision Trees - Pruning Underachieving Features Early. - Ron Appel; Thomas J. Fuchs; Piotr Dollár; Pietro Perona (ICML (3), 2013)

Feature Selection Strategies for Classifying High Dimensional Astronomical Data Sets. - Ciro Donalek; Arun Kumar A.; S. George Djorgovski; Ashish Mahabal; Matthew J. Graham; Thomas J. Fuchs; Michael J. Turmon; N. Sajeeth Philip; Michael Ting-Chang Yang; Giuseppe Longo (CoRR, 2013)

Structure Preserving Embedding of Dissimilarity Data. - Volker Roth 001; Thomas J. Fuchs; Julia E. Vogt; Sandhya Prabhakaran; Joachim M. Buhmann (Similarity-Based Pattern Analysis and Recognition, 2013)

Automated Analysis of Tissue Micro-Array Images on the Example of Renal Cell Carcinoma. - Peter J. Schüffler; Thomas J. Fuchs; Cheng Soon Ong; Volker Roth 001; Joachim M. Buhmann (Similarity-Based Pattern Analysis and Recognition, 2013)

Automated Real-Time Classification and Decision Making in Massive Data Streams from Synoptic Sky Surveys. - S. George Djorgovski; Ashish Mahabal; Ciro Donalek; Matthew J. Graham; Andrew J. Drake; Michael J. Turmon; Thomas J. Fuchs (eScience, 2014)

Sparse meta-Gaussian information bottleneck. - Mélanie Rey; Volker Roth 001; Thomas J. Fuchs (ICML, 2014)

Early Recognition of Human Activities from First-Person Videos Using Onset Representations. - Michael S. Ryoo; Thomas J. Fuchs; Lu Xia; J. K. Aggarwal; Larry H. Matthies (CoRR, 2014)

Robot-Centric Activity Prediction from First-Person Videos: What Will They Do to Me'. - Michael S. Ryoo; Thomas J. Fuchs; Lu Xia; Jake K. Aggarwal; Larry H. Matthies (HRI, 2015)

Machine learning approaches to analyze histological images of tissues from radical prostatectomies. - Arkadiusz Gertych; Nathan Ing; Zhaoxuan Ma; Thomas J. Fuchs; Sadri Salman; Sambit Mohanty; Sanica Bhele; Adriana Velásquez-Vacca; Mahul B. Amin; Beatrice S. Knudsen (Comput. Medical Imaging Graph., 2015)

Boosting Convolutional Features for Robust Object Proposals. - Nikolaos Karianakis; Thomas J. Fuchs; Stefano Soatto (CoRR, 2015)

Understanding Neural Networks Through Deep Visualization. - Jason Yosinski; Jeff Clune; Anh Mai Nguyen; Thomas J. Fuchs; Hod Lipson (CoRR, 2015)

DeepScope: Nonintrusive Whole Slide Saliency Annotation and Prediction from Pathologists at the Microscope. - Andrew J. Schaumberg; S. Joseph Sirintrapun; Hikmat A. Al-Ahmadie; Peter J. Schüffler; Thomas J. Fuchs (CIBB, 2016)

Mitochondria-based Renal Cell Carcinoma Subtyping: Learning from Deep vs. Flat Feature Representations. - Peter J. Schüffler; Judy Sarungbam; Hassan Muhammad; Ed Reznik; Satish K. Tickoo; Thomas J. Fuchs (MLHC, 2016)

Multi-Organ Cancer Classification and Survival Analysis. - Stefan Bauer; Nicolas Carion; Peter J. Schüffler; Thomas J. Fuchs; Peter J. Wild; Joachim M. Buhmann (CoRR, 2016)

Real-time data mining of massive data streams from synoptic sky surveys. - S. George Djorgovski; Matthew J. Graham; Ciro Donalek; Ashish Mahabal; Andrew J. Drake; Michael J. Turmon; Thomas J. Fuchs (Future Gener. Comput. Syst., 2016)

Autonomous Terrain Classification With Co- and Self-Training Approach. - Kyohei Otsu; Masahiro Ono; Thomas J. Fuchs; Ian Baldwin; Takashi Kubota (IEEE Robotics Autom. Lett., 2016)

Survival Modeling of Pancreatic Cancer with Radiology Using Convolutional Neural Networks. - Hassan Muhammad; Ida Häggström; David S. Klimstra; Thomas J. Fuchs (POCUS/BIVPCS/CuRIOUS/CPM@MICCAI, 2018)

Towards machine learned quality control: A benchmark for sharpness quantification in digital pathology. - Gabriele Campanella; Arjun R. Rajanna; Lorraine Corsale; Peter J. Schüffler; Yukako Yagi; Thomas J. Fuchs (Comput. Medical Imaging Graph., 2018)

DeepRec: A deep encoder-decoder network for directly solving the PET reconstruction inverse problem. - Ida Haeggstroem; Charles Ross Schmidtlein; Gabriele Campanella; Thomas J. Fuchs (CoRR, 2018)

Terabyte-scale Deep Multiple Instance Learning for Classification and Localization in Pathology. - Gabriele Campanella; Vitor Werneck Krauss Silva; Thomas J. Fuchs (CoRR, 2018)

Unsupervised Subtyping of Cholangiocarcinoma Using a Deep Clustering Convolutional Autoencoder. - Hassan Muhammad; Carlie S. Sigel; Gabriele Campanella; Thomas Börner; Linda M. Pak; Stefan Büttner; Jan N. M. IJzermans; Bas Groot Koerkamp; Michael Doukas; William R. Jarnagin; Amber L. Simpson; Thomas J. Fuchs (MICCAI (1), 2019)

VOCA: Cell Nuclei Detection In Histopathology Images By Vector Oriented Confidence Accumulation. - Chensu Xie; Chad M. Vanderbilt; Anne Grabenstetter; Thomas J. Fuchs (MIDL, 2019)

Towards Unsupervised Cancer Subtyping: Predicting Prognosis Using A Histologic Visual Dictionary. - Hassan Muhammad; Carlie S. Sigel; Gabriele Campanella; Thomas Börner; Linda M. Pak; Stefan Büttner; Jan N. M. IJzermans; Bas Groot Koerkamp; Michael Doukas; William R. Jarnagin; Amber L. Simpson; Thomas J. Fuchs (CoRR, 2019)

DeepPET: A deep encoder-decoder network for directly solving the PET image reconstruction inverse problem. - Ida Häggström; Charles Ross Schmidtlein; Gabriele Campanella; Thomas J. Fuchs (Medical Image Anal., 2019)

Deep Interactive Learning: An Efficient Labeling Approach for Deep Learning-Based Osteosarcoma Treatment Response Assessment. - David Joon Ho; Narasimhan P. Agaram; Peter J. Schüffler; Chad M. Vanderbilt; Marc-Henri Jean; Meera R. Hameed; Thomas J. Fuchs (MICCAI (5), 2020)

Beyond Classification: Whole Slide Tissue Histopathology Analysis By End-To-End Part Learning. - Chensu Xie; Hassan Muhammad; Chad M. Vanderbilt; Raul Caso; Dig Vijay Kumar Yarlagadda; Gabriele Campanella; Thomas J. Fuchs (MIDL, 2020)

Nuc2Vec: Learning Representations of Nuclei in Histopathology Images with Contrastive Loss. - Chao Feng; Chad M. Vanderbilt; Thomas J. Fuchs (MIDL, 2021)

EPIC-Survival: End-to-end Part Inferred Clustering for Survival Analysis, with Prognostic Stratification Boosting. - Hassan Muhammad; Chensu Xie; Carlie S. Sigel; Michael Doukas; Lindsay Alpert; Amber Lea Simpson; Thomas J. Fuchs (MIDL, 2021)

Deep Multi-Magnification Networks for multi-class breast cancer image segmentation. - David Joon Ho; Dig Vijay Kumar Yarlagadda; Timothy M. D'Alfonso; Matthew G. Hanna; Anne Grabenstetter; Peter Ntiamoah; Edi Brogi; Lee K. Tan; Thomas J. Fuchs (Comput. Medical Imaging Graph., 2021)

EPIC-Survival: End-to-end Part Inferred Clustering for Survival Analysis, Featuring Prognostic Stratification Boosting. - Hassan Muhammad; Chensu Xie; Carlie S. Sigel; Michael Doukas; Lindsay Alpert; Thomas J. Fuchs (CoRR, 2021)

Integrated digital pathology at scale: A solution for clinical diagnostics and cancer research at a large academic medical center. - 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; et al. (J. Am. Medical Informatics Assoc., 2021)

Deep Interactive Learning-based ovarian cancer segmentation of H&E-stained whole slide images to study morphological patterns of BRCA mutation. - David Joon Ho; M. Herman Chui; Chad M. Vanderbilt; Ji Won Jung; Mark E. Robson; Chan-Sik Park; Jin Roh; Thomas J. Fuchs (CoRR, 2022)

H&E-based Computational Biomarker Enables Universal EGFR Screening for Lung Adenocarcinoma. - Gabriele Campanella; David Joon Ho; Ida Häggström; Anton S. Becker; Jason Chang; Chad M. Vanderbilt; Thomas J. Fuchs (CoRR, 2022)

Deep Learning-Based Objective and Reproducible Osteosarcoma Chemotherapy Response Assessment and Outcome Prediction. - 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 (CoRR, 2022)

Deep conditional transformation models for survival analysis. - Gabriele Campanella; Lucas Kook; Ida Häggström; Torsten Hothorn; Thomas J. Fuchs (CoRR, 2022)

Joint Breast Neoplasm Detection and Subtyping using Multi-Resolution Network Trained on Large-Scale H&E Whole Slide Images with Weak Labels. - Adam Casson; Siqi Liu; Ran A. Godrich; Hamed Aghdam; Brandon Rothrock; Kasper Malfroid; Christopher Kanan; Thomas J. Fuchs (MIDL, 2023)

Virchow: A Million-Slide Digital Pathology Foundation Model. - Eugene Vorontsov; Alican Bozkurt; Adam Casson; George Shaikovski; Michal Zelechowski; Siqi Liu; Philippe Mathieu; Alexander van Eck; Donghun Lee; Julian Viret; Eric Robert; Yi Kan Wang; et al. (CoRR, 2023)

Computational Pathology at Health System Scale - Self-Supervised Foundation Models from Three Billion Images. - 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; et al. (CoRR, 2023)

Keyword-optimized Template Insertion for Clinical Information Extraction via Prompt-based Learning. - Eugenia Alleva; Isotta Landi; Leslee J. Shaw; Erwin P. Böttinger; Thomas J. Fuchs; Ipek Ensari (CoRR, 2023)

Benchmarking Embedding Aggregation Methods in Computational Pathology: A Clinical Data Perspective. - Shengjia Chen; Gabriele Campanella; Abdulkadir Elmas; Aryeh Stock; Jennifer Zeng; Alexandros D. Polydorides; Adam J. Schoenfeld; Kuan-Lin Huang; Jane Houldsworth; Chad Vanderbilt; Thomas J. Fuchs (COMPAY@MICCAI, 2024)

Beyond Multiple Instance Learning: Full Resolution All-In-Memory End-To-End Pathology Slide Modeling. - Gabriele Campanella; Eugene Fluder; Jennifer Zeng; Chad M. Vanderbilt; Thomas J. Fuchs (CoRR, 2024)

PRISM: A Multi-Modal Generative Foundation Model for Slide-Level Histopathology. - George Shaikovski; Adam Casson; Kristen Severson 001; Eric Zimmermann; Yi Kan Wang; Jeremy D. Kunz; Juan Retamero; Gerard Oakley; David S. Klimstra; Christopher Kanan; Matthew G. Hanna; Michal Zelechowski; et al. (CoRR, 2024)

Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology. - Eric Zimmermann; Eugene Vorontsov; Julian Viret; Adam Casson; Michal Zelechowski; George Shaikovski; Neil A. Tenenholtz; James Brian Hall; David S. Klimstra; Razik Yousfi; Thomas J. Fuchs; Nicoló Fusi; et al. (CoRR, 2024)

Screen Them All: High-Throughput Pan-Cancer Genetic and Phenotypic Biomarker Screening from H&E Whole Slide Images. - Yi Kan Wang; Ludmila Tydlitatova; Jeremy D. Kunz; Gerard Oakley; Ran A. Godrich; Matthew C. H. Lee; Chad Vanderbilt; Razik Yousfi; Thomas J. Fuchs; David S. Klimstra; Siqi Liu (CoRR, 2024)

PRISM2: Unlocking Multi-Modal General Pathology AI with Clinical Dialogue. - George Shaikovski; Eugene Vorontsov; Adam Casson; Julian Viret; Eric Zimmermann; Neil A. Tenenholtz; Yi Kan Wang; Jan Bernhard; Ran A. Godrich; Juan Retamero; Razik Yousfi; Nicolò Fusi; et al. (CoRR, 2025)

Predict Patient Self-reported Race from Skin Histological Images. - Shengjia Chen; Ruchika Verma; Kevin Clare; Jannes Jegminat; Eugenia Alleva; Kuan-Lin Huang; Brandon Veremis; Thomas J. Fuchs; Gabriele Campanella (CoRR, 2025)

Keyword-optimized template insertion for clinical note classification via prompt-based learning. - Eugenia Alleva; Isotta Landi; Leslee J. Shaw; Erwin P. Bottinger; Ipek Ensari; Thomas J. Fuchs (BMC Medical Informatics Decis. Mak., 2025)