COMPAYL 2024
PROGRAM
The workshop was a half-day satellite event at MICCAI 2024 on the 6th of October 2024.
All accepted papers were presented in poster form, and a selected few were invited for an oral presentation. We also had two talks by invited keynote speakers and a session presenting the results of the DALPHIN chatbot arena.
All papers have been published under Proceeding of Machine Learning Research and on OpenReview.
WSI-SAM: Multi-resolution Segment Anything Model (SAM) for histopathology whole-slide images
Hong Liu, Haosen Yang, Paul J. van Diest, Josien P.W. Pluim, Mitko Veta
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
Preprocessing Pathology Reports for Vision-Language Model Development
Ruben T. Lucassen, Tijn van de Luijtgaarden, Sander P. J. Moonemans, Willeke A. M. Blokx, Mitko Veta
PathAlign: A vision-language model for whole slide images in histopathology
Faruk Ahmed, Andrew Sellergen, Lin Yang, Shawn Xu, Boris Babenko, Abbi Ward, Niels Olson, Arash Mohtashamian, Yossi Matias, Greg S. Corrado, Quang Duong, Dale R. Webster, Shravya Shetty, Daniel Golden, Yun Liu, David F. Steiner, Ellery Wulczyn
ContriMix: Scalable stain color augmentation for domain generalization without domain labels in digital pathology
Tan H. Nguyen, Dinkar Juyal, Jin Li, Aaditya Prakash, Shima Nofallah, Chintan Shah, Sai Chowdary Gullapally, Limin Yu, Michael Griffin, Anand Sampat, John Abel, Justin Lee, Amaro Taylor-Weiner
Histopathobiome – integrating histopathology and microbiome data via multimodal deep learning
Agata Polejowska, Annemarie Boleij, Francesco Ciompi
Stromal Tissue Segmentation in Multi-Stained Serial Histopathological Sections of Pancreatic Tumors
David Montalvo-García, Juan E. Ortuño, Ana D. Ramos-Guerra, Sofía Granados-Aparici, Subhra S. Goswami, Pablo Santiago Diaz, Maria Evangelina Patriarca-Amiano, Joan Lop Gros, Lidia Estudillo, Mar Iglesias Coma, Rosa Noguera, Nuria Malats, María J. Ledesma-Carbayo
Upscaling Prostate Cancer MRI Images to Cell-level Resolution Using Self-supervised Learning
Yaying Shi, Srijan Das, Yonghong Yan
Scoring Tumor-Infiltrating Lymphocytes in breast DCIS: A guideline-driven artificial intelligence approach
Matteo Pozzi, Natalie Klubickova, Michela Campora, Frederique Meeuwsen, Joey Spronck, Carlijn Lems, Michelle Stegeman, Leslie Tessier, Mattia Barbareschi, Jeroen van der Laak, Giuseppe Jurman, Francesco Ciompi
Early Fusion of H&E and IHC Histology Images for Pediatric Brain Tumor Classification
Christoforos Spyretos, Iulian Emil Tampu, Nadieh Khalili, Juan Manuel Pardo Ladino, Per Nyman, Ida Blystad, Anders Eklund, Neda Haj-Hosseini
StairwayToStain: A Gradual Stain Translation Approach for Glomeruli Segmentation
Ali Alhaj Abdo, Islem Mhiri, Zeeshan Nisar, Barbara Seeliger, Thomas Lampert
Prediction of KRAS mutation status from H&E foundation model embeddings in non-small cell lung cancer
Marc Robbins, Jessica Loo, Saurabh Vyawahare, Yang Von Wang, Carson Mcneil, Dave Steiner, Sudha Rao, Pok Fai Wong, Ehud Rivlin, Shamira Weaver, Roman Goldenberg
Multi-scale Whole Slide Image Assessment Improves Deep Learning based WHO 2021 Glioma Classification
Shubham Innani, MacLean P. Nasrallah, W. Robert Bell, Bhakti Baheti, Spyridon Bakas
SurvivMIL: A Multimodal, Multiple Instance Learning Pipeline for Survival Outcome of Neuroblastoma Patients
Reed Naidoo, Olga Fourkioti, Matt De Vries, Chris Bakal
Deep-Learning Based Virtual Stain Multiplexing Immunohistochemistry Slides – a Pilot Study
Oded Ben-David, Elad Arbel, Daniela Rabkin, Itay Remer, Amir Ben-Dor, Sarit Aviel-Ronen, Frederik Aidt, Tine Hagedorn-Olsen, Lars Jacobsen, Kristopher Kersch, Anya Tsalenko
CDNet: Causal Inference inspired Diversified Aggregation Convolution for Pathology Image Segmentation
Dawei Fan, Yifan Gao, Jiaming Yu, Changcai Yang, Riqing Chen, Lifang Wei
Lymphocytes subtyping on H&E slides with automatic labelling through same-tissue stained ImmunoFluorescence images
Etienne Pochet, Luis Cano Ayestas, Alhassan Casse, Qi Tang, Roger Trullo
[OpenReview] [PDF on PMLR]
Multi-head Attention-based Deep Multiple Instance Learning
Hassan Keshvarikhojasteh, Josien P. W. Pluim, Mitko Veta
[OpenReview] [PDF on PMLR]
The poster size is A0, portrait mode (33.1 x 46.8 in). Possible templates for talks (pptx) and posters (PDF) are available here.