Feel free to send questions to the speakers via the following links: oral session questions, panel discussion questions
The full proceedings of COMPAY 2021 are available as Proceedings of Machine Learning Research
Time zone: UCT
| 9:00 | Opening | |
| SESSION 1 – Chair: Henning Müller | ||
| 9:10 | Keynote presentation | |
| AI in pathology: promise and potential Monika Lamba Saini (CellCarta, Belgium) | ||
| 9:40 | Oral presentations | |
| Automated Quantification Of Blood Microvessels In Hematoxylin And Eosin Whole Slide Images Azam Hamidinekoo, Anna Kelsey, Nicholas Trahearn, Joanna Selfe, Janet Shipley, Yinyin Yuan HistoCartography: A Toolkit for Graph Analytics in Digital Pathology Guillaume Jaume, Pushpak Pati, Valentin Anklin, Antonio Foncubierta, Maria Gabrani Detecting genetic alterations in BRAF and NTRK as oncogenic drivers in digital pathology images: towards model generalization within and across multiple thyroid cohorts Johannes Höhne, Jacob de Zoete, Arndt A Schmitz, Tricia Bal, Emmanuelle di Tomaso, Matthias Lenga | ||
| 10:10 | Q/A session oral presentations | |
| 10:25 | Software demo pitches | |
| A practical guide to using HookNet Mart van Rijthoven Stainlib: a python library for augmentation and normalization of histopathology H&E images Niccolò Marini Multi_Scale_Tools: a python library to exploit multi-scale whole slide images Niccolò Marini QuickAnnotator Andrew Janowczyk | ||
| 10:35 | Poster & software demo session #1 | |
| Posters Automated Quantification Of Blood Microvessels In Hematoxylin And Eosin Whole Slide Images Azam Hamidinekoo, Anna Kelsey, Nicholas Trahearn, Joanna Selfe, Janet Shipley, Yinyin Yuan HistoCartography: A Toolkit for Graph Analytics in Digital Pathology Guillaume Jaume, Pushpak Pati, Valentin Anklin, Antonio Foncubierta, Maria Gabrani Detecting genetic alterations in BRAF and NTRK as oncogenic drivers in digital pathology images: towards model generalization within and across multiple thyroid cohorts Johannes Höhne, Jacob de Zoete, Arndt A Schmitz, Tricia Bal, Emmanuelle di Tomaso, Matthias Lenga End-to-end Multiple Instance Learning for Whole-Slide Cytopathology of Urothelial Carcinoma Joshua Butke, Tatjana Frick, Florian Roghmann, Samir El-Mashtoly, Klaus Gerwert, Axel Mosig Attention-based Multiple Instance Learning with Mixed Supervision on the Camelyon16 Dataset Paul Tourniaire, Nicholas Ayache, Hervé Delingette A Multi-scale Graph Network with Multi-head Attention for Histopathology Image Diagnosis Xiaodan Xing, Yixin Ma, Lei Jin, Tianyang Sun, Zhong Xue, Feng Shi, Jinsong Wu, Dinggang Shen Unsupervised Domain Adaptation for the Histopathological Cell Segmentation through Self-Ensembling Chaoqun Li, Yitian Zhou, Tangqi Shi, Yenan Wu, Meng Yang, Zhongyu Li Creating small but meaningful representations of digital pathology images Corentin Guerendel, Phil Arnold, Benjamin Torben-Nielsen Molecular Subtype Prediction for Breast Cancer Using H&E Specialized Backbone Samaneh Abbasi Sureshjani, Anil Yuce, Simon Till Schönenberger, Maris Skujevskis, Uwe Schalles, Fabien Gaire, Konstanty Korski SMILE: Sparse-Attention based Multiple Instance Contrastive Learning for Glioma Sub-type Classification Using Pathological Image Mengkang Lu, Yongsheng Pan, Dong Nie, Feng Shi, Feihong Liu, Yong Xia, Dinggang Shen Software demos A practical guide to using HookNet Mart van Rijthoven Stainlib: a python library for augmentation and normalization of histopathology H&E images Multi_Scale_Tools: a python library to exploit multi-scale whole slide images Niccolò Marini | ||
| SESSION 2 – Chair: Jeroen van der Laak | ||
| 11:45 | Keynote presentation | |
| Taking AI to the next level with Data Centric approach in Computational Pathology Chen Sagiv (DeePathology.ai, Israel) | ||
| 12:15 | Oral presentations | |
| SparseConvMIL: Sparse Convolutional Context-Aware Multiple Instance Learning for Whole Slide Image Classification Marvin Lerousseau, Maria Vakalopoulou, Eric Deutsch, Nikos Paragios Multi-scale Regional Attention Deeplab3+: Multiple Myeloma Plasma Cells Segmentation in Microscopic Images Afshin Bozorgpour, Reza Azad, Eman Showkatian, Alaa Sulaiman Symmetric Dense Inception Network for Simultaneous Cell Detection and Classification in Multiplex Immunohistochemistry Images Hanyun Zhang, Tami Grunewald, Ayse U. Akarca, Teresa Marafioti, Jonathan A. Ledermann, Yinyin Yuan | ||
| 12:45 | Q/A session oral presentations | |
| 13:00 | Lunch break | |
| SESSION 3 – Chair: Mitko Veta | ||
| 14:00 | Keynote presentation | |
| Data-efficient and multimodal computational pathology Faisal Mahmood (Harvard Medical School) | ||
| 14:30 | Oral presentations | |
| Self supervised learning improves dMMR/MSI detection from histology slides across multiple cancers Charlie Saillard, Olivier Dehaene, Tanguy Marchand, Olivier Moindrot, Aurélie Kamoun, Benoit Schmauch, Simon Jegou Automatic and explainable grading of meningiomas from histopathology images Jonathan Ganz, Tobias Kirsch, Christof Albert Bertram, Christoph Hoffmann, Andreas Maier, Katharina Breininger, Ingmar Blümcke, Samir Jabari, Marc Aubreville Robust quad-tree based registration of whole slide images Christian Marzahl, Frauke Wilm, Christine Kröger, Franz F Dressler, Lars Tharun, Sven Perner, Christof Bertram, Jörn Voigt, Robert Klopfleisch, Andreas Maier, Marc Aubreville, Katharina Breininger | ||
| 15:15 | Poster and software demo session #2 | |
| Posters SparseConvMIL: Sparse Convolutional Context-Aware Multiple Instance Learning for Whole Slide Image Classification Marvin Lerousseau, Maria Vakalopoulou, Eric Deutsch, Nikos Paragios Multi-scale Regional Attention Deeplab3+: Multiple Myeloma Plasma Cells Segmentation in Microscopic Images Afshin Bozorgpour, Reza Azad, Eman Showkatian, Alaa Sulaiman Symmetric Dense Inception Network for Simultaneous Cell Detection and Classification in Multiplex Immunohistochemistry Images Hanyun Zhang, Tami Grunewald, Ayse U. Akarca, Teresa Marafioti, Jonathan A. Ledermann, Yinyin Yuan Self supervised learning improves dMMR/MSI detection from histology slides across multiple cancers Charlie Saillard, Olivier Dehaene, Tanguy Marchand, Olivier Moindrot, Aurélie Kamoun, Benoit Schmauch, Simon Jegou Automatic and explainable grading of meningiomas from histopathology images Jonathan Ganz, Tobias Kirsch, Christof Albert Bertram, Christoph Hoffmann, Andreas Maier, Katharina Breininger, Ingmar Blümcke, Samir Jabari, Marc Aubreville Robust quad-tree based registration of whole slide images Christian Marzahl, Frauke Wilm, Christine Kröger, Franz F Dressler, Lars Tharun, Sven Perner, Christof Bertram, Jörn Voigt, Robert Klopfleisch, Andreas Maier, Marc Aubreville, Katharina Breininger Multi-Scale Task Multiple Instance Learning for the Classification of Digital Pathology Images with Global Annotations Niccolò Marini, Sebastian Otálora, Francesco Ciompi, Gianmaria Silvello, Stefano Marchesin, Simona Vatrano, Gianziana Buttafuoco, Manfredo Atzori, Henning Müller Improving Mask R-CNN for Nuclei Instance Segmentation in Hematoxylin & Eosin-Stained Histological Images Benjamin Bancher, Amirreza Mahbod, Isabella Ellinger, Rupert Ecker, Georg Dorffner Random Multi-Channel Image Synthesis for Multiplexed Immunofluorescence Imaging Shunxing Bao, Yucheng Tang, Ho Hin Lee, Riqiang Gao, Sophie Chiron, Ilwoo Lyu, Lori A. Coburn, Keith T. Wilson, Joseph T. Roland, Bennett A. Landman, Yuankai Huo An Automatic Nuclei Image Segmentation Based on Multi-Scale Split-Attention U-Net Qing Xu, Wenting Duan Magnetic Resonance Imaging Virtual Histopathology from Weakly Paired Data Amaury Leroy, Kumar Shreshtha, Marvin Lerousseau, Théophraste Henry, Théo ESTIENNE, Marion Classe, Nikos Paragios, Vincent Grégoire, Eric Deutsch Deep Learning for interpretable end-to-end survival prediction in gastrointestinal cancer histopathology Narmin Ghaffari Laleh, Amelie Echle, Hannah Sophie Muti, Katherine Jane Hewitt, Volkmar Schulz, Jakob Nikolas Kather A Novel Cell Map Representation for Weakly Supervised Prediction of ER and PR Status from H&E WSIs Hammam Alghamdi, Navid Alemi Koohbanani, Nasir Rajpoot, SHAN E AHMED RAZA Software demos HistoQC QuickAnnotator PatchSorter Andrew Janowczyk | ||
| 16:45 | PANEL DISCUSSION – Chairs: Nasir Rajpoot, Francesco Ciompi | |
| Invited panelists: – Katherine Elfer (FDA) – Chen Sagiv (DeePathology.ai) – Roberto Salgado (TIL Working Group) – Inti Zlobec (University of Bern) – Faisal Mahmood (Harvard Medical School) – Monika Lamba Saini (CellCarta) | ||
| 17:45 17:55 | Organizing team short presentations Awards & closing |
