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ORCIDCOMPAY@MICCAI 2021: Virtual Event / Strasbourg, France
- Manfredo Atzori, Nikolay Burlutskiy, Francesco Ciompi, Zhang Li, Fayyaz A. Minhas, Henning Müller, Tingying Peng, Nasir M. Rajpoot, Ben Torben-Nielsen, Jeroen van der Laak, Mitko Veta, Yinyin Yuan, Inti Zlobec:
MICCAI Workshop on Computational Pathology, COMPAY@MICCAI 2021, 27 September 2021, Virtual Event. Proceedings of Machine Learning Research 156, PMLR 2021 - Samaneh Abbasi-Sureshjani, Anil Yüce, Simon Schönenberger, Maris Skujevskis, Uwe Schalles, Fabien Gaire, Konstanty Korski:
Molecular Subtype Prediction for Breast Cancer Using H&E Specialized Backbone. 1-9 - Hammam M. AlGhamdia, Navid Alemi Koohbanani, Nasir M. Rajpoot, Shan E Ahmed Raza:
A Novel Cell Map Representation for Weakly Supervised Prediction of ER & PR Status from H&E WSIs. 10-19 - Benjamin Bancher, Amirreza Mahbod, Isabella Ellinger
, Rupert Ecker, Georg Dorffner:
Improving Mask R-CNN for Nuclei Instance Segmentation in Hematoxylin & Eosin-Stained Histological Images. 20-35 - 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:
Random Multi-Channel Image Synthesis for Multiplexed Immunofluorescence Imaging. 36-46 - Afshin Bozorgpour, Reza Azad, Eman Showkatian, Alaa Sulaiman:
Multi-scale Regional Attention Deeplab3+: Multiple Myeloma Plasma Cells Segmentation in Microscopic Images. 47-56 - Joshua Butke, Tatjana Frick, Florian Roghmann, Samir F. El-Mashtoly, Klaus Gerwert, Axel Mosig:
End-to-end Multiple Instance Learning for Whole-Slide Cytopathology of Urothelial Carcinoma. 57-68 - Jonathan Ganz, Tobias Kirsch, Lucas Hoffmann, Christof A. Bertram, Christoph Hoffmann, Andreas K. Maier, Katharina Breininger, Ingmar Blümcke, Samir Jabari, Marc Aubreville:
Automatic and explainable grading of meningiomas from histopathology images. 69-80 - Narmin Ghaffari Laleh, Amelie Echle, Hannah Sophie Muti, Katherine Jane Hewitt, Volkmar Schulz, Jakob Nikolas Kather:
Deep Learning for interpretable end-to-end survival (E-ESurv) prediction in gastrointestinal cancer histopathology. 81-93 - Azam Hamidinekoo, Anna Kelsey, Nicholas Trahearn, Joanna Selfe, Janet Shipley, Yinyin Yuan:
Automated Quantification Of Blood Microvessels In Hematoxylin And Eosin Whole Slide Images. 94-104 - Johannes Höhne, Jacob de Zoete, Arndt A. Schmitz, Tricia Bal, Emmanuelle di Tomaso, Matthias Lenga:
Detecting genetic alterations in BRAF and NTRK as oncogenic drivers in digital pathology images: towards model generalization within and across multiple thyroid cohorts. 105-116 - Guillaume Jaume, Pushpak Pati, Valentin Anklin, Antonio Foncubierta, Maria Gabrani:
HistoCartography: A Toolkit for Graph Analytics in Digital Pathology. 117-128 - Marvin Lerousseau, Maria Vakalopoulou, Eric Deutsch, Nikos Paragios:
SparseConvMIL: Sparse Convolutional Context-Aware Multiple Instance Learning for Whole Slide Image Classification. 129-139 - Amaury Leroy, Kumar Shreshtha, Marvin Lerousseau, Théophraste Henry, Théo Estienne, Marion Classe, Nikos Paragios, Vincent Grégoire, Eric Deutsch:
Magnetic Resonance Imaging Virtual Histopathology from Weakly Paired Data. 140-150 - Chaoqun Li, Yitian Zhou, Tangqi Shi, Yenan Wu, Meng Yang, Zhongyu Li:
Unsupervised Domain Adaptation for the Histopathological Cell Segmentation through Self-Ensembling. 151-158 - Mengkang Lu, Yongsheng Pan, Dong Nie, Feihong Liu, Feng Shi, Yong Xia, Dinggang Shen:
SMILE: Sparse-Attention based Multiple Instance Contrastive Learning for Glioma Sub-Type Classification Using Pathological Images. 159-169 - Niccolò Marini, Sebastian Otálora, Francesco Ciompi, Gianmaria Silvello, Stefano Marchesin, Simona Vatrano, Genziana Buttafuoco, Manfredo Atzori, Henning Müller:
Multi-Scale Task Multiple Instance Learning for the Classification of Digital Pathology Images with Global Annotations. 170-181 - Christian Marzahl, Frauke Wilm, Franz F. Dressler, Lars Tharun, Sven Perner, Christof A. Bertram, Christine Kröger, Jörn Voigt, Robert Klopfleisch, Andreas K. Maier, Marc Aubreville, Katharina Breininger:
Robust Quad-Tree based Registration on Whole Slide Images. 181-190 - Charlie Saillard, Olivier Dehaene, Tanguy Marchand, Olivier Moindrot, Aurélie Kamoun, Benoit Schmauch, Simon Jégou:
Self-supervised learning improves dMMR/MSI detection from histology slides across multiple cancers. 191-205 - Corentin Gueréndel, Phil Arnold, Ben Torben-Nielsen:
Creating small but meaningful representations of digital pathology images. 206-215 - Paul Tourniaire, Marius Ilie, Paul Hofman, Nicholas Ayache, Herve Delingette:
Attention-based Multiple Instance Learning with Mixed Supervision on the Camelyon16 Dataset. 216-226 - Xiaodan Xing, Yixin Ma, Lei Jin, Tianyang Sun, Zhong Xue, Feng Shi, Jinsong Wu, Dinggang Shen:
A Multi-scale Graph Network with Multi-head Attention for Histopathology Image Diagnosisn. 227-235 - Qing Xu, Wenting Duan:
An Automatic Nuclei Image Segmentation Based on Multi-Scale Split-Attention U-Net. 236-245 - Hanyun Zhang, Tami Grunewald, Ayse U. Akarca, Jonathan A. Ledermann, Teresa Marafioti, Yinyin Yuan:
Symmetric Dense Inception Network for Simultaneous Cell Detection and Classification in Multiplex Immunohistochemistry Images. 246-257
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