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Proceedings of Machine Learning Research

Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research
Proceedings of Machine Learning Research
PMLR · 2026-05-29 · via Proceedings of Machine Learning Research

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Volume 316: Proceedings of the MICCAI Workshop on Computational Pathology, 27 September 2025, Marrakesh, Morocco

[edit]

Editors: Linda Studer, Francesco Ciompi, Nadieh Khalili, Khrystyna Faryna, Khrystyna Faryna, Joe Yeong, Mai Chan Lau, Hao Chen, Ziyi Liu, Biagio Brattoli

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On the Importance of Text Preprocessing for Multimodal Representation Learning and Pathology Report Generation

Ruben T. Lucassen, Tijn van de Luijtgaarden, Sander P. J. Moonemans, Gerben E. Breimer, Willeke A. M. Blokx, Mitko Veta; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:1-11

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Attention-based Generative Latent Replay: A Continual Learning Approach for WSI Analysis

Pratibha Kumari, Daniel Reisenbüchler, Afshin Bozorgpour, Nadine S. Schaadt, Friedrich Feuerhake, Dorit Merhof; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:12-23

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Scalable and Loosely-Coupled Multimodal Deep Learning for Breast Cancer Subtyping

; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:24-38

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Uncertainty-Aware Ensemble Segmentation of Breast Cancer Tissue Microarrays

Lucia Schmidt-Santiago, Roman Kinakh, Sergio Carreras-Salinas, Sara Guerrero-Aspizcua, Gonzalo R. Ríos-Muñoz, Arrate Muñoz-Barrutia; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:39-51

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GenST: A Generative Cross-Modal Model for Predicting Spatial Transcriptomics from Histology Images

Ruby Wood, Yang Hu, Jens Rittscher, Bin Li; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:52-65

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A Spatially-Aware Multiple Instance Learning Framework for Digital Pathology

Hassan Keshvarikhojasteh, Mihail Tifrea, Sibylle Hess, Josien P.W. Pluim, Mitko Veta; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:66-74

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Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder

Biagio Brattoli, Jack Shi, Jongchan Park, Taebum Lee, Donggeun Yoo, Sergio Pereira; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:75-85

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Linear Attention-based Multiple Instance Learning for Computational Pathology

Charlotte Richter, Daniel Reisenbüchler, Nadine S. Schaadt, Friedrich Feuerhake, Dorit Merhof; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:86-96

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ContriMix: Scalable stain color augmentation for domain generalization without domain labels in digital pathology

Lisa Hensens, Sergio Sabroso-Lasa, Caroline Verbeke, Nuria Malats, ThePanGenEU consortium, Geert Litjens, Pierpaolo Vendittelli; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:97-105

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KidneyGrader: Fine-Grained Tubulitis Scoring Using Weakly Supervised Transformers

Abrar Rashid, Vishal Jain, Sarah Cechnicka, Aamir Chaudry, Candice Roufosse, Bernhard Kainz; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:106-115

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MVHybrid: Improving Spatial Transcriptomics Prediction with Hybrid State Space-Vision Transformer Backbone in Pathology Vision Foundation Models

Won June Cho, Hongjun Yoon, Daeky Jeong, Hyeongyeol Lim, Yosep Chong; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:116-138

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Enhancing Interpretation of Histopathology Whole Slide Image Analysis via Regional Causal Dependency Discovery

Zixian Li, Jun Shi, Zhiguo Jiang, Fengying Xie, Yushan Zheng; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:139-149

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Centroid-Aware Gaussian Prompt Learning with Erosion-Guided Accumulator for Robust Semantic Cell Segmentation

Nur Suriza Syazwany, Su Jung Kim, Ju-Hyeon Nam, Sang-Chul Lee; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:160-170

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fmMAP: A Framework Reducing Site-Bias Batch Effect from Foundation Models in Pathology

Hai Cao Truong Nguyen, David Joon Ho; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:171-186

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Context-guided Prompt Learning for Continual WSI Classification

Giulia Corso, Francesca Miccolis, Angelo Porrello, Federico Bolelli, Simone Calderara, Elisa Ficarra; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:187-198

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A Benchmark of Foundation Model Encoders for Histopathological Image Segmentation

Itsaso Vitoria, Cristina L. Saratxaga, Cristina Penas Lago, Rosa Izu, Ana Sanchez-Diez, Goikoana Cancho-Galan, Maria Dolores Boyano, Ignacio Arganda-Carreras, Adrian Galdran; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:199-212

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Semantic Mosaicing of Histo-Pathology Image Fragments using Visual Foundation Models

Stefan Brandstätter, Maximilan Köller, Philipp Seeböck, Alissa Blessing, Felicitas Oberndorfer, Svitlana Pochepnia, Helmut Prosch, Georg Langs; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:213-222

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Reliable and Efficient Tissue Segmentation in Whole-Slide Images

Sander Elias Magnussen Helgesen, Anthony Manet, Karolina Cyll, Kari Anne Risan Tobin, Marna Lill Kjæreng, Ilyá Kostolomov, Audun Ljone Henriksen, Sepp de Raedt, Hanne Arenberg Askautrud, Miangela Lacle, Robert Jones, Cornelis Verhoef, Tarjei Sveinsgjerd Hveem, Ole-Johan Skrede, Andreas Kleppe; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:223-233

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Low-Rank Adaptations for increased Generalization in Foundation Model features

Vilde Schulerud Bøe, Andreas Kleppe, Sebastian Foersch, Daniel-Christoph Wagner, Lill-Tove Rasmussen Busund, Adín Ramírez Rivera; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:234-247

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Towards Automated Banff Lesion Scoring: Tissue Segmentation in Kidney Transplant Biopsies using Deep Learning

Sebastiaan Ram, Dominique van Midden, Jeroen van der Laak, Linda Studer; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:248-265

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Chromosome Mask-Conditioned Generative Inpainting for Atypical Mitosis Classification

Sweta Banerjee, Viktoria Weiss, Thomas Conrad, Taryn A. Donovan, Jonas Ammeling, Rutger H.J. Fick, Jonas Utz, Robert Klopfleisch, Christopher Kaltenecker, Christof A. Bertram, Katharina Breininger, Marc Aubreville; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:266-277

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Learning Disentangled Stain and Structural Representations for Semi-Supervised Histopathology Segmentation

Ha-Hieu Pham, Nguyen Lan Vi Vu, Thanh-Huy Nguyen, Ulas Bagci, Min Xu, Trung-Nghia Le, Huy-Hieu Pham; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:278-287

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Effortless Vision-Language Model Specialization in Histopathology without Annotation

Jingna Qiu, Nishanth Jain, Jonas Ammeling, Marc Aubreville, Katharina Breininger; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:288-300

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From Gene Expression to Tissue Morphology: Can Generative Models Uncover the Link?

Frederieke Lohmann, Alberto Valdeolivas, Jelica Vasiljevic; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:301-317

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OXA-MISS: A Robust Multimodal Architecture for Chemotherapy Response Prediction under Data Scarcity

Francesca Miccolis, Fabio Marinelli, Vittorio Pipoli, Daria Afenteva, Anni Virtanen, Marta Lovino, Elisa Ficarra; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:318-327

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NeXtMarker: Contrastive Learning for Marker-Level Interpretability in Single-Cell Multiplex Imaging

Simon Gutwein, Daria Lazic, Thomas Walter, Sabine Taschner-Mandl, Roxane Licandro; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:328-337

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WSI-BayesUNet: Uncertainty-Aware Deep Learning for Histopathological Image Segmentation with Active Learning

Yijun Cui, Geert Litjens, Khalili Nadieh; Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 316:338-346

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