Histopathology Image Classification

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9 papers in the last four weeks, up 29% on the four weeks before. 0.1% of all new papers.

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Hierarchical Prototype-based Domain Priors for Multiple Instance Learning in Multimodal Histopathology Analysis
Apr 27, 2026Xuemei Qiu, Dawei Fan, Yebin Huang +2Cross-Modal Alignment Prototype Learning
College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China · Fujian Agriculture and Forestry University, Fuzhou, 350002, China · Department of Pathology, Clinical Oncology School of Fujian Medical University, and Fujian Cancer Hospital, Fuzhou, 350014, China +2
Weakly Supervised Multicenter Nancy Index Scoring in Ulcerative Colitis Using Foundation Models
Apr 26, 2026Adam Kukučka, Ondřej Fabián, Vít Musil +1Computational Pathology Pathology Foundation Models
Masaryk University, Faculty of Informatics, Brno, Czech Republic · Institute of Clinical and Experimental Medicine, Prague, Czech Republic
Leveraging Spatial Transcriptomics as Alternative to Manual Annotations for Deep Learning-Based Nuclei Analysis
Apr 26, 2026Kazuya Nishimura, Ryoma Bise, Haruka Hirose +1Computational Pathology Histopathology Image Segmentation
The University of Osaka, Osaka, Japan · National Cancer Center Tokyo, Japan · Kyushu University, Fukuoka, Japan
Clinically-Informed Modeling for Pediatric Brain Tumor Classification from Whole-Slide Histopathology Images
Apr 22, 2026Joakim Nguyen, Jian Yu, Jinrui Fang +7Pathology Foundation Models Medical Image Classification
Dept. of Computer Science University of Texas at Austin Austin, TX, USA · School of Information University of Texas at Austin Austin, TX, USA · Dept. of Computer Science UNC at Chapel Hill Chapel Hill, NC, USA +3
A Digital Pathology Resource for Liver Cancer Quantification with Datasets, Benchmarks, and Tools
Apr 22, 2026Ying Xiao, Shimiao Tang, Xitong Ling +11Computational Pathology Image Segmentation
Department of Pathology, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua Medicine, Tsinghua University, Beijing, China · Shenzhen International Graduate School, Tsinghua University, Shenzhen, China
Unified Multi-Foundation-Model Slide Representation for Pan-Cancer Recognition and Text-Guided Tumor Localization
Apr 21, 2026Tianyang Wang, Ziyu Su, Abdul Rehman Akbar +6Pathology Foundation Models Oncology
Department of Pathology, College of Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, USA · Department of Biomedical Engineering, The Ohio State University, Columbus, OH, USA
Region-Affinity Attention for Whole-Slide Breast Cancer Classification in Deep Ultraviolet Imaging
Apr 19, 2026Nagur Shareef Shaik, Teja Krishna Cherukuri, Dong Hye YeMedical Image Classification Histopathology Image Classification
Department of Computer Science, Georgia State University, Atlanta, GA USA
Multimodal Fusion of Histopathology Images and Electronic Health Records for Early Breast Cancer Diagnosis
Apr 18, 2026Aditya Shribhagwan Khandelwal, Mohammad Samar Ansari, Asra AslamBreast Cancer Computational Pathology
University of Sheffield, UK · University of Chester, UK
Dual-Modal Lung Cancer AI: Interpretable Radiology and Microscopy with Clinical Risk Integration
Apr 17, 2026Baramee Sukumal, Aueaphum AueawatthanaphisutMedical Image Classification Explainable Medical Image Analysis
Hatyaiwittayalai School, Hat Yai, Songkhla, Thailand, 90110 · School of Information, Computer, and Communication Technology,2026 Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani, Thailand
SSMamba: A Self-Supervised Hybrid State Space Model for Pathological Image Classification
Apr 17, 2026Enhui Chai, Sicheng Chen, Tianyi Zhang +2Self-Supervised Learning Pathology Foundation Models
School of Computer Science, Northwest University · PuzzleLogic Pte Ltd, Singapore 229594, Singapore · Department of Electrical & Computer Engineering, National University of Singapore +1
ReconMIL: Synergizing Latent Space Reconstruction with Bi-Stream Mamba for Whole Slide Image Analysis
Mar 20, 2026Lubin Gan, Jing Zhang, Heng Zhang +4Histopathology Image Classification Medical Image Localization
USTC, Anhui, China · Anhui Province Key Laboratory of Biomedical Imaging and Intelligent Processing, Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Anhui, China · SCNU, Guangdong, China +2
Context-aware Skin Cancer Epithelial Cell Classification with Scalable Graph Transformers
Feb 17, 2026Lucas Sancéré, Noémie Moreau, Katarzyna BozekComputational Pathology Oncology
Faculty of Mathematics and Natural Sciences, University of Cologne, Cologne, North Rhine-Westphalia, Germany · Institute for Biomedical Informatics, Faculty of Medicine and University Hospital Cologne, University of Cologne, North Rhine-Westphalia, Germany · Center for Molecular Medicine Cologne (CMMC), Faculty of Medicine and University Hospital Cologne, University of Cologne, North Rhine-Westphalia, Germany +1
Semi-Supervised Domain Adaptation with Latent Diffusion for Pathology Image Classification
Jan 23, 2026Tengyue Zhang, Ruiwen Ding, Luoting Zhuang +3Computational Pathology Synthetic Data Augmentation
Medical & Imaging Informatics, Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA 90024, USA · Bioengineering Department, Henry Samueli School of Engineering, UCLA, Los Angeles, CA 90024, USA · Department of Pathology & Laboratory Sciences, David Geffen School of Medicine, UCLA, Los Angeles, CA 90024, USA
CytoCLIP: Learning Cytoarchitectural Characteristics in Developing Human Brain Using Contrastive Language Image Pre-Training
Jan 18, 2026Pralaypati Ta, Sriram Venkatesaperumal, Keerthi Ram +1Medical VLMs Histopathology Image Classification
Sudha Gopalakrishnan Brain Centre, Indian Institute of Technology, Madras, Chennai, India. · Department of Electrical Engineering, Indian Institute of Technology, Madras, Chennai, India.
Towards Accurate and Lightweight Peripheral Neuroblastic Tumor Diagnosis via Contrastive Multi-scale Pathological Image Analysis
Apr 18, 2025Zhu Zhu, Shuo Jiang, Jingyuan Zheng +7Computational Pathology Oncology
Children’s Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China · Hangzhou Dianzi University, Hangzhou 310018, China · Chinese University of Hong Kong, Hong Kong SAR, China +1
Data Alchemy: Mitigating Cross-Site Model Variability Through Test Time Data Calibration
Jul 18, 2024Abhijeet Parida, Antonia Alomar, Zhifan Jiang +7Image Enhancement Test-Time Adaptation
Children’s National Hospital, Washington, DC, USA · Universitat Pompeu Fabra, Barcelona, Spain · Universidad Polit´ecnica de Madrid, Madrid, Spain +2

Apr 27, 2026, cs.CVJ/K move · Enter open · S save

Hierarchical Prototype-based Domain Priors for Multiple Instance Learning in Multimodal Histopathology Analysis

Xuemei Qiu, Dawei Fan, Yebin Huang, Yanping Chen+1

College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China · Fujian Agriculture and Forestry University, Fuzhou, 350002, China · Department of Pathology, Clinical Oncology School of Fujian Medical University, and Fujian Cancer Hospital, Fuzhou, 350014, China+2

Cross-Modal Alignment Prototype Learning Histopathology Image Classification Multimodal Fusion Multiple Instance Learning Whole-Slide Image Analysis

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Digital pathology has fundamentally altered diagnostic workflows by enabling the computational analysis of gigapixel Whole Slide Images (WSIs), yet effectively deciphering their complex tumor microenvironments remains a formidable challenge. Existing Multiple Instance Learning (MIL) frameworks typically treat Whole Slide Images as unstructured bags of patches, discarding critical morphological semantics and spatial geometry. This lack of inductive bias often leads to overfitting on background noise and fails to align visual features with high-level diagnostic knowledge. To overcome these limitations, we propose the Hierarchical Prototype-based Domain Priors (HPDP) framework, a unified multimodal approach for joint histopathology diagnosis and prognosis. HPDP mitigates the data-driven "black box" issue by introducing a Morphologically Anchored Prototype System (MAPS), which anchors learning to interpretable morphological clusters, and a Sinusoidal Positional Encoder (SPE) to explicitly model tissue architecture. Furthermore, we bridge the semantic gap via a Hierarchical Cross-Modal Alignment (HCMA) module, using Large Language Model (LLM)-generated descriptions to contextually refine visual representations. Extensive experiments across seven cancer cohorts demonstrate that HPDP consistently achieves state-of-the-art performance with superior robustness and interpretability.

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