Explainable Medical Image Analysis

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Overview

This field studies how AI systems analyze medical images and how clinicians can inspect the evidence behind predictions, segmentations, and reports. Approaches include post-hoc saliency and perturbation methods, prototypes and concept bottlenecks, interpretable radiomic features, counterfactuals, and vision-language systems that link findings to clinical concepts or anatomical regions. Methods are tested across tasks such as chest X-ray diagnosis, retinal grading, tumor segmentation, and whole-slide pathology, with growing attention to external-site generalization and clinician assessment. A central challenge is that attractive explanations may not faithfully reflect what drives a model, while explanation stability, clinical usefulness, and predictive performance can vary across architectures, methods, and datasets.

Latest papers

CardsList

256 papers23 papers in the last four weeks, up 10% on the four weeks before. 0.1% of all new papers.

  1. Prototype Instance-semantic Disentanglement with Low-rank Regularized Subspace Clustering for WSIs Explainable Recognition

    Feb 16, 2026Chentao Li, Pan HuangWhole-Slide Image AnalysisHistopathology Image Classification

  2. retinalysis-vascx: An explainable software toolbox for the extraction of retinal vascular biomarkers

    Feb 9, 2026Jose D. Vargas Quiros, Michael J. Beyeler, Sofia Ortin Vela +5Medical Image AnalysisFundus Imaging

    Department of Ophthalmology, Erasmus University Medical Center, Rotterdam, the Netherlands · Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands · 5Dept. of Computational Biology, University of Lausanne, Lausanne, Switzerland +4

  3. MedAD-R1: Consistency-Reinforced Policy Optimization for Interpretable Medical Anomaly Detection

    Feb 1, 2026Haitao Zhang, Yingying Wang, Jiaxiang Wang +5HealthcareGroup Relative Policy Optimization

    School of Informatics, Xiamen University · Institute of Artificial Intelligence, Xiamen University · Zhejiang Expressway Co., Ltd. +3

  4. A Tool Bottleneck Framework for Clinically-Informed and Interpretable Medical Image Understanding

    Dec 24, 2025Christina Liu, Alan Q. Wang, Joy Hsu +2Tool Use in VLMsMedical Image Classification

    California Institute of Technology, Pasadena, CA 91125 · Stanford University, Stanford, CA 94305

  5. BrainRotViT: Transformer-ResNet Hybrid for Explainable Modeling of Brain Aging from 3D sMRI

    Nov 19, 2025Wasif Jalal, Md Nafiu Rahman, Atif Hasan Rahman +1Brain Age PredictionBrain MRI

    Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology

  6. Towards Cellular-Scale Interpretability in Pathology Foundation Models for Biomarker Assessment

    Nov 7, 2025Jingsong Liu, Han Li, Zhengyang Xu +19Computational PathologyHealthcare

    Institute of Pathology, Technical University of Munich, Munich, Germany · Munich Center for Machine Learning (MCML), Munich, Germany · Munich Data Science Institute (MDSI), Munich, Germany +6

  7. CXRAgent: Director-Orchestrated Multi-Stage Reasoning for Chest X-Ray Interpretation

    Oct 24, 2025Jinhui Lou, Yan Yang, Zhou Yu +4Chest X-Ray ClassificationLLM Agent Orchestration

    School of Computer Science, Hangzhou Dianzi University, Hangzhou, 310018, China · Department of Automation, Tsinghua University, Beijing 100084, China · Department of Colorectal Medical Oncology, Zhejiang Cancer Hospital, Hangzhou, 310022, China +2

  8. BiomedXPro: Prompt Optimization for Explainable Diagnosis with Biomedical Vision Language Models

    Oct 17, 2025Kaushitha Silva, Mansitha Eashwara, Sanduni Ubayasiri +2Medical VLMsExplainable Medical Image Analysis

    University of Peradeniya Peradeniya, Sri Lanka · RMIT University Melbourne, Australia

  9. Multimodal Feature Prototype Learning for Interpretable and Discriminative Cancer Survival Prediction

    Oct 7, 2025Shuo Jiang, Zhuwen Chen, Liaoman Xu +6Computational PathologyCancer Survival Prediction

    Hangzhou Dianzi University, Hangzhou 310018, China · School of Information and Communication Technology, Griffith University, QLD 4215, Australia · Shenzhen Research Institute of Big Data, Shenzhen 518172, China +3

  10. Latent Space Analysis for Interpretable Uncertainty in Melanoma Classification

    Jun 23, 2025Ciro Listone, Aniello MuranoVariational AutoencodersSkin Lesion Classification

    University of Naples Federico II, Naples, Italy.

  11. WoundAmbit: Bridging State-of-the-Art Semantic Segmentation and Real-World Wound Care

    Apr 8, 2025Vanessa Borst, Timo Dittus, Tassilo Dege +2Medical Image AnalysisMedical Image Segmentation

    Julius-Maximilians-University Würzburg, 97070 Würzburg, Germany · University Hospital Würzburg, 97070 Würzburg, Germany

  12. Explainability in mulimodal deep transformation models for stroke outcome prediction

    Apr 7, 2025Lisa Herzog, Jonas Brändli, Maurice Schneeberger +7Clinical Outcome PredictionExplainable Medical Image Analysis

    University Hospital Zurich, Department of Neurology, Frauenklinikstrasse 26, 8091 Zurich, Switzerland · Zurich University of Applied Sciences, Institute of Data Analysis and Process Design (IDP), Technikumstrasse 9, 8401 Winterthur, Switzerland · University of Zurich, Epidemiology, Biostatistics and Prevention Institute (EBPI), Hirschengraben 84, 8001 Zurich, Switzerland +1

  13. Interpretable Retinal Disease Prediction Using Biology-Informed Heterogeneous Graph Representations

    Feb 23, 2025Laurin Lux, Alexander H. Berger, Maria Romeo Tricas +8Medical ImagingDiabetic Retinopathy Grading

    Munich Center for Machine Learning (MCML), Munich, Germany · School of Medicine and Health, TUM University Hospital, Munich, Germany · School of Computation, Information and Technology, TUM, Munich, Germany

  14. Hierarchical Vision Transformer with Prototypes for Interpretable Medical Image Classification

    Feb 13, 2025Luisa Gallée, Meinrad Beer, Michael GötzMedical Image ClassificationExplainable Medical Image Analysis

    Experimental Radiology, Ulm University Medical Center, Germany · XAIRAD - Cooperation for Artificial Intelligence in Experimental Radiology, Germany · Department of Diagnostic and Interventional Radiology, Ulm University Medical Center, Germany +2

  15. Data Alchemy: Mitigating Cross-Site Model Variability Through Test Time Data Calibration

    Jul 18, 2024Abhijeet Parida, Antonia Alomar, Zhifan Jiang +7Image EnhancementTest-Time Adaptation

    Children’s National Hospital, Washington, DC, USA · Universitat Pompeu Fabra, Barcelona, Spain · Universidad Polit´ecnica de Madrid, Madrid, Spain +2

  16. Explainable Convolutional Neural Networks for Retinal Fundus Classification and Cutting-Edge Segmentation Models for Retinal Blood Vessels from Fundus Images

    May 12, 2024Fatema Tuj Johora Faria, Mukaffi Bin Moin, Pronay Debnath +2Explainable Medical Image AnalysisRetinal Vessel Segmentation

    aDepartment of Computer Science and Engineering, Ahsanullah University of Science and Technology, Dhaka, Bangladesh