Explainable Medical Image Analysis

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12 papers in the last four weeks, up 33% on the four weeks before. 0.1% of all new papers.

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Beyond Explanation: Debugging Medical Imaging Models via Concept Intervention
Oct 6, 2026Samrajya Thapa, Daniel J. Quest, Timothy L. Kline +3Explainable Medical Image Analysis Concept Bottleneck Models
Iowa State University, Ames IA, USA · Mayo Clinic, Rochester MN, USA
Evidence-Bound Reasoning: Neuro-Semantic Verification of Biomedical AI in Glioblastoma Radiogenomics
Oct 6, 2026Mariya Miteva, Maria Nisheva-PavlovaExplainable Medical Image Analysis Radiomics
Faculty of Mathematics and Informatics – Sofia University St. Kliment Ohridski, 5 James Bourchier Blvd., Sofia 1164, Bulgaria
MedCORE: Criteria-Grounded Clinical Reasoning for Interpretable Medical Image Diagnosis
Oct 6, 2026Asim Khan, Samee Ullah Khan, Dwarikanath MahapatraMedical Image Classification Medical VLMs
Deparment of Computer Science, Khalifa University, Abu Dhabi, UAE · Department of Aerosapce Engineering, Khalifa University, Abu Dhabi, UAE
Multi-Dataset Diagnostic Utility of Clinical Visual Concepts in AI Systems for Dermatology
Oct 6, 2026Linda Wermelinger, Simone Lionetti, Fabian Gröger +6Skin Lesion Classification Explainable Medical Image Analysis
University of Basel · Lucerne University of Applied Sciences and Arts · University Hospital of Basel
From Image Latent Space to Fuzzy Rules: Interpretable Analysis of Gastrointestinal Foundation Model
Sep 30, 2026Michael D. Vasilakakis, Dimitris K. IakovidisMedical Imaging Foundation Models Medical Image Classification
Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, Greece
CAMEO: A Class-Activation-Mapped Equitable Overlay Framework for Fair and Robust Deep Learning-based Skin Condition Diagnosis
Sep 28, 2026Youssef Attia, Debasmita MukherjeeSkin Lesion Classification Algorithmic Fairness
Department of Electrical and Computer Engineering, University of New Brunswick, Fredericton, NB, Canada
Evidence Before Accuracy: A MRI-PET Fusion Network for Alzheimer Disease Classification with Causal Regional Validation
Sep 28, 2026Saeid Firouzi Daghigh, Saeed AyatAlzheimer's Disease Classification Explainable Medical Image Analysis
Department of Computer Engineering and Information Technology, Payame Noor University, Tehran, Iran
MoSPR: Histology-to-Gene Expression Prediction with Morpho-Spatial Macrostates and Low-Rank Molecular Programs
Sep 28, 2026Dongmyung Shin, Geongyu Lee, Yesung Cho +1Computational Pathology Explainable Medical Image Analysis
OmixAI Co. Ltd. · Oncocross Co. Ltd. · Kyunghee University
Interpretable AI plus Handheld, Portable Retinal Photographs: A Low-Cost Glaucoma Screening Solution for West Africa
Sep 22, 2026Charis Y. N. Chiang, Tarela Sarimiye, Adeyinka Ashaye +4Medical Diagnosis Medical Image Segmentation
Department of Ophthalmology, Emory University, Atlanta, Georgia, United States · Department of Biomedical Engineering, National University of Singapore, Singapore · Singapore Eye Research Institute, Singapore National Eye Centre, Singapore +5
Towards Transparent Diagnostics: Investigating Architectural Trade-offs and Explainability in Malaria Detection
Sep 16, 2026Suman Kunwar, Avishek DangolEfficient Neural Network Inference Medical Diagnosis
DWaste, Baltimore, USA
Anatomical Grounding and Leakage-Aware Multimodal Contrastive Learning for Alzheimer's Disease Classification from Structural MRI
Sep 14, 2026Paul-Gabriel Nicolae, Irina Georgiana MocanuData Leakage Alzheimer's Disease Classification
Computer Science and Engineering Department, Faculty of Automatic Control and Computers, National University of Science and Technology POLITEHNICA Bucharest, Romania
MedDiME: Efficient Latent Diffusion with Adaptive Masking for Medical Counterfactual Generation
Sep 14, 2026Yan Zeng, Changlu Guo, Anders Nymark Christensen +2Counterfactual Explanations Latent Diffusion Models
Department of Applied Mathematics and Computer Science, Technical University of Denmark
A Multimodal Explainable Deep Learning Framework for Alzheimer's Disease Diagnosis using 3D Magnetic Resonance Imaging and Clinical Data
Sep 14, 2026Yusuf Brima, Marcellin Atemkeng, Lakshmana Rao Namamula +13D Medical Imaging Multimodal Classification
Computer Vision, Institute of Cognitive Science, Osnabrück University, Germany. · Department of Mathematics, Rhodes University, South Africa. · National Institute for Theoretical and Computational Sciences (NITheCS), Stellenbosch, 7600, South Africa. +2
Medical AI Encodes a "Feeling of Error": Verifying Cancer Segmentation via Internal Concepts
Sep 8, 2026Mengmeng Ma, Yunxiang Peng, Tang Li +4Medical Image Segmentation Explainable Medical Image Analysis
University of Virginia, Charlottesville, VA, USA · University of Delaware, Newark, DE, USA · Memorial Sloan Kettering Cancer Center, New York City, NY, USA
CAR-MIL: Counterfactual Attention Regularization for Multiple Instance Learning
Sep 8, 2026Imane Chraki, Pierre Marza, Stergios Christodoulidis +1Computational Pathology Weakly Supervised Learning
Université Paris-Saclay, CentraleSupélec, Gustave Roussy, INSERM, IHU PRISM, Cancer Data Science Unit, France · Université Paris-Saclay, CentraleSupélec, MICS Laboratory, France
Understanding the Impact of Model Pruning on Long-Tail Forgetting and Explanation Reliability in Medical Imaging
Sep 7, 2026Nazish Khalid, Tausifa Jan Saleem, Amal Saqib +2Model Compression Explainable Medical Image Analysis
Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO 65409 USA · Computing and Mathematical Sciences Division, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates
Beyond Blur: A Semantic Tri-view Pipeline for Teledermatology Gradability via Skin Micro-relief
Sep 2, 2026Robert EngelExplainable Medical Image Analysis Image Quality Assessment
Avalytiq San Francisco, USA
ICON Decomposition: Auditing deep neural networks for shortcuts by decomposing layer-wise representations using concepts
Aug 26, 2026Roshan Prakash Rane, Marco Simnacher, Manuel Pfeuffer +7Concept-Based Explanations Neural Network Interpretability
Hertie Institute for AI in Brain Health, University of Tübingen, Tübingen, Germany. · Department of Psychiatry and Neurosciences, Charité - Universitätsmedizin Berlin, Berlin, Germany. · Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany. +5
TRACE: Training-time Report-guided and Clinically Ordered Concept Editing
Aug 21, 2026Wentao Yue, Tianyou Lai, Jiayu Luo +4Concept Bottleneck Models Medical Image Classification
Lanzhou University Lanzhou, China · Shenzhen University Shenzhen, China · Southern Medical University Guangzhou, China +1
Counterfactual Contrastive Analysis
Aug 19, 2026Yunlong He, Pietro GoriCounterfactual Explanations Image Generation
LTCI, Télécom Paris, Institut Polytechnique de Paris, France
Less Annotation, More Interpretation: Prior-Guided Concept Bottleneck Models for Interpretable Cancer Imaging Diagnosis
Aug 13, 2026Baoqiang Ma, Kenneth GilhuijsConcept Bottleneck Models Medical Image Classification
Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
COGENT: Counterfactual Gaussian Explanations for Volumetric Medical Images
Aug 11, 2026Dorian Rząsa, Bartosz Zabdyr, Krzysztof Piekarz +7Counterfactual Explanations Explainable Medical Image Analysis
Jagiellonian University · Warsaw University of Technology · University of Warsaw +2
Uncertainty-Aware and Explainable Ensemble Deep Learning Framework for Multi-Class Skin Lesion Classification
Aug 11, 2026Rofiqul Islam, Lilatul FerdouseSkin Lesion Classification Deep Ensembles
Department of Computer Science and Physics, Wilfrid Laurier University, Waterloo, ON, Canada
P3CA: Encoder-Agnostic Interpretation of Vision Foundation Model Embeddings via Spatial Probing
Aug 10, 2026Amoon Jamzad, Dilakshan Srikanthan, Faranak Akbarifar +2Vision Foundation Models Representation Probing
School of Computing, Queen’s University, Kingston, Ontario, K7L 2N8, Canada
Disentangling Co-Occurring Retinal Pathologies with Saliency-Guided Sparse Expert Routing
Aug 10, 2026Nagur Shareef Shaik, Jeongwoo Park, Yeong-Jin Kim +3Medical Imaging Sparse Mixture-of-Experts
Department of Computer Science, Georgia State University, Atlanta, GA 30324, USA · Piehealthcare Inc., Suwon-si, Gyeonggi-do, 16311, Republic of Korea
PARAGraph: Pathology-Anatomy-Aware Hierarchical Graph for Diabetic Retinopathy Grading
Aug 8, 2026Ziyang Zhang, Yuankai Huo, Yalin Zheng +1Graph Neural Networks Diabetic Retinopathy Grading
Vanderbilt University, USA · University of Liverpool, UK
Distilling CT Foundation Models into Editable Concept Bottlenecks for Lung Nodule Malignancy Prediction
Aug 8, 2026Fakrul Islam Tushar, Stephen Adamo, Geoffrey D. RubinMedical Imaging Foundation Models Concept Bottleneck Models
Department of Radiology and Imaging Sciences, University of Arizona, Tucson, AZ, USA
Beyond Fluency: A Clinical Benchmark and Anomaly-Enhanced Baseline for Spine MRI Report Generation
Aug 7, 2026Bruno Palau, Franziska Vogt, Daria Laslo +4VLM Evaluation Radiology Report Generation
ETH Zurich, Switzerland · 2Swiss Institute of Bioinformatics (SIB), Switzerland
Human-Centered Explainable AI for TinyML Edge Devices: A Pareto-Based Selection Framework with LLM-Guided Design
Aug 7, 2026Zeinab Dehghani, Dhavalkumar Thakker, Koorosh Aslansefat +4Explainable Artificial Intelligence Tiny ML
School of Digital and Physical Sciences, University of Hull, Cottingham Road, Hull, HU6 7RX, United Kingdom
LocAnyMed: Vision-Language Grounding for Multimodal Medical Images
Aug 4, 2026Zihan Wang, Tong Liu, Zhiwei Wang +6Medical VLMs Medical Image Grounding
School of Computer Science, Wuhan University, Wuhan, China · College of Computing and Data Science, Nanyang Technological University, Singapore · Australian Artificial Intelligence Institute, School of Computer Science, University of Technology Sydney, Sydney, Australia +1

Oct 6, 2026, cs.CVJ/K move · Enter open · S save

Beyond Explanation: Debugging Medical Imaging Models via Concept Intervention

Samrajya Thapa, Daniel J. Quest, Timothy L. Kline, Carrie L. Langstraat+2

Iowa State University, Ames IA, USA · Mayo Clinic, Rochester MN, USA

Explainable Medical Image Analysis Concept Bottleneck Models Medical Image Classification

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Medical imaging models often operate as black boxes, limiting interpretability and systematic debugging. We introduce an easy-to-use, plug-and-play framework for concept-based interpretation and model refinement. By aligning a single-modality encoder to BioMedCLIP, we construct a Concept Bottleneck Model (CBM) that enables concept-level interventions. These interventions allow us to isolate causal versus spuriously correlated concepts, validate insights with domain experts, and generate counterfactual samples for targeted fine-tuning. We evaluate our framework on a Mayo Clinic ultrasound dataset and the CheXpert 5x200 chest X-ray dataset. Results demonstrate that concept intervention enables reliable model diagnosis while maintaining, and occasionally improving predictive performance via guided fine-tuning. Our findings highlight the practical value of this framework for controlled, interpretable refinement of clinical deep learning models.

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