Medical Image Classification

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53 papers in the last four weeks, up 8% on the four weeks before. 0.3% of all new papers.

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Integrating Implicit and Explicit Relational Biases through Graph-Based Multiple Instance Learning: A Case Study in Skin Lesion Diagnosis
Aug 6, 2026Rafał Buler, Jakub Buler, Maciej Bobowicz +1Skin Lesion Classification Graph Representation Learning
Gdańsk University of Technology · Gda´nsk University of Technology, Gda´nsk, Poland · Medical University of Gdańsk +1
Big, Bright, or Invisible: A Frozen-Feature Benchmark of 3D CT Foundation Models
Aug 6, 2026Maulik Chevli, Johannes Brandt, Rickmer Braren +23D Foundation Models Medical Imaging Foundation Models
Chair for AI in Healthcare and Medicine, Technical University of Munich (TUM) and TUM University Hospital, Munich, Germany · Dept. of Diagnostic and Interventional Radiology, UKE Hamburg, Germany · Dept. of Computing, Imperial College London, UK +1
STAIL: Semantic Text-Anchored Incremental Learning for Medical Imaging via Large Language Models
Aug 6, 2026Songpan Gao, Yajie Zhang, Guanxing Chen +9Continual Learning Medical Image Classification
Segmentation Pre-training for Label-Efficient Lumbar Spine Degeneration Grading
Aug 5, 2026Monzon Maria, Zisserman Andrew, Jutzeler Catherine R. +1Medical Image Classification Medical Image Representation Learning
Biomedical Data Science Lab, Dept. D-HEST, ETH Zurich, Zurich, Switzerland · Swiss Institute of Bioinformatics (SIB), Lausanne, 1015, Switzerland · Visual Geometry Group, Dept. of Engineering Science, University of Oxford, UK
DisMix: Order-Aware Mixup for Medical Imaging via Disentangling Ordinal and Non-Ordinal Features
Aug 5, 2026Dileepa Pitawela, Gustavo Carneiro, Hsiang-Ting ChenDisentangled Representation Learning Data Augmentation
1AIML, Adelaide University, Australia · 2CVSSP, University of Surrey, UK
LiNC: Lightweight Noise Correction via Per-Sample Trust and Gaussian Mixture Modeling
Aug 4, 2026Abhishek Moturu, Babak Taati, Anna GoldenbergMedical Image Classification Noisy-Label Learning
Department of Computer Science University of Toronto The Hospital for Sick Children UHN KITE Research Institute T-CAIREM Vector Institute · Department of Computer Science Institute of Biomedical Engineering University of Toronto Rehabilitation Sciences Institute UHN KITE Research Institute Vector Institute · Department of Computer Science Department of Laboratory Medicine and Pathobiology University of Toronto The Hospital for Sick Children T-CAIREM Vector Institute
Multimodal Skin Lesion Classification with Swin Transformer and Clinical Metadata Fusion
Aug 4, 2026Nethmi Pathirana, Isuru Munasinghe, Dileeka AlwisSkin Lesion Classification Multimodal Classification
School of Computing, Informatics Institute of Technology, Colombo, Sri Lanka · Department of Electronic and Telecommunication Engineering, University of Moratuwa, Katubedda, Sri Lanka
How Many Labels Are Enough? ALDA: Active Learning Deployment Advisor for Medical Image Classification
Aug 4, 2026Julia Machnio, Mads Nielsen, Mostafa Mehdipour GhaziActive Learning Medical Image Classification
Pioneer Centre for AI, University of Copenhagen, Copenhagen, Denmark
Recurrent Contrastive Learning for Imbalanced Medical Image Classification
Aug 4, 2026Zhiyuan Zhu, Xinling Meng, Junxuan Yu +15Class-Imbalanced Learning Contrastive Learning
School of Biomedical Engineering, Medical School, Shenzhen University, China · Ultra-X AI Lab, Shenzhen University, Guangdong, China · School of Biomedical Engineering, South-Central Minzu University, Wuhan, China +4
SecondOpinion: Anatomy-Aware Gated Reasoning for Efficient Medical Image Analysis
Aug 3, 2026Siam Tahsin Bhuiyan, Rashedur Rahman, Sefatul Wasi +4Chest X-Ray Classification Medical Image Analysis
Center for Computational & Data Sciences, Independent University, Bangladesh, Dhaka, Bangladesh · Department of Computer Science and Engineering, Independent University, Bangladesh, Dhaka, Bangladesh · Graduate School of Engineering, University of Hyogo, Kobe, Japan
XEns-CKD: An Explainable Ensemble-Based Approach for Chronic Kidney Disease Stage Detection
Aug 2, 2026Rehan Ahmad, Gousia Habib, Muhammad Shaban +1Medical Image Classification Clinical Prediction
SVKM’s, NMIMS, Mukesh Patel School of Technology Management and Engineering, Shirpur, Maharashtra, India. · *2FCAI Fellow University of Helsinki and ELLIS Institute Helsinki, Finland · COER University, Roorkee, India +1
MoPET: Parameter-Efficient Mixture-of-Experts for Unified Medical Image Classification
Jul 31, 2026Sebastian Doerrich, Daniel Würtinger, Francesco Di Salvo +2Medical Imaging Foundation Models Medical Image Classification
xAILab Bamberg, University of Bamberg, Bamberg, Germany
Classification of COVID-19 cases from chest CT volumes using hybrid model of 3D CNN and 3D MLP-Mixer
Jul 31, 2026Masahiro Oda, Tong Zheng, Yuichiro Hayashi +53D Medical Imaging Medical Image Classification
aInformation and Communications, Nagoya University, Nagoya, Japan · bGraduate School of Informatics, Nagoya University, Nagoya, Japan · cGraduate School of Science and Technology, Nara Institute of Science and Technology, Nara, Japan +3
Performance of large language models in the optical diagnosis of colorectal polyps
Jul 31, 2026Joshua C. Vences, William T. Tran, Nikko Gimpaya +15Endoscopy Multimodal Large Language Models
1. Scarborough Health Network Research Institute, Toronto, Ontario, Canada · 2. Division of Gastroenterology, Hepatology and Nutrition, and The SickKids Learning and Research Institutes, The Hospital for Sick Children, Toronto, Ontario, Canada · 3. Department of Paediatrics, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada +11
Automated classification method of COVID-19 cases from chest CT volumes using 2D and 3D hybrid CNN for anisotropic volumes
Jul 31, 2026Masahiro Oda, Tong Zheng, Yuichiro Hayashi +5Medical Image Classification Convolutional Neural Networks
Information Strategy Office, Information and Communications, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi, 464-8601, Japan · Graduate School of Informatics, Nagoya University, Nagoya, Japan · Graduate School of Science and Technology, Nara Institute of Science and Technology, Nara, Japan +3
ScaFE: Data-Efficient Scar Classification with LLM-Generated Clinical Feature Programs
Jul 30, 2026Ruman Wang, Hangting YeLLM-Based Program Synthesis Medical Image Classification
Liaoning University of Traditional Chinese Medicine · School of Artificial Intelligence, Jilin University
What Makes Deep Learning Work for Traditional Chinese Medicine Tongue Diagnosis? A Comprehensive Ablation Study
Jul 30, 2026Longxia Gao, Linan Wang, Yuhe Han +3Medical Diagnosis Medical Image Classification
College of Traditional Chinese Medicine, Hebei University, Baoding, Hebei, China
MPP-GNN: Subject-Adaptive Community Detection for fMRI-Based Alzheimer's Disease Classification
Jul 29, 2026Yang Zhang, Xiao Zhou, Jonathan Warrell +3Graph Neural Networks Graph Pooling
Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520 USA · Department of Psychiatry, Robert Wood Johnson Medical School, and the Brain Health Institute, Rutgers University, Piscataway, NJ 08854 USA · School of Design, Pratt Institute, New York, NY 11205 USA
Shared Semantic Codebook Distillation for Unpaired Cross-Modal Medical Classification
Jul 29, 2026Dillan Imans, Phuoc-Nguyen Bui, Duc-Tai Le +1Cross-Modal Knowledge Distillation Medical Image Classification
Department of Computer Science and Engineering, Sungkyunkwan University, Suwon, South Korea · Convergence Research Institute, Sungkyunkwan University, Suwon, South Korea · Department of AI Systems Engineering, Sungkyunkwan University, Suwon, South Korea +1
Toward Multi-Modal Deep Learning for Pulmonary Disease Classification: A Texture-Based Machine Learning Pilot Study on Public Chest X-Ray Data
Jul 29, 2026Yogisri Pujitha ChinthotiChest X-Ray Classification Medical Image Classification
Independent Researcher, Bengaluru, India
PRISM-Net: Patient-specific reference-guided inter-breast symmetry matching for three-class breast DCE-MRI classification
Jul 29, 2026Boya Zhang, Shuaiwen Zhou, Di Kong +7Medical Image Analysis Medical Image Classification
Nankai University, No. 94 Weijin Road, Nankai District, Tianjin, 300071, China · Zhongguancun Academy, Beijing, China · Beijing University of Posts and Telecommunications, Beijing, China +5
Searching for Robust Augmentations to Improve Out-of-Domain Generalization in Dermoscopic Skin Cancer Classification
Jul 29, 2026Alexander Kozachok, Ilya Latyshev, Evgeny Karpulevich +3Skin Lesion Classification Data Augmentation
Trusted AI Research Center, Russian Academy of Sciences, 109004 Moscow, Russia
An Attention-Based Framework for Alzheimers Disease Classification Using Resting-State fMRI
Jul 29, 2026Harshiddhi Pathak, Gowtham Reddy N, Mrinal Acharya +1Alzheimer's Disease Functional Connectivity
School of Medical Science and Technology · Department of Computer Science and Engineering at the Indian Institute of Technology Gandhinagar · Dr B C Roy Multi Speciality Medical Research Centre, Indian Institute of Technology Kharagpur, India
LLM-Guided Initialization for Accelerated Hybrid Quantum-Classical Medical Image Classification
Jul 29, 2026Riza Alaudin Syah, Irwan Alnarus Kautsar, Haza Nuzly Bin Abdull HamedNeural Network Initialization Hybrid Quantum-Classical ML
Faculty of Computing Universiti Teknologi Malaysia Johor Bahru, Malaysia · Remote Student based in Jakarta, Indonesia · Informatics Department Faculty of Science and Technology Universitas Muhammadiyah Sidoarjo Sidoarjo, Indonesia
Interpretable Image-Level Acne Severity Grading via EfficientNet-B0 Transfer Learning and Grad-CAM
Jul 29, 2026Sophie Zeng, Sean Kalaycioglu, Collin Hong +1Medical Diagnosis Medical Image Classification
Dr. Robot Inc., Toronto, ON, Canada · Department of Aerospace Engineering, Toronto Metropolitan University, Toronto, ON, Canada · Skinopathy Inc., Toronto, ON, Canada
Re-thinking Mammography Transfer Learning: The Dataset-Informed Transfer Learning (DITL) Framework for Breast Cancer Screening and Lesion Diagnosis
Jul 28, 2026Adarsh Bhandary Panambur, Siming Bayer, Andreas MaierMetric Learning Medical Image Classification
Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany · Siemens Healthineers, Erlangen, Germany
Long-Tailed Medical Image Classification
Jul 26, 2026Nathanael Ren, Saagar AryaClass-Imbalanced Learning Long-Tailed Classification
Pratt School of Engineering Duke University Durham, NC 27708, USA
BoneAgeTW2: Automated Skeletal Maturation Assessment via the Tanner-Whitehouse 2 Method, Deep Learning, and Clinical Report Generation with Distribution Curves
Jul 25, 2026Juan Manuel Castillo PintoMedical Image Classification
Maestria en Inteligencia Artificial Universidad de La Salle, Bogota, Colombia
Gradient-Based Latent Decomposition Reveals Mechanisms of Feature Degradation in Weakly Supervised Mammography
Jul 24, 2026Vinceline Bertrand, Ionut CardeiVariational Autoencoders Hierarchical Representation Learning
Florida Atlantic University, Boca Raton, FL, USA
Do emulated quantum circuits change what CNNs look at? Performance and explainability comparison in medical image classification
Jul 23, 2026Guillermo Rubiños Rodríguez, Martín Ottavianelli, Mateo Alonso +4Quantum Convolutional Neural Networks Quantum-Inspired ML
Instituto Tecnol´ogico de Galicia, Cant´on Grande 9, Planta 3, 15003 A Coru˜na, Spain · Centro Singular de Investigaci´on en Tecnolox´ıas Intelixentes (CiTIUS), Universidade de Santiago de Compostela, Santiago de Compostela, 15782, Spain · Department of Neuroradiology, LMU University Hospital, Ludwig Maximilian University of Munich, Marchioninistraße 15, 81377 Munich, Germany +1

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Integrating Implicit and Explicit Relational Biases through Graph-Based Multiple Instance Learning: A Case Study in Skin Lesion Diagnosis

Rafał Buler, Jakub Buler, Maciej Bobowicz, Michał Grochowski

Gdańsk University of Technology · Gda´nsk University of Technology, Gda´nsk, Poland · Medical University of Gdańsk+1

Skin Lesion Classification Graph Representation Learning Medical Image Classification

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Relational inductive biases are essential for capturing structural dependencies among data. This study investigates a dual-level relational framework for image classification, bridging the gap between implicit representation learning and explicit structural modelling. We begin by establishing a baseline using an EfficientNetB3 architecture. To move beyond standard convolutional biases, we adopt a patch-based strategy, employing a convolutional masked autoencoder to learn implicit inter-patch relationships through self-supervised reconstruction. We then extend this approach by incorporating explicit relational modelling, organizing the learned embeddings into various graph topologies, including grid-based, random, and k-nearest neighbour structures. Experimental results on the ISIC-2018 and ISIC-2019 skin lesion diagnosis benchmarks show that combining implicit inter-patch modelling with explicit graph-based message passing yields the best performance. On the ISIC-2018 test set, the baseline model achieves a balanced accuracy of 76.17%, which improves to 77.12% with implicit patch-based relational modelling. The fully integrated grid-structured Graph Attention Network further increases performance to 79.27%. Similarly, on ISIC-2019, the implicit approach reaches 59.84% balanced accuracy, while the combination of implicit and explicit modelling yields 60.67%.