Medical Image Benchmarks

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Overview

Medical image benchmarks provide datasets, annotations, and shared protocols for comparing systems on tasks such as segmentation, diagnosis, image synthesis, and report generation across modalities including CT, MRI, X-rays, ultrasound, and pathology. They evaluate methods ranging from U-Net and nnU-Net models to vision transformers, foundation models, and multimodal language models, using measures such as Dice, AUROC, calibration, and expert review. A central challenge is whether strong results transfer across patients, hospitals, scanners, populations, and difficult cases; external testing, patient-level splits, and audits for leakage and shortcuts help expose gaps hidden by average scores. The field is moving toward workflow-based and evidence-grounded evaluation, but there is still tension between standardized, easily comparable scores and measures that reflect clinical safety, uncertainty, and real-world usefulness.

Latest papers

CardsList

339 papers31 papers in the last four weeks, up 7% on the four weeks before. 0.2% of all new papers.

  1. Benchmarking Deep Learning Models for Laryngeal Cancer Staging Using the LaryngealCT Dataset

    Oct 13, 2025Nivea Roy, Son Tran, Atul Sajjanhar +4Medical Image ClassificationOncology

    School of Information Technology, Deakin University, Burwood, Australia · Department of Head and Neck Surgery, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India · Department of Radiodiagnosis and Imaging, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India +1

  2. Revisiting Performance Claims for Chest X-Ray Models Using Clinical Context

    Sep 24, 2025Andrew Wang, Jiashuo Zhang, Michael OberstChest X-Ray ClassificationDistribution Shift

    Brown University · Johns Hopkins University

  3. Subcortical Masks Generation in CT Images via Ensemble-Based Cross-Domain Label Transfer

    Aug 15, 2025Augustine X. W. Lee, Pak-Hei Yeung, Jagath C. RajapakseCross-Modality Medical Image SegmentationMedical Image Segmentation

    College of Computing and Data Science, Nanyang Technological University, Singapore

  4. EndoCogniAgent: Closed-Loop Agentic Reasoning with Self-Consistency Validation for Endoscopic Diagnosis

    Aug 10, 2025Yi Tang, Kai-Ni Wang, Liang-Peng Pu +3EndoscopyMedical Imaging

    School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China · Jiangsu Key Laboratory of Biomaterials and Devices, Southeast University, Nanjing 211189, China · State Key Laboratory of Digital Medical Engineering, Southeast University, Nanjing 211189, China +2

  5. Trexplorer Super: Topologically Correct Centerline Tree Tracking of Tubular Objects in CT Volumes

    Jul 15, 2025Roman Naeem, David Hagerman, Jennifer Alvén +2Medical Image Analysis3D Medical Imaging

    Chalmers University of Technology, 412 96 Gothenburg, Sweden

  6. Benchmarking Classification Tasks of Chest X-ray AI Across Multinational Public and Private Datasets: a retrospective diagnostic accuracy study

    May 21, 2025Qinmei Xu, Yiheng Li, Wenya Zhao +21Chest X-Ray ClassificationMedical Image Benchmarks

    Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine, Stanford University, Stanford, CA, USA · Department of Radiology, the Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing, China · Stanford Breast Imaging, Department of Radiology, Stanford University, Stanford, CA, USA +3

  7. OncoReg: Medical Image Registration for Oncological Challenges

    Mar 29, 2025Wiebke Heyer, Yannic Elser, Lennart Berkel +15Medical Image RegistrationCross-Modal Image Registration

    Institute of Medical Informatics, University of Lübeck, Lübeck, Germany · Institute of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Lübeck, Germany · Department of Biomedical Engineering and Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, USA +8

  8. SegCol Challenge: Semantic Segmentation for Tools and Fold Edges in Colonoscopy data

    Dec 20, 2024Xinwei Ju, Rema Daher, Razvan Caramalau +7EndoscopyImage Segmentation

    UCL Hawkes Institute, University College London, London, UK · Department of Computer Science, University College London, London, UK · Medtronic, London, UK +3

  9. The TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography

    Dec 29, 2023Kaiyuan Yang, Fabio Musio, Yihui Ma +112Image SegmentationMedical Image Segmentation