ArticleScientific data2024
MedSegBench: A comprehensive benchmark for medical image segmentation in diverse data modalities.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Why Only 3D for 3D? 2D-Guided Supervision for 3D Medical Vision-Language Models.KDD : proceedings. International Conference on Knowledge Discovery & Data Mining · 2026Article
- NucFuseRank: Dataset Fusion and Performance Ranking for Nuclei Instance Segmentation.Bioengineering (Basel, Switzerland) · 2026Article
- Benchmarking deep learning models for laryngeal cancer staging using the LaryngealCT dataset.Scientific reports · 2026Article
- SULBA: A Task-Agnostic Data Augmentation Framework for Deep Learning in Medical Image Analysis.Diagnostics (Basel, Switzerland) · 2026Article
- Foreign Body Response to Neuroimplantation: Machine Learning-Assisted Quantitative Analysis of Astrogliosis.International journal of molecular sciences · 2026Article
- AI-based detection of Certas Plus shunt valve settings in CT scans.Scientific reports · 2026Article
- A Large-Scale Peripheral Blood Cell Dataset for Automated Hematological Analysis.Scientific data · 2026Article
- Post-MI: unsupervised brain tissue segmentation via post-maximized mutual information.Frontiers in medicine · 2026Article
- Predictive AI in Clinical Pharmacology: A Call to Action to Develop Robust Benchmarking Practices.CPT: pharmacometrics & systems pharmacology · 2026Article
- A Structured Review and Quantitative Profiling of Public Brain MRI Datasets for Foundation Model Development.Journal of imaging · 2025Review
- RepSAU-Net: Semantic Segmentation of Barcodes in Complex Backgrounds via Fused Self-Attention and Reparameterization Methods.Journal of imaging · 2025Article
- Self-Attention Diffusion Models for Zero-Shot Biomedical Image Segmentation: Unlocking New Frontiers in Medical Imaging.Bioengineering (Basel, Switzerland) · 2025Article
- Artificial Intelligence for Organelle Segmentation in Live-Cell Imaging.Research (Washington, D.C.) · 2025Review
- Applications, image analysis, and interpretation of computer vision in medical imaging.Frontiers in radiology · 2025Review
- Exploring Multi-Pathology Brain Segmentation: From Volume-Based to Component-Based Deep Learning Analysis.Journal of imaging · 2024Article
- MedSegBench: A comprehensive benchmark for medical image segmentation in diverse data modalities.Scientific data · 2024Article
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Authors and funding
2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
MedSegBench is a comprehensive benchmark designed to evaluate deep learning models for medical image segmentation across a wide range of modalities. It covers a wide range of modalities, including 35 datasets with over 60,000 images from ultrasound, MRI, and X-ray. The benchmark addresses challenges in medical imaging by providing standardized datasets with train/validation/test splits, considering variability in image quality and dataset imbalances. The benchmark supports binary and multi-class segmentation tasks with up to 19 classes and uses the U-Net architecture with various encoder/decoder networks such as ResNets, EfficientNet, and DenseNet for evaluations. MedSegBench is a valuable resource for developing robust and flexible segmentation algorithms and allows for fair comparisons across different models, promoting the development of universal models for medical tasks. It is the most comprehensive study among medical segmentation datasets. The datasets and source code are publicly available, encouraging further research and development in medical image analysis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.