Evaluation of foundation models for medical image segmentation tasks
PyTorch-based pipeline includes data preprocessing, model inference, and performance evaluation with standard metrics (Dice score, Hausdorff distance). The repository provides tools for visualizing segmentation results and comparing MedSAM-2's performance against baseline models, offering insights into adapting foundation models for medical imaging
Open, modular MCP server for medical image analysis agents: containerized models (MedSAM2, SAM 2.1, TotalSegmentator, lungmask, HD-BET, SynthStrip, nnU-Net, MONAI, TorchXRayVision), preset/custom guidelines, and a code-customizable viewer.
Atlas-Augmented Semantic Segmentation for Robust Ultra-Low-Field Pediatric Brain Imaging
AI-Powered Medical Imaging Analysis & Research Segmentation Platform
TagMed is designed to facilitate the annotation of sensitive images and corresponding medical reports for computer vision projects.
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