#267 · Primary category: Computer Vision
MedicalZooPytorch
A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation
Project last updated:07/25/24
GitHub Stars
1.9K
Forks
305
Contributors
5
License
MIT
Why we included this project
For teams doing medical image segmentation in PyTorch, this library collects several 3D network designs, including UNet, VNet, DenseNet, and ResNet variants, plus data loaders for common benchmark sets like BraTS, iSeg, and MRBrainS18. The loaders matter because wrangling volumetric scans into a usable format often eats more time than the modeling itself. The project started as an MSc thesis, and the included Colab notebooks and manual make it a reasonable entry point for students new to 3D segmentation, while the model zoo gives experienced researchers a quick basis for comparisons and experiments.
Articles for this project
No articles for this project yet.
To suggest a topic or contribute an article, contact us.
Related projects in this category
opencv
Open Source Computer Vision Library
RuView
π RuView turns commodity WiFi signals into real-time spatial intelligence, vital sign monitoring, and presence detection — all without a single pixel of video.
PaddleOCR
Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages.
MinerU
Transforms complex documents like PDFs and Office docs into LLM-ready markdown/JSON for your Agentic workflows.
tesseract
Tesseract Open Source OCR Engine (main repository)