Unet2d
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| 3dunetcnn | 1,750 | 3 months ago | 8 | mit | Python | |||||
| Pytorch 3D U-Net Convolution Neural Network (CNN) designed for medical image segmentation | ||||||||||
| Ssl4mis | 1,595 | 9 months ago | 25 | mit | Python | |||||
| Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations. | ||||||||||
| Attention Gated Networks | 1,099 | 3 years ago | mit | Python | ||||||
| Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation | ||||||||||
| Unet Family | 1,029 | 4 years ago | 4 | Python | ||||||
| Paper and implementation of UNet-related model. | ||||||||||
| Medicalzoopytorch | 896 | 2 years ago | 13 | mit | Python | |||||
| A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation | ||||||||||
| Medpy | 523 |  | 15 | 29 | 4 months ago | 6 | February 14, 2019 | 6 | gpl-3.0 | Python |
| Medical image processing in Python | ||||||||||
| Vnet.pytorch | 421 | 6 years ago | 20 | bsd-3-clause | Python | |||||
| A PyTorch implementation for V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation | ||||||||||
| Ai News | 361 | 4 years ago | 1 | |||||||
| Summarize the paper and code in AI(Semantic Segmentation, Medical Segmentation,REID,Super-Resolution,Registration,CVPR,ECCV,ICCV,AAAI,MICCAI) | ||||||||||
| Miscnn | 338 | a year ago | 60 | February 11, 2022 | 55 | gpl-3.0 | Python | |||
| A framework for Medical Image Segmentation with Convolutional Neural Networks and Deep Learning | ||||||||||
| Self Supervised Fewshot Medical Image Segmentation | 314 | 6 months ago | 5 | mit | Python | |||||
| [ECCV'20] Self-supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation (code&data-processing pipeline) | ||||||||||
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