teeth_segmentation
importedsoftware/teeth-segmentation
teeth segmentation using UNet and customize attention module
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Documentation
- unknown
- Tags
- communityexchange · dentistry · educative · learn · medical-imaging · pytorch · unet-image-segmentation
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- calorie-contracommunityexchange
A calorie counter web app that searches for food and keeps tracks of your macros and calories, embedded with a nutritionist chatbot
- CMU-Netpytorch · unet-image-segmentation
[ISBI 2023] Official Pytorch implementation of "CMU-Net: A Strong ConvMixer-based Medical Ultrasound Image Segmentation Network"
- DAEFormerpytorch · unet-image-segmentation
[MICCAI 2023] DAE-Former: Dual Attention-guided Efficient Transformer for Medical Image Segmentation
- SelfReg-UNetmedical-imaging · unet-image-segmentation
Code for the paper "SelfReg-UNet: Self-Regularized UNet for Medical Image Segmentation "
- unetmedical-imaging · unet-image-segmentation
"pip install unet": PyTorch Implementation of 1D, 2D and 3D U-Net architecture.
- UNeXt-pytorchmedical-imaging · unet-image-segmentation
Official Pytorch Code base for "UNeXt: MLP-based Rapid Medical Image Segmentation Network", MICCAI 2022
- api.github.com/repos/saeedahmadicp/teeth_segmentationretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2024-02-26, 26 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/38.json→ .entries["teeth-segmentation"]
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