BraTS2018-tumor-segmentation
importedsoftware/brats2018-tumor-segmentation
We provide DeepMedic and 3D UNet in pytorch for brain tumore segmentation. We also integrate location information with DeepMedic and 3D UNet by adding additional brain parcellation with original MR…
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
- Documentation
- unknown
- Tags
- 3d-unet · brain-tumor-segmentaiton · brats · deep-learning · deep-neural-networks · deepmedic · medical-image-segmentation · pytorch · pytorch-3d-unet · pytorch-deepmedic
- Regulatory
- unknown
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- KiU-Net-pytorchbrats · deep-neural-networks · medical-image-segmentation · pytorch
Official Pytorch Code of KiU-Net for Image/3D Segmentation - MICCAI 2020 (Oral), IEEE TMI
- TextMamba3Dbrats · medical-image-segmentation · pytorch
Text-guided 3D brain tumor segmentation with unified Mamba architecture | 基于统一Mamba架构的文本引导3D脑肿瘤分割
- RARE-UNet3d-unet · medical-image-segmentation
This repository features RARE-UNet a resolution-aware 3D U-Net for adaptive medical segmentation. It uses multi-scale entry blocks and resolution-based routing to dynamically adjust the inference…
- U-Net-PyTorch3d-unet · medical-image-segmentation
🧠 Implement U-Net in PyTorch for effective binary image segmentation, focusing on brain tumor detection with a complete pipeline from data prep to evaluation.
- nas_3d_unetbrats · pytorch
Neural Architecture Search for Gliomas Segmentation on Multimodal Magnetic Resonance Imaging
- OSS-Netbrats · pytorch
Official and maintained implementation of the paper "OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data" [BMVC 2021].
- api.github.com/repos/pykao/BraTS2018-tumor-segmentationretrieved 2026-08-25 · via github-api
Machine-imported from GitHub search. Last push 2020-07-17, 112 stars, license reported as NOASSERTION. Category and schematic were assigned by keyword heuristics and are unreviewed. GitHub reported NOASSERTION; the licence was read from the LICENSE file as MIT, because GitHub's detector does not recognise open hardware licences.
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