Brain-Tumor-Segmentation-and-Survival-Prediction-using-Deep-Neural-Networks
importeddata/brain-tumor-segmentation-and-survival-prediction-using-deep-neural-networks
Use of state of the art Convolutional neural network architectures including 3D UNet, 3D VNet and 2D UNets for Brain Tumor Segmentation and using segmented image features for Survival Prediction of…
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Data & Standards
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/shalabh147/Brain-Tumor-Segmentation-and-Survival-Prediction-using-Deep-Neural-Networks
- Documentation
- unknown
- Tags
- aiformedicine · brain-tumor-segmentation · brats-dataset · cnn-segmentation · deep-learning · deep-neural-networks · dice-coefficient · dice-loss
- Regulatory
- unknown
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- M2FTransbrats-dataset
[IEEE-JBHI'2024] M2FTrans: Modality-Masked Fusion Transformer for Incomplete Multi-Modality Brain Tumor Segmentation
- VT-UNetbrats-dataset
[MICCAI2022] This is an official PyTorch implementation for A Robust Volumetric Transformer for Accurate 3D Tumor Segmentation
- HistoSegdice-loss
HistoSeg is an Encoder-Decoder DCNN which utilizes the novel Quick Attention Modules and Multi Loss function to generate segmentation masks from histopathological images with greater accuracy. This…
- AUDITbrain-tumor-segmentation
AUDIT - Analysis & Evaluation Dashboard of Artificial Intelligence
- Brain-Tumor-Segmentation-using-UNETR-in-TensorFlowbrain-tumor-segmentation
This repository demonstrates the utilization of UNETR for brain tumor segmentation.
- nas_3d_unetbrain-tumor-segmentation
Neural Architecture Search for Gliomas Segmentation on Multimodal Magnetic Resonance Imaging
- api.github.com/repos/shalabh147/Brain-Tumor-Segmentation-and-Survival-Prediction-using-Deep-Neural-Networksretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2020-07-24, 171 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
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