MCTSeg
importedsoftware/mctseg
[Preprint] Official implementation of "A Multimodal Feature Distillation with CNN-Transformer Network for Brain Tumor Segmentation with Incomplete Modalities".
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- BSD-3-Clause(osi)
- Status
- maintained
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/mkang315/MCTSeg
- Documentation
- unknown
- Tags
- 3d-cnn-model · 3d-computer-vision · 3d-convolutional-network · 3d-mri-segmentation · brain-tumor-segmentation · cross-modal-fusion · cross-modality · deep-neural-networks · dice-loss · feature-distillation · hybrid-transformer · knowledge-distillation · medical-image-analysis · medical-image-computing · medical-image-segmentation · multimodal-deep-learning · multimodality-fusion · semantic-segmentation · transformer-segmentation · unimodal-map
- Regulatory
- unknown
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- AUDITbrain-tumor-segmentation · medical-image-analysis · medical-image-computing · medical-image-segmentation
AUDIT - Analysis & Evaluation Dashboard of Artificial Intelligence
- Brain-Tumor-Segmentation-and-Survival-Prediction-using-Deep-Neural-Networksbrain-tumor-segmentation · deep-neural-networks · dice-loss
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…
- medical-segmentation-pytorchknowledge-distillation · medical-image-segmentation
PyTorch implementation of medical semantic segmentations models, e.g. UNet, UNet++, DUCKNet, ResUNet, ResUNet++, and support knowledge distillation, distributed training, Optuna etc.
- HyperDenseNet3d-convolutional-network · deep-neural-networks
This repository contains the code of HyperDenseNet, a hyper-densely connected CNN to segment medical images in multi-modal image scenarios.
- SE-Attention-Half-UNetdice-loss · medical-image-segmentation
Implementation of a compact Attention Half U-Net with Attention Gates and Squeeze-and-Excitation blocks for medical image segmentation. Features a modular PyTorch pipeline, BCE-Dice hybrid loss,…
- BEFUnethybrid-transformer
A Hybrid CNN-Transformer Architecture for Precise Medical Image Segmentation
- api.github.com/repos/mkang315/MCTSegretrieved 2026-08-25 · via github-api
Machine-imported from GitHub search. Last push 2025-12-15, 6 stars, license reported as BSD-3-Clause. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/12.json→ .entries["mctseg"]
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