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M2FTrans

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data/m2ftrans

[IEEE-JBHI'2024] M2FTrans: Modality-Masked Fusion Transformer for Incomplete Multi-Modality Brain Tumor Segmentation

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record
Category
Data & Standards
Subcategory
unknown
License
MIT(osi)
Status
dormant
Maturity
deployed
Organization
unknown
Country
unknown
Documentation
unknown
Tags
brats-dataset · medical-image-segmentation · missing-modalities · pytorch-implementation · transformer
Regulatory
unknown
built by · 1

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similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

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    [MICCAI2022] This is an official PyTorch implementation for A Robust Volumetric Transformer for Accurate 3D Tumor Segmentation

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    nnDetection is a self-configuring framework for 3D (volumetric) medical object detection which can be applied to new data sets without manual intervention. It includes guides for 12 data sets that…

  • DAEFormermedical-image-segmentation · transformer

    [MICCAI 2023] DAE-Former: Dual Attention-guided Efficient Transformer for Medical Image Segmentation

  • Mobile-U-ViTmedical-image-segmentation · transformer

    [ACM MM 2025] Mobile U-ViT: Revisiting large kernel and U-shaped ViT for efficient medical image segmentation

  • TransBTSmedical-image-segmentation · transformer

    This repo provides the official code for : 1) TransBTS: Multimodal Brain Tumor Segmentation Using Transformer (https://arxiv.org/abs/2103.04430) , accepted by MICCAI2021. 2) TransBTSV2: Towards…

sources
  1. api.github.com/repos/Jun-Jie-Shi/M2FTrans
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2024-10-06, 28 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.

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