Brain Tumor Segmentation
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Benchmarks
BRATS 2018
BRATS 2019
BRATS-2015
BRATS-2013
BRATS-2017 val
BRATS-2013 leaderboard
768 chest X-ray images
BRATS 2018 val
BRATS-2014
BRISC
BraTS-Africa
BraTs Peds 2024
Most implemented
Attention U-Net: Learning Where to Look for the Pancreas
Brain Tumor Segmentation with Deep Neural Networks
3D MRI brain tumor segmentation using autoencoder regularization
Brain Tumor Segmentation and Radiomics Survival Prediction: Contribution to the BRATS 2017 Challenge
Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural Networks
TBraTS: Trusted Brain Tumor Segmentation
Papers
De-GAN - Dynamic Parameter Tuned GAN for 3D Medical Image Segmentation: A Step Towards Generalisation
Brain tumor segmentation remains difficult because enhancing tumor (ET) has low contrast and overlaps surrounding tissue, while scanner and site variation causes domain shift. We propose DE-GAN, a contrast-enhancing cond…
Medical Image SegmentationBrain Tumor SegmentationGSToken: Geometry-Structured Gaussian Tokens for Compact 3D Medical Image Representation
Effective segmentation of multi-modal MRI is central to improving neural network accuracy in brain tumor recognition. Existing methods typically compress 3D volumes into token sequences via fixed patch encoding or learne…
Brain Tumor SegmentationSimilarity Weighted Aggregation with Global Differential Privacy for Federated Brain Lesion Segmentation
Federated Learning (FL) enables collaborative training of machine learning models across multiple institutions without sharing sensitive data, making it particularly suitable for medical imaging applications. However, he…
Brain Tumor SegmentationLesion SegmentationFederated LearningMIND: Multimodal Intent-Driven Network via Diffusion Transformers for Medical Image Fusion
Medical image fusion aims to integrate complementary information from diverse imaging modalities to support clinical diagnosis. Existing methods typically apply uniform fusion rules globally, lacking a deep understanding…
Brain Tumor SegmentationPartial Information Decomposition as a Multi-Contrast 3D MRI Selection Strategy for Resource-Constrained Deep Neural Network Training in Brain Tumor Segmentation
Multi-contrast 3D MRI segmentation can be computationally demanding when all available sequences are used. We evaluate a pre-training Partial Information Decomposition framework that ranks input pairs according to their …
Brain Tumor SegmentationRUFNet: Query-Guided Support Mask Refinement and Uncertainty Fusion based on Hybrid Mamba for Few-Shot Brain Tumor Segmentation
Few-shot brain tumor segmentation remains challenging due to noisy support masks, inter-patient variations between support and query images, and the lack of pixel-wise confidence estimation. This study proposes RUFNet, a…
Medical Image SegmentationBrain Tumor Segmentation