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Brain Tumor Segmentation

Brain Tumor Segmentation is a medical image analysis task that involves the separation of brain tumors from normal brain tissue in magnetic resonance imaging (MRI) scans. The goal of brain tumor segmentation is to produce a binary or multi-class segmentation map that accurately reflects the location and extent of the tumor.

( Image credit: Brain Tumor Segmentation with Deep Neural Networks )

Papers

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Showing 1–50 of 436 papers

TitleStatusHype
SegFormer3D: an Efficient Transformer for 3D Medical Image SegmentationCode3
MedSegDiff: Medical Image Segmentation with Diffusion Probabilistic ModelCode3
UNetFormer: A Unified Vision Transformer Model and Pre-Training Framework for 3D Medical Image SegmentationCode3
BraTS orchestrator : Democratizing and Disseminating state-of-the-art brain tumor image analysisCode2
The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)Code2
TransBTSV2: Towards Better and More Efficient Volumetric Segmentation of Medical ImagesCode2
Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI ImagesCode2
TextBraTS: Text-Guided Volumetric Brain Tumor Segmentation with Innovative Dataset Development and Fusion Module ExplorationCode1
Rethinking Brain Tumor Segmentation from the Frequency Domain PerspectiveCode1
DC-Seg: Disentangled Contrastive Learning for Brain Tumor Segmentation with Missing ModalitiesCode1
GBT-SAM: Adapting a Foundational Deep Learning Model for Generalizable Brain Tumor Segmentation via Efficient Integration of Multi-Parametric MRI DataCode1
CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentationCode1
XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-DecoderCode1
cWDM: Conditional Wavelet Diffusion Models for Cross-Modality 3D Medical Image SynthesisCode1
Optimizing Brain Tumor Segmentation with MedNeXt: BraTS 2024 SSA and PediatricsCode1
Enhanced MRI brain tumor detection and classification via topological data analysis and low-rank tensor decompositionCode1
Multiscale Encoder and Omni-Dimensional Dynamic Convolution Enrichment in nnU-Net for Brain Tumor SegmentationCode1
Fed-MUnet: Multi-modal Federated Unet for Brain Tumor SegmentationCode1
SimTxtSeg: Weakly-Supervised Medical Image Segmentation with Simple Text CuesCode1
Unsupervised Domain Adaptation for Pediatric Brain Tumor SegmentationCode1
CAVM: Conditional Autoregressive Vision Model for Contrast-Enhanced Brain Tumor MRI SynthesisCode1
BrainSegFounder: Towards 3D Foundation Models for Neuroimage SegmentationCode1
SiNGR: Brain Tumor Segmentation via Signed Normalized Geodesic Transform RegressionCode1
Federated Modality-specific Encoders and Multimodal Anchors for Personalized Brain Tumor SegmentationCode1
D-Net: Dynamic Large Kernel with Dynamic Feature Fusion for Volumetric Medical Image SegmentationCode1
E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image SegmentationCode1
Prototype-Driven and Multi-Expert Integrated Multi-Modal MR Brain Tumor Image SegmentationCode1
AME-CAM: Attentive Multiple-Exit CAM for Weakly Supervised Segmentation on MRI Brain TumorCode1
M-VAAL: Multimodal Variational Adversarial Active Learning for Downstream Medical Image Analysis TasksCode1
Brain tumor segmentation using synthetic MR images -- A comparison of GANs and diffusion modelsCode1
The Brain Tumor Segmentation (BraTS) Challenge: Local Synthesis of Healthy Brain Tissue via InpaintingCode1
M3AE: Multimodal Representation Learning for Brain Tumor Segmentation with Missing ModalitiesCode1
PCRLv2: A Unified Visual Information Preservation Framework for Self-supervised Pre-training in Medical Image AnalysisCode1
Scratch Each Other's Back: Incomplete Multi-Modal Brain Tumor Segmentation via Category Aware Group Self-Support LearningCode1
Hybrid Window Attention Based Transformer Architecture for Brain Tumor SegmentationCode1
NestedFormer: Nested Modality-Aware Transformer for Brain Tumor SegmentationCode1
SFusion: Self-attention based N-to-One Multimodal Fusion BlockCode1
PA-Seg: Learning from Point Annotations for 3D Medical Image Segmentation using Contextual Regularization and Cross Knowledge DistillationCode1
High-Resolution Swin Transformer for Automatic Medical Image SegmentationCode1
Single MR Image Super-Resolution using Generative Adversarial NetworkCode1
TBraTS: Trusted Brain Tumor SegmentationCode1
mmFormer: Multimodal Medical Transformer for Incomplete Multimodal Learning of Brain Tumor SegmentationCode1
SMU-Net: Style matching U-Net for brain tumor segmentation with missing modalitiesCode1
Translation Consistent Semi-supervised Segmentation for 3D Medical ImagesCode1
Self Pre-training with Masked Autoencoders for Medical Image Classification and SegmentationCode1
Factorizer: A Scalable Interpretable Approach to Context Modeling for Medical Image SegmentationCode1
Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation TaskCode1
Generalized Wasserstein Dice Loss, Test-time Augmentation, and Transformers for the BraTS 2021 challengeCode1
Ensemble CNN Networks for GBM Tumors Segmentation using Multi-parametric MRICode1
Extending nn-UNet for brain tumor segmentationCode1
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