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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 401–436 of 436 papers

TitleStatusHype
Brain Tumor Segmentation Based on Deep Learning, Attention Mechanisms, and Energy-Based Uncertainty PredictionCode0
M-GenSeg: Domain Adaptation For Target Modality Tumor Segmentation With Annotation-Efficient SupervisionCode0
Towards fully automated deep-learning-based brain tumor segmentation: is brain extraction still necessary?Code0
Efficient 3D Brain Tumor Segmentation with Axial-Coronal-Sagittal EmbeddingCode0
Brain Tumor Segmentation and Tractographic Feature Extraction from Structural MR Images for Overall Survival PredictionCode0
Modality Completion via Gaussian Process Prior Variational Autoencoders for Multi-Modal Glioma SegmentationCode0
Brain Tumor Detection using Convolutional Neural NetworkCode0
Model Ensemble for Brain Tumor Segmentation in Magnetic Resonance ImagingCode0
Volumetric medical image segmentation through dual self-distillation in U-shaped networksCode0
Weakly Supervised Fine Tuning Approach for Brain Tumor Segmentation ProblemCode0
DSFNet: Dual-GCN and Location-fused Self-attention with Weighted Fast Normalized Fusion for Polyps SegmentationCode0
SEDNet: Shallow Encoder-Decoder Network for Brain Tumor SegmentationCode0
SegAN: Adversarial Network with Multi-scale L_1 Loss for Medical Image SegmentationCode0
Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation ProblemsCode0
Adaptive Active Contour Model for Brain Tumor SegmentationCode0
A4-Unet: Deformable Multi-Scale Attention Network for Brain Tumor SegmentationCode0
Task-oriented Uncertainty Collaborative Learning for Label-Efficient Brain Tumor SegmentationCode0
Arbitrary Scale Super-Resolution for Brain MRI ImagesCode0
A Novel Confidence Induced Class Activation Mapping for MRI Brain Tumor SegmentationCode0
Selective Complementary Feature Fusion and Modal Feature Compression Interaction for Brain Tumor SegmentationCode0
An Optimization Framework for Processing and Transfer Learning for the Brain Tumor SegmentationCode0
3D-TransUNet for Brain Metastases Segmentation in the BraTS2023 ChallengeCode0
Automatic Brain Tumor Segmentation with Scale Attention NetworkCode0
Unified Attentional Generative Adversarial Network for Brain Tumor Segmentation From Multimodal Unpaired ImagesCode0
multiPI-TransBTS: A Multi-Path Learning Framework for Brain Tumor Image Segmentation Based on Multi-Physical InformationCode0
UPMAD-Net: A Brain Tumor Segmentation Network with Uncertainty Guidance and Adaptive Multimodal Feature FusionCode0
Domain Knowledge Based Brain Tumor Segmentation and Overall Survival PredictionCode0
Multi-scale self-guided attention for medical image segmentationCode0
A New Logic For Pediatric Brain Tumor SegmentationCode0
Multi-step Cascaded Networks for Brain Tumor SegmentationCode0
A Multimodal Feature Distillation with CNN-Transformer Network for Brain Tumor Segmentation with Incomplete ModalitiesCode0
Semi-Supervised Variational Autoencoder for Survival PredictionCode0
Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image SegmentationCode0
Development of RLK-Unet: a clinically favorable deep learning algorithm for brain metastasis detection and treatment response assessmentCode0
DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image SegmentationCode0
Decoupling Feature Representations of Ego and Other Modalities for Incomplete Multi-modal Brain Tumor SegmentationCode0
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