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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 301–350 of 436 papers

TitleStatusHype
Inter-slice Context Residual Learning for 3D Medical Image SegmentationCode1
Efficient embedding network for 3D brain tumor segmentation—0
SoftSeg: Advantages of soft versus binary training for image segmentation—0
Automatic Brain Tumor Segmentation with Scale Attention NetworkCode0
DR-Unet104 for Multimodal MRI brain tumor segmentationCode1
A Two-Stage Cascade Model with Variational Autoencoders and Attention Gates for MRI Brain Tumor SegmentationCode1
Generalized Wasserstein Dice Score, Distributionally Robust Deep Learning, and Ranger for brain tumor segmentation: BraTS 2020 challengeCode1
nnU-Net for Brain Tumor SegmentationCode1
Brain tumor segmentation with self-ensembled, deeply-supervised 3D U-net neural networks: a BraTS 2020 challenge solutionCode1
Brain Tumor Segmentation Network Using Attention-based Fusion and Spatial Relationship Constraint—0
Impact of Spherical Coordinates Transformation Pre-processing in Deep Convolution Neural Networks for Brain Tumor Segmentation and Survival Prediction—0
Does anatomical contextual information improve 3D U-Net based brain tumor segmentation?—0
What is the best data augmentation for 3D brain tumor segmentation?Code1
Context Aware 3D UNet for Brain Tumor Segmentation—0
Modality-Pairing Learning for Brain Tumor Segmentation—0
SAR: Scale-Aware Restoration Learning for 3D Tumor Segmentation—0
Unsupervised Region-based Anomaly Detection in Brain MRI with Adversarial Image Inpainting—0
KiU-Net: Overcomplete Convolutional Architectures for Biomedical Image and Volumetric SegmentationCode1
Enhancing MRI Brain Tumor Segmentation with an Additional Classification Network—0
Brain Tumor Segmentation using 3D-CNNs with Uncertainty Estimation—0
Qutrit-inspired Fully Self-supervised Shallow Quantum Learning Network for Brain Tumor Segmentation—0
Brain Tumor Survival Prediction using Radiomics Features—0
Spherical coordinates transformation pre-processing in Deep Convolution Neural Networks for brain tumor segmentation in MRI—0
Abstracting Deep Neural Networks into Concept Graphs for Concept Level InterpretabilityCode1
A Computation-Efficient CNN System for High-Quality Brain Tumor Segmentation—0
Deep Learning Based Brain Tumor Segmentation: A SurveyCode1
CANet: Context Aware Network for 3D Brain Glioma SegmentationCode1
Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restorationCode1
Multi-Domain Image Completion for Random Missing Input Data—0
Adaptive feature recombination and recalibration for semantic segmentation with Fully Convolutional NetworksCode0
3D Self-Supervised Methods for Medical ImagingCode1
A Review on End-To-End Methods for Brain Tumor Segmentation and Overall Survival Prediction—0
Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation ProblemsCode0
Neural Architecture Search for Gliomas Segmentation on Multimodal Magnetic Resonance ImagingCode1
An Inductive Transfer Learning Approach using Cycle-consistent Adversarial Domain Adaptation with Application to Brain Tumor Segmentation—0
DeepSeg: Deep Neural Network Framework for Automatic Brain Tumor Segmentation using Magnetic Resonance FLAIR ImagesCode1
Decentralized Differentially Private Segmentation with PATE—0
Arbitrary Scale Super-Resolution for Brain MRI ImagesCode0
Attention-Guided Version of 2D UNet for Automatic Brain Tumor SegmentationCode1
Deep Learning-Based Concurrent Brain Registration and Tumor SegmentationCode1
Brain tumor segmentation with missing modalities via latent multi-source correlation representation—0
Segmentation of brain tumor on magnetic resonance imaging using a convolutional architecture—0
DDU-Nets: Distributed Dense Model for 3D MRI Brain Tumor Segmentation—0
Robust Multimodal Brain Tumor Segmentation via Feature Disentanglement and Gated FusionCode1
Knowledge Distillation for Brain Tumor SegmentationCode1
Brain Tumor Segmentation by Cascaded Deep Neural Networks Using Multiple Image Scales—0
Distributionally Robust Deep Learning using Hardness Weighted SamplingCode0
Robust Semantic Segmentation of Brain Tumor Regions from 3D MRIsCode1
Transfer Learning for Brain Tumor Segmentation—0
Robustness of Brain Tumor Segmentation—0
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