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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 326–350 of 436 papers

TitleStatusHype
A Multi-task Contextual Atrous Residual Network for Brain Tumor Detection & Segmentation—0
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
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
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
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
A Computation-Efficient CNN System for High-Quality Brain Tumor Segmentation—0
Multi-Domain Image Completion for Random Missing Input Data—0
Adaptive feature recombination and recalibration for semantic segmentation with Fully Convolutional NetworksCode0
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
An Inductive Transfer Learning Approach using Cycle-consistent Adversarial Domain Adaptation with Application to Brain Tumor Segmentation—0
Decentralized Differentially Private Segmentation with PATE—0
Arbitrary Scale Super-Resolution for Brain MRI ImagesCode0
Brain tumor segmentation with missing modalities via latent multi-source correlation representation—0
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