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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 431–436 of 436 papers

TitleStatusHype
Multi-Modal Brain Tumor Segmentation via 3D Multi-Scale Self-attention and Cross-attention—0
Multimodal CNN Networks for Brain Tumor Segmentation in MRI: A BraTS 2022 Challenge Solution—0
Multi Modal Convolutional Neural Networks for Brain Tumor Segmentation—0
Multimodal MRI brain tumor segmentation using random forests with features learned from fully convolutional neural network—0
Multimodal Self-Supervised Learning for Medical Image Analysis—0
Multi-Resolution 3D CNN for MRI Brain Tumor Segmentation and Survival Prediction—0
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