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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 311–320 of 436 papers

TitleStatusHype
Brain Tumor Detection Based On Symmetry Information—0
Brain Tumor Segmentation: A Comparative Analysis—0
Brain Tumor Segmentation and Survival Prediction—0
Brain Tumor Segmentation and Survival Prediction using Automatic Hard mining in 3D CNN Architecture—0
Brain Tumor Segmentation (BraTS) Challenge 2024: Meningioma Radiotherapy Planning Automated Segmentation—0
Brain Tumor Segmentation by Cascaded Deep Neural Networks Using Multiple Image Scales—0
Brain Tumor Segmentation from MRI Images using Deep Learning Techniques—0
Brain Tumor Segmentation in MRI Images with 3D U-Net and Contextual Transformer—0
Brain Tumor Segmentation Network Using Attention-based Fusion and Spatial Relationship Constraint—0
Brain Tumor Segmentation on MRI with Missing Modalities—0
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