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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 371–380 of 436 papers

TitleStatusHype
Enhancing MRI Brain Tumor Segmentation with an Additional Classification Network—0
Ensemble Learning with Residual Transformer for Brain Tumor Segmentation—0
Experimenting with Knowledge Distillation techniques for performing Brain Tumor Segmentation—0
Exploring SAM Ablations for Enhancing Medical Segmentation in Radiology and Pathology—0
Feature-enhanced Generation and Multi-modality Fusion based Deep Neural Network for Brain Tumor Segmentation with Missing MR Modalities—0
Federated brain tumor segmentation: an extensive benchmark—0
Few-Shot Generation of Brain Tumors for Secure and Fair Data Sharing—0
Flexible Fusion Network for Multi-modal Brain Tumor Segmentation—0
Focus, Segment and Erase: An Efficient Network for Multi-Label Brain Tumor Segmentation—0
Fully Automated Tumor Segmentation for Brain MRI data using Multiplanner UNet—0
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