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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

Showing 131140 of 436 papers

TitleStatusHype
Segment Anything Model for Brain Tumor Segmentation0
Cheap Lunch for Medical Image Segmentation by Fine-tuning SAM on Few Exemplars0
DSFNet: Dual-GCN and Location-fused Self-attention with Weighted Fast Normalized Fusion for Polyps SegmentationCode0
Automated ensemble method for pediatric brain tumor segmentation0
Automated Ensemble-Based Segmentation of Adult Brain Tumors: A Novel Approach Using the BraTS AFRICA Challenge Data0
Differential Privacy for Adaptive Weight Aggregation in Federated Tumor Segmentation0
Ensemble Learning with Residual Transformer for Brain Tumor Segmentation0
Deepfake Image Generation for Improved Brain Tumor Segmentation0
Prototype-Driven and Multi-Expert Integrated Multi-Modal MR Brain Tumor Image SegmentationCode1
Confidence Intervals for Performance Estimates in Brain MRI Segmentation0
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