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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 101–125 of 436 papers

TitleStatusHype
Efficient Brain Tumor Segmentation Using a Dual-Decoder 3D U-Net with Attention Gates (DDUNet)—0
Multi-Modal Brain Tumor Segmentation via 3D Multi-Scale Self-attention and Cross-attention—0
Here Comes the Explanation: A Shapley Perspective on Multi-contrast Medical Image Segmentation—0
AdaViT: Adaptive Vision Transformer for Flexible Pretrain and Finetune with Variable 3D Medical Image Modalities—0
Few-Shot Generation of Brain Tumors for Secure and Fair Data Sharing—0
Attention Xception UNet (AXUNet): A Novel Combination of CNN and Self-Attention for Brain Tumor Segmentation—0
PSO-UNet: Particle Swarm-Optimized U-Net Framework for Precise Multimodal Brain Tumor Segmentation—0
Selective Complementary Feature Fusion and Modal Feature Compression Interaction for Brain Tumor SegmentationCode0
Task-oriented Uncertainty Collaborative Learning for Label-Efficient Brain Tumor SegmentationCode0
Clinical Inspired MRI Lesion Segmentation—0
Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation—0
Deep Ensemble approach for Enhancing Brain Tumor Segmentation in Resource-Limited Settings—0
Position Paper: Building Trust in Synthetic Data for Clinical AI—0
AMM-Diff: Adaptive Multi-Modality Diffusion Network for Missing Modality Imputation—0
Enhancing Brain Tumor Segmentation Using Channel Attention and Transfer learningCode0
Generative Style Transfer for MRI Image Segmentation: A Case of Glioma Segmentation in Sub-Saharan AfricaCode0
Incomplete Multi-modal Brain Tumor Segmentation via Learnable Sorting State Space Model—0
KMD: Koopman Multi-modality Decomposition for Generalized Brain Tumor Segmentation under Incomplete Modalities—0
SuperLightNet: Lightweight Parameter Aggregation Network for Multimodal Brain Tumor SegmentationCode0
Election of Collaborators via Reinforcement Learning for Federated Brain Tumor Segmentation—0
Recommender Engine Driven Client Selection in Federated Brain Tumor Segmentation—0
Parameter-efficient Fine-tuning for improved Convolutional Baseline for Brain Tumor Segmentation in Sub-Saharan Africa Adult Glioma DatasetCode0
Unified HT-CNNs Architecture: Transfer Learning for Segmenting Diverse Brain Tumors in MRI from Gliomas to Pediatric Tumors—0
QCResUNet: Joint Subject-level and Voxel-level Segmentation Quality PredictionCode0
A4-Unet: Deformable Multi-Scale Attention Network for Brain Tumor SegmentationCode0
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