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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 376–400 of 436 papers

TitleStatusHype
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
Fully Automatic Brain Tumor Segmentation using a Normalized Gaussian Bayesian Classifier and 3D Fluid Vector Flow—0
GANet-Seg: Adversarial Learning for Brain Tumor Segmentation with Hybrid Generative Models—0
Generating 3D Brain Tumor Regions in MRI using Vector-Quantization Generative Adversarial Networks—0
Glioblastoma Multiforme Patient Survival Prediction—0
Global Planar Convolutions for improved context aggregation in Brain Tumor Segmentation—0
H2NF-Net for Brain Tumor Segmentation using Multimodal MR Imaging: 2nd Place Solution to BraTS Challenge 2020 Segmentation Task—0
Here Comes the Explanation: A Shapley Perspective on Multi-contrast Medical Image Segmentation—0
Hierarchical multi-class segmentation of glioma images using networks with multi-level activation function—0
HI-Net: Hyperdense Inception 3D UNet for Brain Tumor Segmentation—0
HNF-Netv2 for Brain Tumor Segmentation using multi-modal MR Imaging—0
Hybrid Multihead Attentive Unet-3D for Brain Tumor Segmentation—0
Image-level supervision and self-training for transformer-based cross-modality tumor segmentation—0
Impact of Spherical Coordinates Transformation Pre-processing in Deep Convolution Neural Networks for Brain Tumor Segmentation and Survival Prediction—0
Improving 3D U-Net for Brain Tumor Segmentation by Utilizing Lesion Prior—0
Improving the Segmentation of Pediatric Low-Grade Gliomas through Multitask Learning—0
Incomplete Multi-modal Brain Tumor Segmentation via Learnable Sorting State Space Model—0
Incremental Learning for Heterogeneous Structure Segmentation in Brain Tumor MRI—0
Integrating Edges into U-Net Models with Explainable Activation Maps for Brain Tumor Segmentation using MR Images—0
Interactive Image Selection and Training for Brain Tumor Segmentation Network—0
Intraoperative Glioma Segmentation with YOLO + SAM for Improved Accuracy in Tumor Resection—0
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