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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 126–150 of 436 papers

TitleStatusHype
Efficient embedding network for 3D brain tumor segmentation—0
Brain Tumor Segmentation from MRI Images using Deep Learning Techniques—0
Brain Tumor Segmentation by Cascaded Deep Neural Networks Using Multiple Image Scales—0
A Pretrained DenseNet Encoder for Brain Tumor Segmentation—0
Brain Tumor Segmentation (BraTS) Challenge 2024: Meningioma Radiotherapy Planning Automated Segmentation—0
A Performance-Consistent and Computation-Efficient CNN System for High-Quality Automated Brain Tumor Segmentation—0
A deep learning model integrating FCNNs and CRFs for brain tumor segmentation—0
A Novel Method for Automatic Segmentation of Brain Tumors in MRI Images—0
A Novel SLCA-UNet Architecture for Automatic MRI Brain Tumor Segmentation—0
A Deep Learning Approach for Brain Tumor Classification and Segmentation Using a Multiscale Convolutional Neural Network—0
Brain Tumor Segmentation and Survival Prediction using Automatic Hard mining in 3D CNN Architecture—0
Domain Game: Disentangle Anatomical Feature for Single Domain Generalized Segmentation—0
Election of Collaborators via Reinforcement Learning for Federated Brain Tumor Segmentation—0
Ensemble Learning with Residual Transformer for Brain Tumor Segmentation—0
Brain Tumor Segmentation and Survival Prediction—0
Generative Adversarial Networks for Weakly Supervised Generation and Evaluation of Brain Tumor Segmentations on MR Images—0
Brain Tumor Segmentation: A Comparative Analysis—0
AdaViT: Adaptive Vision Transformer for Flexible Pretrain and Finetune with Variable 3D Medical Image Modalities—0
DIGEST: Deeply supervIsed knowledGE tranSfer neTwork learning for brain tumor segmentation with incomplete multi-modal MRI scans—0
Dilated Inception U-Net (DIU-Net) for Brain Tumor Segmentation—0
Brain Tumor Detection Based On Symmetry Information—0
Brain Tumor Detection Based On Mathematical Analysis and Symmetry Information—0
An Inductive Transfer Learning Approach using Cycle-consistent Adversarial Domain Adaptation with Application to Brain Tumor Segmentation—0
Brain Tumor Classification by Cascaded Multiscale Multitask Learning Framework Based on Feature Aggregation—0
Brain MRI study for glioma segmentation using convolutional neural networks and original post-processing techniques with low computational demand—0
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