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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 101–150 of 436 papers

TitleStatusHype
End-to-end autoencoding architecture for the simultaneous generation of medical images and corresponding segmentation masks—0
ASC-Net: Unsupervised Medical Anomaly Segmentation Using an Adversarial-based Selective Cutting Network—0
Brain tumor segmentation with missing modalities via latent multi-source correlation representation—0
A Feasibility study for Deep learning based automated brain tumor segmentation using Magnetic Resonance Images—0
Enhancing Brain Tumor Classification Using TrAdaBoost and Multi-Classifier Deep Learning Approaches—0
Artificial Intelligence Solution for Effective Treatment Planning for Glioblastoma Patients—0
AEPL: Automated and Editable Prompt Learning for Brain Tumor Segmentation—0
Brain Tumor Segmentation Using Deep Learning by Type Specific Sorting of Images—0
Brain Tumor Segmentation using an Ensemble of 3D U-Nets and Overall Survival Prediction using Radiomic Features—0
A Review on End-To-End Methods for Brain Tumor Segmentation and Overall Survival Prediction—0
Efficient Brain Tumor Segmentation Using a Dual-Decoder 3D U-Net with Attention Gates (DDUNet)—0
Brain Tumor Segmentation using 3D-CNNs with Uncertainty Estimation—0
Brain Tumor Survival Prediction using Radiomics Features—0
Brain Tumor Synthetic Segmentation in 3D Multimodal MRI Scans—0
Brain Tumor Segmentation on MRI with Missing Modalities—0
Empirical Evaluation of the Segment Anything Model (SAM) for Brain Tumor Segmentation—0
BraSyn 2023 challenge: Missing MRI synthesis and the effect of different learning objectives—0
Adult Glioma Segmentation in Sub-Saharan Africa using Transfer Learning on Stratified Finetuning Data—0
Brain Tumor Segmentation Network Using Attention-based Fusion and Spatial Relationship Constraint—0
BRISC: Annotated Dataset for Brain Tumor Segmentation and Classification with Swin-HAFNet—0
Building Brain Tumor Segmentation Networks with User-Assisted Filter Estimation and Selection—0
Brain Tumor Segmentation in MRI Images with 3D U-Net and Contextual Transformer—0
A Prior Knowledge Based Tumor and Tumoral Subregion Segmentation Tool for Pediatric Brain Tumors—0
CASPIANET++: A Multidimensional Channel-Spatial Asymmetric Attention Network with Noisy Student Curriculum Learning Paradigm for Brain Tumor Segmentation—0
A Tri-attention Fusion Guided Multi-modal Segmentation Network—0
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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