SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 276–300 of 436 papers

TitleStatusHype
Analysis of the MICCAI Brain Tumor Segmentation -- Metastases (BraTS-METS) 2025 Lighthouse Challenge: Brain Metastasis Segmentation on Pre- and Post-treatment MRI—0
Analyzing Deep Learning Based Brain Tumor Segmentation with Missing MRI Modalities—0
Anatomical Consistency Distillation and Inconsistency Synthesis for Brain Tumor Segmentation with Missing Modalities—0
An End-to-End learnable Flow Regularized Model for Brain Tumor Segmentation—0
An Ensemble Approach for Brain Tumor Segmentation and Synthesis—0
An Inductive Transfer Learning Approach using Cycle-consistent Adversarial Domain Adaptation with Application to Brain Tumor Segmentation—0
Generative Adversarial Networks for Weakly Supervised Generation and Evaluation of Brain Tumor Segmentations on MR Images—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 Performance-Consistent and Computation-Efficient CNN System for High-Quality Automated Brain Tumor Segmentation—0
A Pretrained DenseNet Encoder for Brain Tumor Segmentation—0
A Prior Knowledge Based Tumor and Tumoral Subregion Segmentation Tool for Pediatric Brain Tumors—0
A Review on End-To-End Methods for Brain Tumor Segmentation and Overall Survival Prediction—0
Artificial Intelligence Solution for Effective Treatment Planning for Glioblastoma Patients—0
ASC-Net: Unsupervised Medical Anomaly Segmentation Using an Adversarial-based Selective Cutting Network—0
A Structural Graph-Based Method for MRI Analysis—0
A Survey and Analysis on Automated Glioma Brain Tumor Segmentation and Overall Patient Survival Prediction—0
Asynchronous Decentralized Federated Lifelong Learning for Landmark Localization in Medical Imaging—0
A Transformer-based Generative Adversarial Network for Brain Tumor Segmentation—0
A Tri-attention Fusion Guided Multi-modal Segmentation Network—0
Attention Xception UNet (AXUNet): A Novel Combination of CNN and Self-Attention for Brain Tumor Segmentation—0
Automated 3D Tumor Segmentation using Temporal Cubic PatchGAN (TCuP-GAN)—0
Automated Ensemble-Based Segmentation of Adult Brain Tumors: A Novel Approach Using the BraTS AFRICA Challenge Data—0
Automated ensemble method for pediatric brain tumor segmentation—0
Automated Tumor Segmentation and Brain Mapping for the Tumor Area—0
Show:102550
← PrevPage 12 of 18Next →

No leaderboard results yet.