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 101–125 of 436 papers

TitleStatusHype
Deep Learning-Based Brain Image Segmentation for Automated Tumour Detection—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
Deep Learning with Mixed Supervision for Brain Tumor Segmentation—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
Decentralized Gossip Mutual Learning (GML) for brain tumor segmentation on multi-parametric MRI—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
Deepfake Image Generation for Improved 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
Decentralized Differentially Private Segmentation with PATE—0
Show:102550
← PrevPage 5 of 18Next →

No leaderboard results yet.