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 51–75 of 436 papers

TitleStatusHype
Enhancing Brain Tumor Classification Using TrAdaBoost and Multi-Classifier Deep Learning Approaches—0
AEPL: Automated and Editable Prompt Learning for Brain Tumor Segmentation—0
Segmentation of Pediatric Brain Tumors using a Radiologically informed, Deep Learning Cascade—0
Two-Stage Approach for Brain MR Image Synthesis: 2D Image Synthesis and 3D Refinement—0
Federated brain tumor segmentation: an extensive benchmark—0
Optimizing Medical Image Segmentation with Advanced Decoder DesignCode0
Enhanced MRI brain tumor detection and classification via topological data analysis and low-rank tensor decompositionCode1
Mind the Gap: Promoting Missing Modality Brain Tumor Segmentation with Alignment—0
Multiscale Encoder and Omni-Dimensional Dynamic Convolution Enrichment in nnU-Net for Brain Tumor SegmentationCode1
multiPI-TransBTS: A Multi-Path Learning Framework for Brain Tumor Image Segmentation Based on Multi-Physical InformationCode0
Model Ensemble for Brain Tumor Segmentation in Magnetic Resonance ImagingCode0
Fed-MUnet: Multi-modal Federated Unet for Brain Tumor SegmentationCode1
Leveraging SeNet and ResNet Synergy within an Encoder-Decoder Architecture for Glioma Detection—0
Intraoperative Glioma Segmentation with YOLO + SAM for Improved Accuracy in Tumor Resection—0
Anatomical Consistency Distillation and Inconsistency Synthesis for Brain Tumor Segmentation with Missing Modalities—0
Detection of Under-represented Samples Using Dynamic Batch Training for Brain Tumor Segmentation from MR Images—0
MedMAP: Promoting Incomplete Multi-modal Brain Tumor Segmentation with Alignment—0
Decoupling Feature Representations of Ego and Other Modalities for Incomplete Multi-modal Brain Tumor SegmentationCode0
A Weakly Supervised and Globally Explainable Learning Framework for Brain Tumor SegmentationCode0
UKAN-EP: Enhancing U-KAN with Efficient Attention and Pyramid Aggregation for 3D Multi-Modal MRI Brain Tumor SegmentationCode0
Promptable Counterfactual Diffusion Model for Unified Brain Tumor Segmentation and Generation with MRIsCode0
BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023—0
Brain Tumor Segmentation in MRI Images with 3D U-Net and Contextual Transformer—0
SimTxtSeg: Weakly-Supervised Medical Image Segmentation with Simple Text CuesCode1
RobU-Net: a heuristic robust multi-class brain tumor segmentation approaches for MRI scans—0
Show:102550
← PrevPage 3 of 18Next →

No leaderboard results yet.