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
Deep Learning-Based Concurrent Brain Registration and Tumor SegmentationCode1
Diffusion Models for Implicit Image Segmentation EnsemblesCode1
DeepSeg: Deep Neural Network Framework for Automatic Brain Tumor Segmentation using Magnetic Resonance FLAIR ImagesCode1
Demystifying Brain Tumour Segmentation Networks: Interpretability and Uncertainty AnalysisCode1
ASC-Net : Adversarial-based Selective Network for Unsupervised Anomaly SegmentationCode1
E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image SegmentationCode1
D-Net: Dynamic Large Kernel with Dynamic Feature Fusion for Volumetric Medical Image SegmentationCode1
Robust Multimodal Brain Tumor Segmentation via Feature Disentanglement and Gated FusionCode1
A Joint Graph and Image Convolution Network for Automatic Brain Tumor SegmentationCode1
DR-Unet104 for Multimodal MRI brain tumor segmentationCode1
Abstracting Deep Neural Networks into Concept Graphs for Concept Level InterpretabilityCode1
Brain Tumor Segmentation with Deep Neural NetworksCode1
Attention-Guided Version of 2D UNet for Automatic Brain Tumor SegmentationCode1
AME-CAM: Attentive Multiple-Exit CAM for Weakly Supervised Segmentation on MRI Brain TumorCode1
BrainSegFounder: Towards 3D Foundation Models for Neuroimage SegmentationCode1
ACN: Adversarial Co-training Network for Brain Tumor Segmentation with Missing ModalitiesCode1
A Two-Stage Cascade Model with Variational Autoencoders and Attention Gates for MRI Brain Tumor SegmentationCode1
BiTr-Unet: a CNN-Transformer Combined Network for MRI Brain Tumor SegmentationCode1
Extending nn-UNet for brain tumor segmentationCode1
A Robust Volumetric Transformer for Accurate 3D Tumor SegmentationCode1
Brain Tumor Segmentation and Radiomics Survival Prediction: Contribution to the BRATS 2017 ChallengeCode1
Brain tumor segmentation using synthetic MR images -- A comparison of GANs and diffusion modelsCode1
Brain Tumor Segmentation and Survival Prediction using 3D Attention UNetCode1
Generalized Wasserstein Dice Loss, Test-time Augmentation, and Transformers for the BraTS 2021 challengeCode1
Enhanced MRI brain tumor detection and classification via topological data analysis and low-rank tensor decompositionCode1
Show:102550
← PrevPage 3 of 18Next →

No leaderboard results yet.