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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 351–400 of 436 papers

TitleStatusHype
One-pass Multi-task Networks with Cross-task Guided Attention for Brain Tumor SegmentationCode0
Optimized U-Net for Brain Tumor SegmentationCode0
Cross-Modality Brain Tumor Segmentation via Bidirectional Global-to-Local Unsupervised Domain AdaptationCode0
FR-MRInet: A Deep Convolutional Encoder-Decoder for Brain Tumor Segmentation with Relu-RGB and Sliding-windowCode0
Optimizing Medical Image Segmentation with Advanced Decoder DesignCode0
HMM Model for Brain Tumor Detection and ClassificationCode0
Distributionally Robust Deep Learning using Hardness Weighted SamplingCode0
Hybrid-Fusion Transformer for Multisequence MRICode0
Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural NetworksCode0
FMG-Net and W-Net: Multigrid Inspired Deep Learning Architectures For Medical Imaging SegmentationCode0
Hypergraph Tversky-Aware Domain Incremental Learning for Brain Tumor Segmentation with Missing ModalitiesCode0
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS ChallengeCode0
Parameter-efficient Fine-tuning for improved Convolutional Baseline for Brain Tumor Segmentation in Sub-Saharan Africa Adult Glioma DatasetCode0
CNN-based Segmentation of Medical Imaging DataCode0
Patient-Specific Real-Time Segmentation in Trackerless Brain UltrasoundCode0
Automatic brain tumor segmentation in 2D intra-operative ultrasound images using MRI tumor annotationsCode0
Category Guided Attention Network for Brain Tumor Segmentation in MRICode0
Autofocus Layer for Semantic SegmentationCode0
Post-hoc Overall Survival Time Prediction from Brain MRICode0
Attention-Enhanced Hybrid Feature Aggregation Network for 3D Brain Tumor SegmentationCode0
FedRef: Communication-Efficient Bayesian Fine Tuning with Reference ModelCode0
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
3D U-Net Based Brain Tumor Segmentation and Survival Days PredictionCode0
Feature Imitating Networks Enhance The Performance, Reliability And Speed Of Deep Learning On Biomedical Image Processing TasksCode0
Whole-brain radiomics for clustered federated personalization in brain tumor segmentationCode0
Exploiting Partial Common Information Microstructure for Multi-Modal Brain Tumor SegmentationCode0
QCResUNet: Joint Subject-level and Voxel-level Segmentation Quality PredictionCode0
AGD-Autoencoder: Attention Gated Deep Convolutional Autoencoder for Brain Tumor SegmentationCode0
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking ResultsCode0
Adaptive feature recombination and recalibration for semantic segmentation with Fully Convolutional NetworksCode0
3D MRI brain tumor segmentation using autoencoder regularizationCode0
Evaluation and Analysis of Different Aggregation and Hyperparameter Selection Methods for Federated Brain Tumor SegmentationCode0
RA-UNet: A hybrid deep attention-aware network to extract liver and tumor in CT scansCode0
Meta-Learned Modality-Weighted Knowledge Distillation for Robust Multi-Modal Learning with Missing DataCode0
Brain tumour segmentation using a triplanar ensemble of U-NetsCode0
Enhancing Incomplete Multi-modal Brain Tumor Segmentation with Intra-modal Asymmetry and Inter-modal DependencyCode0
Magnetic Resonance Imaging Feature-Based Subtyping and Model Ensemble for Enhanced Brain Tumor SegmentationCode0
Adaptive feature recombination and recalibration for semantic segmentation: application to brain tumor segmentation in MRICode0
MAProtoNet: A Multi-scale Attentive Interpretable Prototypical Part Network for 3D Magnetic Resonance Imaging Brain Tumor ClassificationCode0
MBDRes-U-Net: Multi-Scale Lightweight Brain Tumor Segmentation NetworkCode0
SuperLightNet: Lightweight Parameter Aggregation Network for Multimodal Brain Tumor SegmentationCode0
Utilizing Attention, Linked Blocks, And Pyramid Pooling To Propel Brain Tumor Segmentation In 3DCode0
Enhancing Brain Tumor Segmentation Using Channel Attention and Transfer learningCode0
Brain Tumor Segmentation using Enhanced U-Net Model with Empirical AnalysisCode0
Brain Tumor Segmentation Based on Refined Fully Convolutional Neural Networks with A Hierarchical Dice LossCode0
Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion SegmentationCode0
Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithmCode0
3D-DDA: 3D Dual-Domain Attention for Brain Tumor SegmentationCode0
A Weakly Supervised and Globally Explainable Learning Framework for Brain Tumor SegmentationCode0
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