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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 176–200 of 436 papers

TitleStatusHype
FedRef: Communication-Efficient Bayesian Fine Tuning with Reference ModelCode0
FMG-Net and W-Net: Multigrid Inspired Deep Learning Architectures For Medical Imaging SegmentationCode0
CNN-based Segmentation of Medical Imaging DataCode0
FR-MRInet: A Deep Convolutional Encoder-Decoder for Brain Tumor Segmentation with Relu-RGB and Sliding-windowCode0
An Optimization Framework for Processing and Transfer Learning for the Brain Tumor SegmentationCode0
Feature Imitating Networks Enhance The Performance, Reliability And Speed Of Deep Learning On Biomedical Image Processing TasksCode0
Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion SegmentationCode0
Attention-Enhanced Hybrid Feature Aggregation Network for 3D Brain Tumor SegmentationCode0
A Tri-attention Fusion Guided Multi-modal Segmentation Network—0
CASPIANET++: A Multidimensional Channel-Spatial Asymmetric Attention Network with Noisy Student Curriculum Learning Paradigm for Brain Tumor Segmentation—0
Cascaded V-Net using ROI masks for brain tumor segmentation—0
A Transformer-based Generative Adversarial Network for Brain Tumor Segmentation—0
Building Brain Tumor Segmentation Networks with User-Assisted Filter Estimation and Selection—0
BRISC: Annotated Dataset for Brain Tumor Segmentation and Classification with Swin-HAFNet—0
BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023—0
Asynchronous Decentralized Federated Lifelong Learning for Landmark Localization in Medical Imaging—0
A Survey and Analysis on Automated Glioma Brain Tumor Segmentation and Overall Patient Survival Prediction—0
BraSyn 2023 challenge: Missing MRI synthesis and the effect of different learning objectives—0
A Structural Graph-Based Method for MRI Analysis—0
Brain Tumor Synthetic Segmentation in 3D Multimodal MRI Scans—0
Brain Tumor Survival Prediction using Radiomics Features—0
Brain tumor segmentation with missing modalities via latent multi-source correlation representation—0
ASC-Net: Unsupervised Medical Anomaly Segmentation Using an Adversarial-based Selective Cutting Network—0
A Feasibility study for Deep learning based automated brain tumor segmentation using Magnetic Resonance Images—0
Artificial Intelligence Solution for Effective Treatment Planning for Glioblastoma Patients—0
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