Brain Image Segmentation
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Benchmarks
Brain Tumor
CREMI
FIB-25 Synaptic Sites
FIB-25 Whole Test
SegEM
T1-weighted MRI
Most implemented
FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics
Non-local U-Net for Biomedical Image Segmentation
SiNGR: Brain Tumor Segmentation via Signed Normalized Geodesic Transform Regression
Boosting multiple sclerosis lesion segmentation through attention mechanism
Papers
An Uncertainty-Aware Loss Function Incorporating Fuzzy Logic: Application to MRI Brain Image Segmentation
Accurate brain image segmentation, particularly for distinguishing various tissues from magnetic resonance imaging (MRI) images, plays a pivotal role in finding the neurological dis ease and medical image computing. In d…
Brain Image SegmentationAn Intuitionistic Fuzzy Logic Driven UNet architecture: Application to Brain Image segmentation
Accurate segmentation of MRI brain images is essential for image analysis, diagnosis of neuro-logical disorders and medical image computing. In the deep learning approach, the convolutional neural networks (CNNs), especi…
Medical Image SegmentationBrain Image SegmentationBrain SegmentationAddressing Annotation Scarcity in Hyperspectral Brain Image Segmentation with Unsupervised Domain Adaptation
This work presents a novel deep learning framework for segmenting cerebral vasculature in hyperspectral brain images. We address the critical challenge of severe label scarcity, which impedes conventional supervised trai…
Unsupervised Domain AdaptationBrain Image SegmentationSiNGR: Brain Tumor Segmentation via Signed Normalized Geodesic Transform Regression
One of the primary challenges in brain tumor segmentation arises from the uncertainty of voxels close to tumor boundaries. However, the conventional process of generating ground truth segmentation masks fails to treat su…
Brain Image SegmentationBrain Tumor SegmentationImage Segmentationregression+3Deep Learning-Based Brain Image Segmentation for Automated Tumour Detection
Introduction: The present study on the development and evaluation of an automated brain tumor segmentation technique based on deep learning using the 3D U-Net model. Objectives: The objective is to leverage state-of-the-…
Brain Image SegmentationBrain Tumor SegmentationDeep LearningImage Segmentation+3Transferring Ultrahigh-Field Representations for Intensity-Guided Brain Segmentation of Low-Field Magnetic Resonance Imaging
Ultrahigh-field (UHF) magnetic resonance imaging (MRI), i.e., 7T MRI, provides superior anatomical details of internal brain structures owing to its enhanced signal-to-noise ratio and susceptibility-induced contrast. How…
Brain Image SegmentationBrain SegmentationImage SegmentationSegmentation+1