Brain Segmentation
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Benchmarks
Brain MRI segmentation
Most implemented
Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional Networks
QuickNAT: A Fully Convolutional Network for Quick and Accurate Segmentation of Neuroanatomy
Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm
MRI Super-Resolution using Multi-Channel Total Variation
CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea Segmentation
A Learning Strategy for Contrast-agnostic MRI Segmentation
Papers
Decoupling Parcellation from Classification: Systematic Benchmark of Fast Brain Segmentation Methods for Alzheimer's Disease Detection
Brain parcellation and classification are typically evaluated in isolation, yet downstream AD detection performance depends on their interaction. We decouple these components and systematically benchmark fast deep learni…
Alzheimer's Disease DetectionBrain SegmentationTowards Reliable and Reproducible Fetal Brain Biometry: A Deep Learning Approach Using MRI
Fetal brain biometry is essential for quantitative assessment of brain development, supporting gestational age estimation, developmental monitoring, and detection of abnormalities. In clinical practice, measurements are …
Brain SegmentationAge EstimationULF-Synth: Physics-Guided Ultra-Low-Field MRI Enhancement for Pediatric Neuroimaging
Ultra-low-field (ULF) MRI offers portable and accessible neuroimaging but suffers from reduced signal-to-noise ratio and limited spatial resolution compared to high-field (HF) systems. Acquiring paired ULF-HF data for su…
Brain SegmentationAutomatic Landmark-Based Segmentation of Human Subcortical Structures in MRI
Precise segmentation of brain structures in magnetic resonance imaging (MRI) is essential for reliable neuroimaging analysis, yet voxel-wise deep models often yield anatomically inconsistent results that diverge from exp…
Semantic SegmentationBrain SegmentationExploring Entropy-based Active Learning for Fair Brain Segmentation
Active learning (AL) has emerged as a crucial strategy for reducing the prohibitive costs associated with medical image segmentation. However, standard uncertainty-based AL methods typically focus on maximizing performan…
Medical Image SegmentationBrain SegmentationActive Learning4DLoG: Generative Modeling of Neurodegenerative Brain Anatomy with 4D Longitudinal Diffusion Model
Modeling and predicting neurodegenerative disease progression from medical images remains a major challenge in medical AI, with significant implications for early diagnosis, disease monitoring, and treatment planning. Ho…
Brain Segmentation