Semisupervised white matter hyperintensities segmentation on MRI

This study proposed a semisupervised loss function named level‐set loss (LSLoss) for cerebral white matter hyperintensities (WMHs) segmentation on fluid‐attenuated inversion recovery images. The training procedure did not require manually labeled WMH masks. Our image preprocessing steps included bia...

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Veröffentlicht in:	Human brain mapping 2023-03, Vol.44 (4), p.1344-1358
Hauptverfasser:	Huang, Fan, Xia, Peng, Vardhanabhuti, Varut, Hui, Sai‐Kam, Lau, Kui‐Kai, Ka‐Fung Mak, Henry, Cao, Peng
Format:	Artikel
Sprache:	eng
Schlagworte:	Alzheimer Disease Alzheimer's disease Brain - diagnostic imaging brain MRI convolutional neural networks Datasets Deep learning Humans Image processing Image Processing, Computer-Assisted - methods Image segmentation Magnetic resonance imaging Magnetic Resonance Imaging - methods Medical imaging Multiple sclerosis Neural networks Neurodegenerative diseases Neuroimaging Patients Scanners segmentation semisupervised learning Skull small vessel diseases Stroke Substantia alba White Matter - diagnostic imaging white matter hyperintensities
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