Ultrasound carotid plaque segmentation via image reconstruction-based self-supervised learning with limited training labels

Carotid total plaque area (TPA) is an important contributing measurement to the evaluation of stroke risk. Deep learning provides an efficient method for ultrasound carotid plaque segmentation and TPA quantification. However, high performance of deep learning requires datasets with many labeled imag...

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Veröffentlicht in:	Mathematical biosciences and engineering : MBE Jg. 20; H. 2; S. 1617 - 1636
Hauptverfasser:	Zhou, Ran, Ou, Yanghan, Fang, Xiaoyue, Azarpazhooh, M. Reza, Gan, Haitao, Ye, Zhiwei, Spence, J. David, Xu, Xiangyang, Fenster, Aaron
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States AIMS Press 01.01.2023
Schlagworte:	Algorithms Carotid Arteries - diagnostic imaging carotid plaque convolutional neural network Humans Image Processing, Computer-Assisted - methods self-supervised learning Supervised Machine Learning Ultrasonography ultrasound image segmentation ultrasound image segmentation self-supervised learning carotid plaque convolutional neural network
ISSN:	1551-0018, 1551-0018
Online-Zugang:	Volltext
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