NAG-Net: Nested attention-guided learning for segmentation of carotid lumen-intima interface and media-adventitia interface

Cardiovascular diseases (CVD), as the leading cause of death in the world, poses a serious threat to human health. The segmentation of carotid Lumen-intima interface (LII) and Media-adventitia interface (MAI) is a prerequisite for measuring intima-media thickness (IMT), which is of great significanc...

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Veröffentlicht in:	Computers in biology and medicine Jg. 156; S. 106718
Hauptverfasser:	Huang, Qinghua, Zhao, Liangrun, Ren, Guanqing, Wang, Xiaoyi, Liu, Chunying, Wang, Wei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Elsevier Ltd 01.04.2023 Elsevier Limited
Schlagworte:	Accuracy Adventitia - diagnostic imaging Artificial intelligence Asymmetric encoder–decoder architecture Attention Attention mechanism Biology Cardiovascular Diseases Carotid arteries Carotid Arteries - diagnostic imaging Carotid Intima-Media Thickness Coders Contours Deep learning Feature extraction Humans Image Processing, Computer-Assisted - methods Internal Medicine LII and MAI segmentation Medical image segmentation Methods Other Segmentation Thickness measurement Transfer learning Tunica Intima - diagnostic imaging Ultrasonic imaging Veins & arteries Visual perception Attention mechanism Asymmetric encoder–decoder architecture LII and MAI segmentation Medical image segmentation
ISSN:	0010-4825, 1879-0534, 1879-0534
Online-Zugang:	Volltext
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