BSMNet: Boundary-salience multi-branch network for intima-media identification in carotid ultrasound images.

Autor: Zhou GQ; The School of Biological Science and Medical Engineering, Southeast University, Nanjing, China; Jiangsu Key Laboratory of Biomaterials and Devices, Southeast University, Nanjing, China; State Key Laboratory of Digital Medical Engineering, Southeast University, Nanjing, China. Electronic address: guangquan.zhou@seu.edu.cn., Wei H; The School of Biological Science and Medical Engineering, Southeast University, Nanjing, China., Wang X; Shenzhen Delica Medical Equipment Co., Ltd, Shenzhen, 518132, China. Electronic address: Gm@delicasz.com., Wang KN; The School of Biological Science and Medical Engineering, Southeast University, Nanjing, China; Jiangsu Key Laboratory of Biomaterials and Devices, Southeast University, Nanjing, China; State Key Laboratory of Digital Medical Engineering, Southeast University, Nanjing, China., Chen Y; The School of Biological Science and Medical Engineering, Southeast University, Nanjing, China., Xiong F; Ethics Committee of Medical and Experimental Animals, Northwestern Polytechnical University, Xi'an, China., Ren G; Shenzhen Delica Medical Equipment Co., Ltd, Shenzhen, 518132, China., Liu C; Ethics Committee of Medical and Experimental Animals, Northwestern Polytechnical University, Xi'an, China., Li L; Institute of Medical Research, Northwestern Polytechnical University, Xi'an, China. Electronic address: lile5@nwpu.edu.cn., Huang Q; School of Artificial Intelligence, OPtics and ElectroNics (iOPEN), Northwestern Polytechnical University, Xi'an, China. Electronic address: qhhuang@nwpu.edu.cn.
Jazyk: angličtina
Zdroj: Computers in biology and medicine [Comput Biol Med] 2023 Aug; Vol. 162, pp. 107092. Date of Electronic Publication: 2023 May 27.
DOI: 10.1016/j.compbiomed.2023.107092
Abstrakt: Carotid artery intima-media thickness (CIMT) is an essential factor in signaling the risk of cardiovascular diseases, which is commonly evaluated using ultrasound imaging. However, automatic intima-media segmentation and thickness measurement are still challenging due to the boundary ambiguity of intima-media and inherent speckle noises in ultrasound images. In this work, we propose an end-to-end boundary-salience multi-branch network, BSMNet, to tackle the carotid intima-media identification from ultrasound images, where the prior shape knowledge and anatomical dependence are exploited using a parallel linear structure learning modules followed by a boundary refinement module. Moreover, we design a strip attention model to boost the thin strip region segmentation with shape priors, in which an anisotropic kernel shape captures long-range global relations and scrutinizes meaningful local salient contexts simultaneously. Extensive experimental results on an in-house carotid ultrasound (US) dataset demonstrate the promising performance of our method, which achieves about 0.02 improvement in Dice and HD95 than other state-of-the-art methods. Our method is promising in advancing the analysis of systemic arterial disease with ultrasound imaging.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper
(Copyright © 2023 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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