生物医学工程研究2023，Vol.42Issue(4)：350-355,6.DOI:10.19529/j.cnki.1672-6278.2023.04.07
基于边界显著性的超声颈动脉内中膜的智能提取
Automatic extraction of carotid intima-media by ultrasound based on boundary saliency
杨继锋 1韦浩 1熊飞 2黄庆华 3李乐 4周光泉1
作者信息
- 1. 东南大学 生物科学与医学工程学院,南京 210096
- 2. 深圳市德力凯医疗设备股份有限公司,深圳 518132
- 3. 西北工业大学 光电与智能研究院,西安 710072
- 4. 西北工业大学 医学研究所,西安 710072
- 折叠
摘要
Abstract
In order to further improve the accuracy of intima-media extraction and measurement by ultrasound,we proposed an im-proved segmentation network based on U-Net model to achieve accurate extraction of carotid intima-media.Firstly,the stripe attention module was added to the network to solve the problem of traditional convolutional restricted receptive field by using prior shape and ana-tomical information.In addition,by combining the post processing refinement module.The interference of noise and artifacts in the im-age was reduced better,and the estimation error was corrected by learning from the intrinsic film shape features of the inner and middle film.The test was carried out in the database of 1000 carotid artery ultrasound images collected.The segmentation Dice reached 0.932,and the average error of the thickness of the inner and media membranes was 0.914 pixels.This research is expected to provide impor-tant reference value for the automatic analysis of arterial diseases.关键词
图像分割/颈动脉内中膜/条形注意力/自编码器/心脑血管Key words
Image segmentation/Carotid intima-media/Stripe attention/Auto-encoder/Cardio-cerebrovascular分类
医药卫生引用本文复制引用
杨继锋,韦浩,熊飞,黄庆华,李乐,周光泉..基于边界显著性的超声颈动脉内中膜的智能提取[J].生物医学工程研究,2023,42(4):350-355,6.
