Automatic extraction of carotid intima-media by ultrasound based on boundary saliency
YANG Jifeng
WEI Hao
XIONG Fei
HUANG Qinghua
LI Le
ZHOU Guangquan
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.
Keywords：Image segmentationCarotid intima-mediaStripe attentionAuto-encoderCardio-cerebrovascular
Publication Date：2023-12-25
Online Publishing Date：2026-09-11(First online date of this platform, not the publication date of the document)
Pages：6( 350-355 )