Intelligent Segmentation of Intima –Media and Plaque Recognition in Carotid Artery Ultrasound Images

Ultrasound imaging has been established as an effective method for measuring the thickness of the intima –media, the thickening of which, along with carotid plaque, is an indicator of cerebrovascular diseases. Here, a 2-D V-Net model that can automatically segment the intima–media in carotid artery ultrasound images is proposed. Moreover, a plaque recognition algorithm that automatically identifies plaque-affected areas is described. Performance tests to determine the average accuracy of the intima–media segmentation yielded the following results (expressed as lumen–intima boundary/media–adventitia boundary): intersection over union (IOU) of 0.752/0.813, pixel accuracy of 0.813/0.885 an d Dice loss of 0.858/0.897.
Source: Ultrasound in Medicine and Biology - Category: Radiology Authors: Tags: Original Contribution Source Type: research