Real-time carotid plaque recognition from dynamic ultrasound videos based on artificial neural network.

ABSTRACT:

Purpose

Carotid ultrasound allows noninvasive assessment of vascular anatomy and function with real-time display. Based on the transfer learning method, a series of research results have been obtained on the optimal image recognition and analysis of static images. However, for carotid plaque recognition, there are high requirements for self-developed algorithms in real-time ultrasound detection. This study aims to establish an automatic recognition system, Be Easy to Use (BETU), for the real-time and synchronous diagnosis of carotid plaque from ultrasound videos based on an artificial neural network.

Materials and methods

445 participants (mean age, 54.6±7.8 years; 227 men) were evaluated. Radiologists labeled a total of 3259 segmented ultrasound images from 445 videos with

SUBMITTER: Wei Y 

PROVIDER: S-EPMC11466531 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature