@inproceedings{b658dc9fbd2a439499f739c5d8b6e44e,
title = "Research on automatic identification based on IVOCT images of coronary plaque",
abstract = "Coronary heart disease is the fatal cardiovascular disease, as well as the leading killer threatening people's health. Coronary atherosclerosis is the main cause of coronary heart disease, the accurate identification of the coronary atherosclerotic plaques is of great importance for the judgement of the pathological conditions of the vascular and the guidance of subsequent treatment. Due to its extremely high imaging resolution, intravascular optical coherence tomography (IVOCT) has been widely used in the clinical diagnosis and treatment of coronary heart disease, of which one of the important functions is to judge the type of plaque in the diseased vessels. The purpose of this paper is to study an algorithm of the IVOCT plague image automatic recognition, which assists the doctors to analyze the images, so as to improve the accuracy of the plaque recognition.",
keywords = "coronary atherosclerotic plaque, feature selection, intravascular optical coherence tomography, random forests, texture feature extraction",
author = "Qin Li and Hao Sun and Jingbo Wang and Na Qin and Wei Liu",
note = "Publisher Copyright: {\textcopyright} 2019 SPIE.; Optics in Health Care and Biomedical Optics IX 2019 ; Conference date: 21-10-2019 Through 23-10-2019",
year = "2019",
doi = "10.1117/12.2537812",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Qingming Luo and Qingming Luo and Xingde Li and Ying Gu and Yuguo Tang and Dan Zhu",
booktitle = "Optics in Health Care and Biomedical Optics IX",
address = "United States",
}
