Research on automatic identification based on IVOCT images of coronary plaque

Qin Li; Hao Sun; Jingbo Wang; Na Qin; Wei Liu

doi:10.1117/12.2537812

Research on automatic identification based on IVOCT images of coronary plaque

Qin Li^*
, Hao Sun
, Jingbo Wang
, Na Qin
, Wei Liu

^*Corresponding author for this work

School of Medical Science and Engineering

Beijing Institute of Technology
North China University of Science and Technology
Capital Medical University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Optics in Health Care and Biomedical Optics IX
Editors	Qingming Luo, Qingming Luo, Xingde Li, Ying Gu, Yuguo Tang, Dan Zhu
Publisher	SPIE
ISBN (Electronic)	9781510630970
DOIs	https://doi.org/10.1117/12.2537812
Publication status	Published - 2019
Event	Optics in Health Care and Biomedical Optics IX 2019 - Hangzhou, China Duration: 21 Oct 2019 → 23 Oct 2019

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	11190
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Conference

Conference	Optics in Health Care and Biomedical Optics IX 2019
Country/Territory	China
City	Hangzhou
Period	21/10/19 → 23/10/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

coronary atherosclerotic plaque
feature selection
intravascular optical coherence tomography
random forests
texture feature extraction

Access to Document

10.1117/12.2537812

Cite this

Li, Q., Sun, H., Wang, J., Qin, N., & Liu, W. (2019). Research on automatic identification based on IVOCT images of coronary plaque. In Q. Luo, Q. Luo, X. Li, Y. Gu, Y. Tang, & D. Zhu (Eds.), Optics in Health Care and Biomedical Optics IX Article 1119008 (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11190). SPIE. https://doi.org/10.1117/12.2537812

@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",

}

Li, Q, Sun, H, Wang, J, Qin, N & Liu, W 2019, Research on automatic identification based on IVOCT images of coronary plaque. in Q Luo, Q Luo, X Li, Y Gu, Y Tang & D Zhu (eds), Optics in Health Care and Biomedical Optics IX., 1119008, Proceedings of SPIE - The International Society for Optical Engineering, vol. 11190, SPIE, Optics in Health Care and Biomedical Optics IX 2019, Hangzhou, China, 21/10/19. https://doi.org/10.1117/12.2537812

Research on automatic identification based on IVOCT images of coronary plaque. / Li, Qin; Sun, Hao; Wang, Jingbo et al.
Optics in Health Care and Biomedical Optics IX. ed. / Qingming Luo; Qingming Luo; Xingde Li; Ying Gu; Yuguo Tang; Dan Zhu. SPIE, 2019. 1119008 (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11190).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Research on automatic identification based on IVOCT images of coronary plaque

AU - Li, Qin

AU - Sun, Hao

AU - Wang, Jingbo

AU - Qin, Na

AU - Liu, Wei

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - coronary atherosclerotic plaque

KW - feature selection

KW - intravascular optical coherence tomography

KW - random forests

KW - texture feature extraction

UR - https://www.scopus.com/pages/publications/85078984698

U2 - 10.1117/12.2537812

DO - 10.1117/12.2537812

M3 - Conference contribution

AN - SCOPUS:85078984698

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Optics in Health Care and Biomedical Optics IX

A2 - Luo, Qingming

A2 - Li, Xingde

A2 - Gu, Ying

A2 - Tang, Yuguo

A2 - Zhu, Dan

PB - SPIE

T2 - Optics in Health Care and Biomedical Optics IX 2019

Y2 - 21 October 2019 through 23 October 2019

ER -

Research on automatic identification based on IVOCT images of coronary plaque

Abstract

Publication series

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UN SDGs

Keywords

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