Face Analysis for Coronary Heart Disease Diagnosis

Shisong Lin; Xiaodong Zhuang; Shiyun Huang; Yahui Liu; Linlin Shen; Xinxue Liao

doi:10.1109/CISP-BMEI48845.2019.8966020

Face Analysis for Coronary Heart Disease Diagnosis

Shisong Lin
, Xiaodong Zhuang
, Shiyun Huang
, Yahui Liu
, Linlin Shen^*
, Xinxue Liao

^*Corresponding author for this work

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

5 Citations (Scopus)

Abstract

CHD (Coronary Heart Disease) is one of the leading causes of cardiovascular disease deaths. Invasive coronary arteriography is one of the widely used approaches to diagnose CHD. However, the time cost and expenses for most of the diagnosis methodologies are high and some patients are reluctant to do such a diagnosis. In this paper, we aim to develop a novel low cost method to predict CHD. As suggested by the cardiologists, there are substantial differences between the facial images of patients with CHD and those of healthy subjects. In this paper, we conduct an automatic analysis of the texture features extracted from eight ROIs (Regions of Interests) of the face images. Based on the texture features, random forest and decision tree are used to predict whether the subject has a CHD, or not. The experimental results on a set of 1528 face images collected from 309 subjects suggest that, our approach achieved a promising, i.e. 72.73%, prediction accuracy.

Original language	English
Title of host publication	Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019
Editors	Qingli Li, Lipo Wang
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728148526
DOIs	https://doi.org/10.1109/CISP-BMEI48845.2019.8966020
Publication status	Published - Oct 2019
Externally published	Yes
Event	12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019 - Huaqiao, China Duration: 19 Oct 2019 → 21 Oct 2019

Publication series

Name	Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019

Conference

Conference	12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019
Country/Territory	China
City	Huaqiao
Period	19/10/19 → 21/10/19

UN SDGs

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

SDG 3 Good Health and Well-being

Free Keywords

CHD
face image
ROIs
texture features

ASJC Scopus subject areas

Information Systems
Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Information Systems and Management

Access to Document

10.1109/CISP-BMEI48845.2019.8966020

Cite this

Lin, S., Zhuang, X., Huang, S., Liu, Y., Shen, L., & Liao, X. (2019). Face Analysis for Coronary Heart Disease Diagnosis. In Q. Li, & L. Wang (Eds.), Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019 Article 8966020 (Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CISP-BMEI48845.2019.8966020

Lin, Shisong ; Zhuang, Xiaodong ; Huang, Shiyun et al. / Face Analysis for Coronary Heart Disease Diagnosis. Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019. editor / Qingli Li ; Lipo Wang. Institute of Electrical and Electronics Engineers Inc., 2019. (Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019).

@inproceedings{ea500084211f4383872516da0fe8cea6,

title = "Face Analysis for Coronary Heart Disease Diagnosis",

abstract = "CHD (Coronary Heart Disease) is one of the leading causes of cardiovascular disease deaths. Invasive coronary arteriography is one of the widely used approaches to diagnose CHD. However, the time cost and expenses for most of the diagnosis methodologies are high and some patients are reluctant to do such a diagnosis. In this paper, we aim to develop a novel low cost method to predict CHD. As suggested by the cardiologists, there are substantial differences between the facial images of patients with CHD and those of healthy subjects. In this paper, we conduct an automatic analysis of the texture features extracted from eight ROIs (Regions of Interests) of the face images. Based on the texture features, random forest and decision tree are used to predict whether the subject has a CHD, or not. The experimental results on a set of 1528 face images collected from 309 subjects suggest that, our approach achieved a promising, i.e. 72.73\%, prediction accuracy.",

keywords = "CHD, face image, ROIs, texture features",

author = "Shisong Lin and Xiaodong Zhuang and Shiyun Huang and Yahui Liu and Linlin Shen and Xinxue Liao",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019 ; Conference date: 19-10-2019 Through 21-10-2019",

year = "2019",

month = oct,

doi = "10.1109/CISP-BMEI48845.2019.8966020",

language = "English",

series = "Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

editor = "Qingli Li and Lipo Wang",

booktitle = "Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019",

address = "United States",

}

Lin, S, Zhuang, X, Huang, S, Liu, Y, Shen, L & Liao, X 2019, Face Analysis for Coronary Heart Disease Diagnosis. in Q Li & L Wang (eds), Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019., 8966020, Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019, Institute of Electrical and Electronics Engineers Inc., 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019, Huaqiao, China, 19/10/19. https://doi.org/10.1109/CISP-BMEI48845.2019.8966020

Face Analysis for Coronary Heart Disease Diagnosis. / Lin, Shisong; Zhuang, Xiaodong; Huang, Shiyun et al.
Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019. ed. / Qingli Li; Lipo Wang. Institute of Electrical and Electronics Engineers Inc., 2019. 8966020 (Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019).

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

TY - GEN

T1 - Face Analysis for Coronary Heart Disease Diagnosis

AU - Lin, Shisong

AU - Zhuang, Xiaodong

AU - Huang, Shiyun

AU - Liu, Yahui

AU - Shen, Linlin

AU - Liao, Xinxue

PY - 2019/10

Y1 - 2019/10

N2 - CHD (Coronary Heart Disease) is one of the leading causes of cardiovascular disease deaths. Invasive coronary arteriography is one of the widely used approaches to diagnose CHD. However, the time cost and expenses for most of the diagnosis methodologies are high and some patients are reluctant to do such a diagnosis. In this paper, we aim to develop a novel low cost method to predict CHD. As suggested by the cardiologists, there are substantial differences between the facial images of patients with CHD and those of healthy subjects. In this paper, we conduct an automatic analysis of the texture features extracted from eight ROIs (Regions of Interests) of the face images. Based on the texture features, random forest and decision tree are used to predict whether the subject has a CHD, or not. The experimental results on a set of 1528 face images collected from 309 subjects suggest that, our approach achieved a promising, i.e. 72.73%, prediction accuracy.

AB - CHD (Coronary Heart Disease) is one of the leading causes of cardiovascular disease deaths. Invasive coronary arteriography is one of the widely used approaches to diagnose CHD. However, the time cost and expenses for most of the diagnosis methodologies are high and some patients are reluctant to do such a diagnosis. In this paper, we aim to develop a novel low cost method to predict CHD. As suggested by the cardiologists, there are substantial differences between the facial images of patients with CHD and those of healthy subjects. In this paper, we conduct an automatic analysis of the texture features extracted from eight ROIs (Regions of Interests) of the face images. Based on the texture features, random forest and decision tree are used to predict whether the subject has a CHD, or not. The experimental results on a set of 1528 face images collected from 309 subjects suggest that, our approach achieved a promising, i.e. 72.73%, prediction accuracy.

KW - CHD

KW - face image

KW - ROIs

KW - texture features

UR - https://www.scopus.com/pages/publications/85079156072

U2 - 10.1109/CISP-BMEI48845.2019.8966020

DO - 10.1109/CISP-BMEI48845.2019.8966020

M3 - Conference contribution

AN - SCOPUS:85079156072

T3 - Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019

BT - Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019

A2 - Li, Qingli

A2 - Wang, Lipo

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019

Y2 - 19 October 2019 through 21 October 2019

ER -

Lin S, Zhuang X, Huang S, Liu Y, Shen L, Liao X. Face Analysis for Coronary Heart Disease Diagnosis. In Li Q, Wang L, editors, Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8966020. (Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019). doi: 10.1109/CISP-BMEI48845.2019.8966020

Face Analysis for Coronary Heart Disease Diagnosis

Abstract

Publication series

Conference

UN SDGs

Free Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this