Detection of Cardiac Artery Disease by Using the DCAD (b) Module

Introduction: In patients with cardiac artery disease, a myocardial perfusion scan, which is a non-invasive method, is utilized. This study is conducted to develop an advantageous software applicable to quantitative myocardial SPECT perfusion. Material and Methods: Each cross-section of the left ven...

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Main Authors: Vahid Khalilzad Sharghi, Alireza Talebpour, Alireza Kamali-Asl, Seyed Mahmoudreza Aghamiri
Format: Article
Language:English
Published: Mashhad University of Medical Sciences 2009-06-01
Series:Iranian Journal of Medical Physics
Subjects:
FCM
Online Access:http://ijmp.mums.ac.ir/article_7293_05bb443fea95c88ff287875e3ce749cd.pdf
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spelling doaj-e9d58fddd94348ae82c5d27b44fa3e822020-11-24T23:07:43ZengMashhad University of Medical SciencesIranian Journal of Medical Physics2345-36722345-36722009-06-0162274010.22038/ijmp.2009.72937293Detection of Cardiac Artery Disease by Using the DCAD (b) ModuleVahid Khalilzad Sharghi0Alireza Talebpour1Alireza Kamali-Asl2Seyed Mahmoudreza Aghamiri3M.Sc. in Medical Radiation Engineering, Radiation Medicine Dept., Shahid-Beheshti University, Tehran, IranAssistant Professor, Radiation Medicine Dept., Shahid-Beheshti University, Tehran, IranAssociate Professor, Radiation Medicine Dept., Shahid-Beheshti University, Tehran, IranAssociate Professor, Radiation Medicine Dept., Shahid-Beheshti University, Tehran, IranIntroduction: In patients with cardiac artery disease, a myocardial perfusion scan, which is a non-invasive method, is utilized. This study is conducted to develop an advantageous software applicable to quantitative myocardial SPECT perfusion. Material and Methods: Each cross-section of the left ventricle was segmented by applying a fuzzy clustering method. After obtaining the myocardial skeleton of the left ventricle from its short axis cross sections, we made use of fuzzy logic to decide whether the pixel belongs to the myocardial muscle and any perfusion perturbation or not. The reconstructed image was divided into 18 equivolume sectors. The features were extracted in each sector and, finally, were compared with a normal data bank. Results: Abnormal critical conditions in rest and stress studies and coronary artery disease diagnosis were investigated in a set of about 317 images. Measurement and allocation of different myocardial sectors to specific coronary arteries were accomplished by utilizing collected information about the patients (75 men and 62 women), and the validity of the artery obstruction diagnosis has been proven in 40 patients undergoing coronary angiography. Conclusion: Our developed software DCAD (b) has demonstrated a considerably good performance in the diagnosis of coronary artery occlusion and can be a promising method aiding nuclear medicine specialists in their diagnosis.http://ijmp.mums.ac.ir/article_7293_05bb443fea95c88ff287875e3ce749cd.pdfCardiac Artery DiseaseFuzzy MethodFCMImage ProcessingImage SkeletonSPECT
collection DOAJ
language English
format Article
sources DOAJ
author Vahid Khalilzad Sharghi
Alireza Talebpour
Alireza Kamali-Asl
Seyed Mahmoudreza Aghamiri
spellingShingle Vahid Khalilzad Sharghi
Alireza Talebpour
Alireza Kamali-Asl
Seyed Mahmoudreza Aghamiri
Detection of Cardiac Artery Disease by Using the DCAD (b) Module
Iranian Journal of Medical Physics
Cardiac Artery Disease
Fuzzy Method
FCM
Image Processing
Image Skeleton
SPECT
author_facet Vahid Khalilzad Sharghi
Alireza Talebpour
Alireza Kamali-Asl
Seyed Mahmoudreza Aghamiri
author_sort Vahid Khalilzad Sharghi
title Detection of Cardiac Artery Disease by Using the DCAD (b) Module
title_short Detection of Cardiac Artery Disease by Using the DCAD (b) Module
title_full Detection of Cardiac Artery Disease by Using the DCAD (b) Module
title_fullStr Detection of Cardiac Artery Disease by Using the DCAD (b) Module
title_full_unstemmed Detection of Cardiac Artery Disease by Using the DCAD (b) Module
title_sort detection of cardiac artery disease by using the dcad (b) module
publisher Mashhad University of Medical Sciences
series Iranian Journal of Medical Physics
issn 2345-3672
2345-3672
publishDate 2009-06-01
description Introduction: In patients with cardiac artery disease, a myocardial perfusion scan, which is a non-invasive method, is utilized. This study is conducted to develop an advantageous software applicable to quantitative myocardial SPECT perfusion. Material and Methods: Each cross-section of the left ventricle was segmented by applying a fuzzy clustering method. After obtaining the myocardial skeleton of the left ventricle from its short axis cross sections, we made use of fuzzy logic to decide whether the pixel belongs to the myocardial muscle and any perfusion perturbation or not. The reconstructed image was divided into 18 equivolume sectors. The features were extracted in each sector and, finally, were compared with a normal data bank. Results: Abnormal critical conditions in rest and stress studies and coronary artery disease diagnosis were investigated in a set of about 317 images. Measurement and allocation of different myocardial sectors to specific coronary arteries were accomplished by utilizing collected information about the patients (75 men and 62 women), and the validity of the artery obstruction diagnosis has been proven in 40 patients undergoing coronary angiography. Conclusion: Our developed software DCAD (b) has demonstrated a considerably good performance in the diagnosis of coronary artery occlusion and can be a promising method aiding nuclear medicine specialists in their diagnosis.
topic Cardiac Artery Disease
Fuzzy Method
FCM
Image Processing
Image Skeleton
SPECT
url http://ijmp.mums.ac.ir/article_7293_05bb443fea95c88ff287875e3ce749cd.pdf
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