NDLI: Automatic Assessment of Cardiac Artery Disease by Using DCAD Module

Content Provider	IEEE Xplore Digital Library
Author	Khalilzad-Sharghi, V. Talebpour, A. Kamali-Asl, A. Hendijani, N.
Copyright Year	2008
Description	Author affiliation: Dept. of Med. Radiat. Eng., Shahid Beheshti Univ., Tehran, Iran (Khalilzad-Sharghi, V.; Talebpour, A.; Kamali-Asl, A.)
Abstract	In patients with cardiac artery disease myocardial perfusion scan, which is a non-invasive method, is utilized. This study is conducted to achieve an advantageous software applicable to quantitative myocardial SPECT perfusion. Each cross-section of the left ventricle is segmented by applying fuzzy clustering method. After obtaining the myocardial skeleton of the left ventricle from its short axis cross sections, we make use of fuzzy logic to decide whether the pixel belongs to myocardial muscle and any perfusion perturbation or not. Abnormal critical conditions in rest and stress studies and coronary artery disease diagnosis were investigated in a set of about 200 images. Measurement and allocation of different myocardial sectors to specific coronary arteries were accomplished by utilizing collected information about respectively 75 patient men and 62 patient women, and the validity of artery obstruction diagnosis has been proved in 40 patients having been under the coronary angiography. We named the achieved software DCAD(b) which has demonstrated a considerably good performance in coronary artery occlusion diagnosis and would be a promising method aiding nuclear medicine specialists in diagnosing these defections.
Starting Page	243
Ending Page	246
File Size	641006
Page Count	4
File Format	PDF
ISBN	9780769535234
DOI	10.1109/SYNASC.2008.57
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-09-26
Publisher Place	Romania
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cardiac Artery Disease Clustering methods Cardiac disease Muscles Image Skeleton Arteries Stress SPECT Coronary arteriosclerosis Fuzzy logic Image Processing Myocardium Skeleton Cardiovascular diseases
Content Type	Text
Resource Type	Article

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