DocumentCode :
241043
Title :
Automatic cardiac MRI localization method
Author :
Mousa, Doaa ; Zayed, Nourhan ; Yassine, Inas A.
Author_Institution :
Comput. & Syst., Electron. Res. Inst., Giza, Egypt
fYear :
2014
fDate :
11-13 Dec. 2014
Firstpage :
153
Lastpage :
157
Abstract :
Cardiovascular diseases remain the biggest cause of death worldwide. Early detection is the most important step to solve this problem. Cardiac Magnetic Resonance Imaging (CMR) has shown its capability of imaging the heart and evaluation of cardiac function without exposure to ionizing radiation. In this paper, we aim to perform automatic heart localization in MRI short axis view using a simple and effective way. The proposed algorithm can be described through the following two steps: (a) preprocessing step to denoise the images using Gaussian filter, and (b) localization step based on shape recognition technique. The algorithm, implemented using MATLAB, was developed and tested using two datasets. First one consists of 33 subjects normal and abnormal for a total of 7980 2D images and the second one consists of 50 2D images related to normal subject. The results here are evaluated through the classification into three types: totally localized case (complete heart falls inside the selected ROI window), partially localized case (small part, less than 10%, of LV or RV falls outside the selected ROI window), and not localized case (more than 10% of the hearts falls outside the selected ROI window). It gives result with 91.4% accuracy for totally localized case, 8.1% for partially localized case, and 0.5% for not localized case.
Keywords :
biomedical MRI; cardiovascular system; diseases; image classification; image denoising; medical image processing; object detection; 2D images; CMR; Gaussian filter; MATLAB; MRI short axis view; automatic cardiac MRI localization method; automatic heart localization; cardiac Magnetic Resonance Imaging; cardiac function; cardiovascular diseases; classification; datasets; early detection; image denoising; localization step; not localized case; partially localized case; shape recognition technique; totally localized case; Educational institutions; Filtration; Heart; Image segmentation; Magnetic resonance imaging; Noise; Shape; Cardiac Magnetic Resonance Imaging (CMR); Cardiovascular diseases (CVDs); Hough transform; heart localization; region of interest (ROI);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Engineering Conference (CIBEC), 2014 Cairo International
Conference_Location :
Giza
ISSN :
2156-6097
Print_ISBN :
978-1-4799-4413-2
Type :
conf
DOI :
10.1109/CIBEC.2014.7020942
Filename :
7020942
Link To Document :
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