DocumentCode
1845448
Title
Automatic Detection of End Systole within a Sequence of Left Ventricular Echocardiographic Images using Autocorrelation and Mitral Valve Motion Detection
Author
Kachenoura, N. ; Delouche, A. ; Herment, A. ; Frouin, F. ; Diebold, B.
Author_Institution
INSERM, Paris
fYear
2007
fDate
22-26 Aug. 2007
Firstpage
4504
Lastpage
4507
Abstract
The automatic detection of end diastole and end systole is the first step of any software developed for a fully automatic calculation of the ejection fraction. In this study, methods of image processing were applied to black and white echocardiographic image sequences corresponding to a cardiac cycle and the end systolic image number was automatically estimated. The first method took the advantage of the rapid mitral valve motion to estimate the end systole from the time signal intensity variation in a cavity region defined thanks to three landmarks usually used for the standard left ventricular segmentation. The second method was fully automatic; it was based on the left ventricular deformation during the cardiac cycle. The deformation curve was estimated using correlation and its minimal value was used to detect end systole. Method 3 was a combination of the two previous methods to overcome their limitations. The three methods were tested on a group of 37 patients (four chambers and two chambers apical views). The first image exhibiting the beginning of the mitral opening was considered as the end systolic on the visual readings. Compared with this visual reference reading, a linear regression led to a correlation coefficient r of 0.84 for the first method. This coefficient was improved to 0.87 for the second method and increased significantly to r= 0.93 for the third method.
Keywords
biomechanics; correlation methods; echocardiography; image motion analysis; image sequences; medical image processing; regression analysis; autocorrelation; automatic end systole detection; cardiac cycle; diastole; ejection fraction; image processing; image sequence; left ventricular deformation; left ventricular echocardiographic image; linear regression; mitral valve motion detection; signal intensity variation; Autocorrelation; DICOM; Electrocardiography; Image processing; Image segmentation; Image sequences; Motion detection; Motion estimation; Testing; Valves; Echocardiography; Female; Heart Ventricles; Humans; Image Processing, Computer-Assisted; Male; Mitral Valve; Systole;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
Conference_Location
Lyon
ISSN
1557-170X
Print_ISBN
978-1-4244-0787-3
Type
conf
DOI
10.1109/IEMBS.2007.4353340
Filename
4353340
Link To Document