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ORIGINAL ARTICLE
Year : 2012  |  Volume : 2  |  Issue : 3  |  Page : 121-127

Modified optical flow technique for cardiac motions analysis in echocardiography images


1 Department of Biomedical Engineering, Iran University of Science and Technology, School of Electrical Engineering, Tehran, Iran
2 Department of Cardiovascular Medicine, Rajaei Cardiovascular Medical and Research Center, Tehran, Iran

Correspondence Address:
Paria Torkashvand
Department of Biomedical Engineering, Iran University of Science and Technology, School of Electrical Engineering, Tehran
Iran
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2228-7477.111975

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The quantitative analysis of cardiac motions in echocardiography images is a noteworthy issue in processing of these images. Cardiac motions can be estimated by optical flow (OF) computation in different regions of image which is based on the assumption that the intensity of a moving pattern remains constant in consecutive frames. However, in echocardiographic sequences, this assumption may be violated because of unique specifications of ultrasound. There are some methodsapplying the brightness variation effect in OF. Almost all of them have presented a mathematical brightness variation model globally in the images. Nevertheless, there is not a brightness variation model for echocardiographic images in these methods. Therefore, we are looking for a method to apply brightness variations locally in different regions of the image. In this study, we proposed a method to modify ausual OF technique by considering intensity variation. To evaluate this method, we implement two other OF-based methods, one usual OF method and a modified OF method applying brightness variation as a multiplier and an offset (generalized dynamic imaging model [GDIM]) and compare them with ours. These algorithms and ours were implemented on real 2D echocardiograms. Our method resulted in more accurate estimations than two others. At last, we compared our method with expert'spoint of view and observed that three distance metrics between them was appropriately smaller than other methods. The Haussdorff distance between the estimated curve defined by the proposed method and the expert defined curve is 4.81 pixels less than this distance for Lucas-Kanade and 2.28 pixels less than GDIM.


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