An image-based comprehensive approach for automatic segmentation of left ventricle from cardiac short axis cine MR images.

Journal of Digital Imaging
Su HuangWieslaw L Nowinski

Abstract

Segmentation of the left ventricle is important in the assessment of cardiac functional parameters. Manual segmentation of cardiac cine MR images for acquiring these parameters is time-consuming. Accuracy and automation are the two important criteria in improving cardiac image segmentation methods. In this paper, we present a comprehensive approach to segment the left ventricle from short axis cine cardiac MR images automatically. Our method incorporates a number of image processing and analysis techniques including thresholding, edge detection, mathematical morphology, and image filtering to build an efficient process flow. This process flow makes use of various features in cardiac MR images to achieve high accurate segmentation results. Our method was tested on 45 clinical short axis cine cardiac images and the results are compared with manual delineated ground truth (average perpendicular distance of contours near 2 mm and mean myocardium mass overlapping over 90%). This approach provides cardiac radiologists a practical method for an accurate segmentation of the left ventricle.

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Citations

Jan 16, 2014·Journal of Cardiovascular Magnetic Resonance : Official Journal of the Society for Cardiovascular Magnetic Resonance·Daniel A AugerBruce S Spottiswoode
Jul 23, 2015·Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society·Bing WangLixu Gu
Jul 22, 2014·Medical Image Analysis·Sandro QueirósJan D'hooge
Jun 14, 2016·International Journal of Computer Assisted Radiology and Surgery·Yurun MaXiaoguang Sun
Jul 2, 2014·Medical Image Analysis·Marco PereañezAlejandro F Frangi
Nov 27, 2020·RöFo : Fortschritte auf dem Gebiete der Röntgenstrahlen und der Nuklearmedizin·Daniel OverhoffUNKNOWN Präsidium der Österreichischen Röntgengesellschaft:
Jan 24, 2021·Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society·Abderazzak AmmarMohamed Youssfi

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