Assessment of local and global cardiac function based on AHA standardization

A special report from the American Heart Association (AHA), American College of Cardiology, and Society of Nuclear Medicine defined standards for plane selection and displays orientation for serial myocardial slices generated by cardiac 2-dimensional (2D) or tomographic imaging witch aimed to give a standardized myocardial nomenclature for CT images. This standardization gives also an efficient evaluation of the cardiac function. In fact, cardiac function allows doctors to have an idea about the extent and the severity of cardiac anomalies, their scalability and the treatment efficiency. Estimation of myocardial function still up to now subjective and depends on doctors opinions. In this work, we propose a quantitative analysis of the myocardium function namely defining the thickness quantification of the myocardium in two specific states of the cardiac cycle (end systole and end diastole) based on the AHA standardization.

[1]  Jasjit S. Suri,et al.  Computer Vision, Pattern Recognition and Image Processing in Left Ventricle Segmentation: The Last 50 Years , 2000, Pattern Analysis & Applications.

[2]  Dana H. Ballard,et al.  Computer Vision , 1982 .

[3]  M. Cerqueira,et al.  Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. A statement for healthcare professionals from the Cardiac Imaging Committee of the Council on Clinical Cardiology of the American Heart Association. , 2002, Circulation.

[4]  Samuel S. Silva,et al.  Left Ventricle Segmentation from Heart MDCT , 2009, IbPRIA.

[5]  M. Oudkerk,et al.  Assessment of global left ventricular functional parameters: analysis of every second short-axis Magnetic Resonance Imaging slices is as accurate as analysis of consecutive slices , 2008, The International Journal of Cardiovascular Imaging.

[6]  M. Cerqueira,et al.  Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart: A statement for healthcare professionals from the Cardiac Imaging Committee of the Council on Clinical Cardiology of the American Heart Association , 2002, The international journal of cardiovascular imaging.

[7]  Yo-Sung Ho,et al.  Automatic liver segmentation for volume measurement in CT Images , 2006, J. Vis. Commun. Image Represent..

[8]  Chunming Li,et al.  Level set evolution without re-initialization: a new variational formulation , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).