Regional heart motion abnormality detection: An information theoretic approach

• Published in: Medical image analysis Vol. 17; no. 3; pp. 311 - 324
• Main Authors: Punithakumar, Kumaradevan, Ben Ayed, Ismail, Islam, Ali, Goela, Aashish, Ross, Ian G., Chong, Jaron, Li, Shuo
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.04.2013
• Subjects: Algorithms; Cardiac motion estimation; Female; Humans; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Information Storage and Retrieval - methods; Information theoretic measures; Magnetic resonance imaging; Magnetic Resonance Imaging, Cine - methods; Male; Middle Aged; Movement; Myocardial Contraction; Nonlinear state estimation; Pattern Recognition, Automated - methods; Regional wall motion abnormality detection; Reproducibility of Results; Sensitivity and Specificity; Ventricular Dysfunction, Left - diagnosis; Ventricular Dysfunction, Left - physiopathology; Information theoretic measures; Regional wall motion abnormality detection; Cardiac motion estimation; Nonlinear state estimation; Magnetic resonance imaging
• ISSN: 1361-8415; 1361-8423; 1361-8423
• DOI: 10.1016/j.media.2012.11.007

[Display omitted] ► Coronary heart disease can be detected by measuring left ventricular motion. ► Clinically, the wall regional motion is scored following the standard by the AHA. ► Given noisy data and model, an unscented Kalman smoother estimates myocardial points. ► The Shannon’s differential en...