Detection of Cardiac Quiescence from B-Mode Echocardiography using a Correlation-Based Frame-to-Frame Deviation Measure
Two novel methods for detecting cardiac quiescent phases from B-mode echocardiography using a correlation-based frame-to-frame deviation measure were developed. Accurate knowledge of cardiac quiescence is crucial to the performance of many imaging modalities, including computed tomography coronary angiography (CTCA). Methods: Synchronous electrocardiography (ECG) and echocardiography data were obtained from 10 healthy human subjects (4 male, 6 female, 23-45 years) and the interventricular septum (IVS) was observed using the apical four-chamber echocardiographic view. The velocity of the IVS was derived from active contour tracking and verified using tissue Doppler imaging echocardiography methods. In turn, the frame-to-frame deviation methods for identifying quiescence of the IVS were verified using active contour tracking. Results: The timing of the diastolic quiescent phase was found to exhibit both inter- and intra-subject variability, suggesting that the current method of CTCA gating based on the ECG is suboptimal and that gating based on signals derived from cardiac motion are likely more accurate in predicting quiescence for cardiac imaging. Conclusions: A robust and efficient method for identifying cardiac quiescent phases from B-mode echocardiographic data was developed and verified. Clinical Impact: The methods presented in this work will be used to develop new CTCA gating techniques and quantify the resulting potential improvement in CTCA image quality.
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Mr. Wick is currently pursuing a Ph.D. from the Georgia Institute of Technology. His current research is focused on digital signal processing of cardiac signals, with applications for motion analysis and tracking.
Dr. McClellan has been a Professor in the School of Electrical and Computer Engineering at Georgia Tech, where he presently holds the John and Marilu McCarty Chair. He is a co-author of the texts Number Theory in Digital Signal Processing, Computer Exercises for Signal Processing, DSP First: A Multimedia Approach, and Signal Processing First.
Mr. Ravichandran was a postdoctoral fellow in the Department of Radiology and Imaging Sciences at Emory University, Atlanta, from 2011 to 2012. His primary research interests are in the areas of development of signal and image processing algorithms, analysis of biomedical data and, architectural implementation of signal processing algorithms.
Dr. Tridandapani is a board-certified radiologist, and is a faculty member in the Department of Radiology and Imaging Sciences at Emory University and an Adjunct Professor in the School of Electrical and Computer Engineering at Georgia Institute of Technology. His research involves the development of novel gating strategies for optimizing cardiac computed tomography and tools to increase patient safety in medical imaging.
This article appeared in the 2013 issue of IEEE Journal of Translational Engineering in Health and Medicine.
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