Our results indicate that when implementing the process on a stationary acquisition dataset, the uncertainty improves at each stage while the uncertainty is reduced. When comparing stationary acquisition dataset to pullback dataset, the values were as follows: calcium: 3.8±1.09mm-1 in stationary and 3.9±1.2 mm-1 in a pullback; lipid: 11.025±0.417 mm-1 in stationary and 11.27±0.25 mm-1 in pullback; fibrous: 6.08±1.337 mm-1 in stationary and 5.58±2.0 mm-1. These results indicates that the process presented in this paper introduce minimal bias and only a small change in uncertainty when comparing a stationary and pullback dataset, thus paves the way to a highly accurate clinical plaque type discrimination, enabling automatic classification.
ACCESS THE FULL ARTICLE
Ronny Shalev, Madhusudhana Gargesha, David Prabhu, Kentaro Tanaka, Andrew M. Rollins, Marco Costa, Hiram G. Bezerra, Guy Lamouche, David L. Wilson, "Validation of parameter estimation methods for determining optical properties of atherosclerotic tissues in intravascular OCT," Proc. SPIE 9037, Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment, 90371D (11 March 2014);