A comparative approach of four different image registration techniques for quantitative assessment of coronary artery calcium lesions using intravascular ultrasound. Issue 2 (February 2015) - Araki, Tadashi; Ikeda, Nobutaka; Dey, Nilanjan; Chakraborty, Sayan; Saba, Luca; Kumar, Dinesh; Godia, Elisa Cuadrado; Jiang, Xiaoyi; Gupta, Ajay; Radeva, Petia; Laird, John R.; Nicolaides, Andrew; et al.
Abstract In IVUS imaging, constant linear velocity and a constant angular velocity of 1800 rev/min causes displacement of the calcium in subsequent image frames. To overcome this error in intravascular ultrasound video, IVUS image frames must be registered prior to the lesion quantification. This paper presents a comprehensive comparison of four registration methods, namely: Rigid, Affine, B-Splines and Demons on five set of calcium lesion quantification parameters namely: (i) the mean lesion area, (ii) mean lesion arc, (iii) mean lesion span, (iv) mean lesion length, and (v) mean lesion distance from catheter. Using our IRB approved data of 100 patient volumes, our results shows that all four registrations showed a decrease in five calcium lesion parameters as follows: for Rigid registration, the values were: 4.92%, 5.84%, 5.89%, 5.27%, and 4.57%, respectively, for Affine registration the values were: 6.06%, 6.51%, 7.28%, 6.50%, and 5.94%, respectively, for B-Splines registration the values were: 7.35%, 8.03%, 9.54%, 8.18%, and 7.62%, respectively, and for Demons registration the five parameters were 7.32%, 8.02%, 10.11%, 7.94%, and 8.92% respectively. The relative overlap of identified lesions decreased by 5.91% in case of Rigid registration, 6.23% in case of Affine registration, 4.48% for Demons registration, whereas it increased by 3.05% in case of B-Splines registration. Rigid and Affine transformation-based registration took only 0.1936 and 0.2893 s per frame, respectively. Demons and B-Splines framework took only 0.5705 and 0.9405 s per frame, respectively, which were significantly slower than Rigid and Affine transformation based image registration.