The optical ow enables the accurate estimation of cardiac motion. In this research, a sparse based algorithm is used to estimate the optical ow in cardiac magnetic resonance images. The dense optical ow eld is represented using a discrete cosine basis dictionary aiming at a sparse representation. The optical ow is estimated in this transformed space by solving a L1 problem inspired on compressive sensing techniques. The algorithm is validated using four synthetic image sequences whose velocity eld is known. A comparison is performed with respect to the Horn and Schunck and the Lucas and Kanade algorithm. Then, the technique is applied to a magnetic resonance image sequence. The results show average magnitude errors as low as 0.35 % for the synthetic sequences, however results on real data are not consistent with respect to the obtained by other algorithms suggesting the need for additional constrains for coping with the dense noise.

Date Published: 19 November 2013
PDF: 9 pages
Proc. SPIE 8922, IX International Seminar on Medical Information Processing and Analysis, 892202 (19 November 2013); doi: 10.1117/12.2035466

Published in SPIE Proceedings Vol. 8922:
IX International Seminar on Medical Information Processing and Analysis
Jorge Brieva; Boris Escalante-Ramírez, Editor(s)