Joint registration of location and orientation of intravascular ultrasound pullbacks using a 3D graph based method

Ling Zhang; Andreas Wahle; Zhi Chen; Li Zhang; Richard Downe; Tomas Kovarnik M.D.; Milan Sonka

doi:10.1117/12.2081475

20 March 2015 Joint registration of location and orientation of intravascular ultrasound pullbacks using a 3D graph based method

Ling Zhang, Andreas Wahle, Zhi Chen, Li Zhang, Richard Downe, Tomas Kovarnik M.D., Milan Sonka

Author Affiliations +

Proceedings Volume 9413, Medical Imaging 2015: Image Processing; 94131I (2015) https://doi.org/10.1117/12.2081475
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

Abstract

A novel method for simultaneous registration of location and orientation of baseline and follow-up intravascular ultrasound (IVUS) pullbacks is reported. The main idea is to represent the registration problem as a 3D graph optimization problem (finding a minimum-cost path) solvable by dynamic programming. Thus, global optimality of the resulting location and orientation registration is guaranteed according to the employed cost function and node connections. The cost function integrates information related to vessel/plaque morphology, plaque shape and plaque/perivascular image data. The node connections incorporate the prior information about angular twisting between consecutively co-registered IVUS image pairs. Pilot validation of our method is currently available for four pairs of IVUS pullback sequences consisting of 323 IVUS image frames from four patients. Results showed the average location and orientation registration errors were 0.26 mm and 5.2°, respectively. Compared with our previous results, the new method offers significant alignment improvement (p < 0.001).

Citation Download Citation

Ling Zhang, Andreas Wahle, Zhi Chen, Li Zhang, Richard Downe, Tomas Kovarnik M.D., and Milan Sonka "Joint registration of location and orientation of intravascular ultrasound pullbacks using a 3D graph based method", Proc. SPIE 9413, Medical Imaging 2015: Image Processing, 94131I (20 March 2015); https://doi.org/10.1117/12.2081475

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