Multiple 2D video/3D medical image registration algorithm

Matthew J. Clarkson; Daniel Rueckert; Derek L.G. Hill; David John Hawkes

doi:10.1117/12.387696

6 June 2000 Multiple 2D video/3D medical image registration algorithm

Matthew J. Clarkson, Daniel Rueckert, Derek L.G. Hill, David John Hawkes

Author Affiliations +

Proceedings Volume 3979, Medical Imaging 2000: Image Processing; (2000) https://doi.org/10.1117/12.387696
Event: Medical Imaging 2000, 2000, San Diego, CA, United States

Abstract

In this paper we propose a novel method to register at least two vide images to a 3D surface model. The potential applications of such a registration method could be in image guided surgery, high precision radiotherapy, robotics or computer vision. Registration is performed by optimizing a similarity measure with respect to the pose parameters. The similarity measure is based on 'photo-consistency' and computes for each surface point, how consistent the corresponding video image information in each view is with a lighting model. We took four video views of a volunteer's face, and used an independent method to reconstruct a surface that was intrinsically registered to the four views. In addition, we extracted a skin surface from the volunteer's MR scan. The surfaces were misregistered from a gold standard pose and our algorithm was used to register both types of surfaces to the video images. For the reconstructed surface, the mean 3D error was 1.53 mm. For the MR surface, the standard deviation of the pose parameters after registration ranged from 0.12 to 0.70 mm and degrees. The performance of the algorithm is accurate, precise and robust.

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Matthew J. Clarkson, Daniel Rueckert, Derek L.G. Hill, and David John Hawkes "Multiple 2D video/3D medical image registration algorithm", Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); https://doi.org/10.1117/12.387696

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