Abstract
The objective of this paper is to generate a unique and robust correspondence between two sets of points, one from the image frame of reference and the other from a set of points in the surgical tool frame of reference; irrespective of the alterations in the number of points or in the sequence of measurement of the points in the image or the tool frame. The radio-opaque markers (affixed to the scalp of the patient before MRI/CT Scan) serve as a reference in neuro-images. The coordinates of the markers on the patient’s scalp with respect to the robot (surgical tool) frame are measured during neurosurgery. From the data, the relationship between the anatomical frame and the tool frame is established. Distance and uniqueness criteria between the markers are used to determine the correspondence. Validation is obtained by conducting correspondence on the phantoms with various configurations of marker points.
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Dwarakanath, S., Bhutani, G., Venkata, P.P.K., Kaushik, A. (2019). Generalized Point Correspondence Algorithm for Neuro-Registration. In: Badodkar, D., Dwarakanath, T. (eds) Machines, Mechanism and Robotics. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-10-8597-0_5
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DOI: https://doi.org/10.1007/978-981-10-8597-0_5
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