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Beating‐heart registration for organ‐mounted robots
Author(s) -
Wood Nathan A.,
Schwartzman David,
Passineau Michael J.,
Moraca Robert J.,
Zenati Marco A.,
Riviere Cameron N.
Publication year - 2018
Publication title -
the international journal of medical robotics and computer assisted surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 53
eISSN - 1478-596X
pISSN - 1478-5951
DOI - 10.1002/rcs.1905
Subject(s) - heartbeat , image registration , computer science , metric (unit) , computer vision , artificial intelligence , robot , operations management , computer security , economics , image (mathematics)
Background Organ‐mounted robots address the problem of beating‐heart surgery by adhering to the heart, passively providing a platform that approaches zero relative motion. Because of the quasi‐periodic deformation of the heart due to heartbeat and respiration, registration must address not only spatial registration but also temporal registration. Methods Motion data were collected in the porcine model in vivo ( N = 6). Fourier series models of heart motion were developed. By comparing registrations generated using an iterative closest‐point approach at different phases of respiration, the phase corresponding to minimum registration distance is identified. Results The spatiotemporal registration technique presented here reduces registration error by an average of 4.2 mm over the 6 trials, in comparison with a more simplistic static registration that merely averages out the physiological motion. Conclusions An empirical metric for spatiotemporal registration of organ‐mounted robots is defined and demonstrated using data from animal models in vivo .