Background: Organ-mounted robots adhere to the surface of a mobile organ as a platform for minimally invasive interventions, providing passive compensation of physiological motion. This approach is beneficial during surgery on the beating heart. Accurate localization in such applications requires accounting for the heartbeat and respiratory motion. Previous work has described methods for modeling quasi-periodic motion of a point and registering to a static preoperative map. The existing techniques, while accurate, require several respiratory cycles to converge. Methods: This paper presents a general localization technique for this application, involving function approximation using radial basis function (RBF) interpolation. Results: In an experiment in the porcine model in vivo, the technique yields mean localization accuracy of 1.25 mm with a 95% confidence interval of 0.22 mm. Conclusions: The RBF approximation provides accurate estimates of robot location instantaneously.

Organ-mounted robot localization via function approximation / Wood, N.A., Schwartzman, D., Passineau, M.J., Halbreiner, M.S., Moraca, R.J., Zenati, M.A., Riviere, C.N.. - In: THE INTERNATIONAL JOURNAL OF MEDICAL ROBOTICS AND COMPUTER ASSISTED SURGERY. - ISSN 1478-5951. - 15:2(2019). [10.1002/rcs.1971]

Organ-mounted robot localization via function approximation

Zenati M. A.;
2019-01-01

Abstract

Background: Organ-mounted robots adhere to the surface of a mobile organ as a platform for minimally invasive interventions, providing passive compensation of physiological motion. This approach is beneficial during surgery on the beating heart. Accurate localization in such applications requires accounting for the heartbeat and respiratory motion. Previous work has described methods for modeling quasi-periodic motion of a point and registering to a static preoperative map. The existing techniques, while accurate, require several respiratory cycles to converge. Methods: This paper presents a general localization technique for this application, involving function approximation using radial basis function (RBF) interpolation. Results: In an experiment in the porcine model in vivo, the technique yields mean localization accuracy of 1.25 mm with a 95% confidence interval of 0.22 mm. Conclusions: The RBF approximation provides accurate estimates of robot location instantaneously.
2019
2
Settore MEDS-13/C - Chirurgia cardiaca
Settore INFO-01/A - Informatica
Wood, N. A.; Schwartzman, D.; Passineau, M. J.; Halbreiner, M. S.; Moraca, R. J.; Zenati, M. A.; Riviere, C. N.
Organ-mounted robot localization via function approximation / Wood, N.A., Schwartzman, D., Passineau, M.J., Halbreiner, M.S., Moraca, R.J., Zenati, M.A., Riviere, C.N.. - In: THE INTERNATIONAL JOURNAL OF MEDICAL ROBOTICS AND COMPUTER ASSISTED SURGERY. - ISSN 1478-5951. - 15:2(2019). [10.1002/rcs.1971]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/474790
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