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Surgical navigation systems enable surgeons to carry out surgical interventions more accurately and less invasively, by tracking
the surgical instruments inside human body with respect to the target anatomy. In order to get the real-time position and
orientation measurements of surgical instruments in the surgical field, we developed a new miniature tracking device, which
is aiming to overcome the constraints of line-of-sight and interference in surgical environment. Currently, optical tracking
(OPT) is the gold standard in surgical navigation systems because of its accuracy but is constrained by direct line of sight (LOS)
between camera sensors and markers. Electromagnetic tracking (EMT) technology is an alternative without the requirement
of LOS, whereas EMT is prone to measurement errors caused by environmental ferromagnetic distortion. An idea for solving
these dilemmas is to integrate respective strengths to overcome the corresponding weaknesses. Instead of conventional postacquisition
loosely coupled fusion of sensor measurements, we built a real-time hybrid tracking system as illustrated in the below
figure and developed a ?pre-data fusion? method, which emphasizes the interactive and tightly coupled fusion of EMT and OPT
sensor data for pose estimation. The primary contribution of this study is that LOS problem and point correspondence problem
can be mitigated using the initial measurements of EMT, and in turn the OPT result can be the initial value for non-linear iterative
solver of EMT sensing module, in order to increase the tracking accuracy of EMT. The experiments show that the mean position
estimation error is 0.87 mm.
Hongliang Ren is currently an assistant professor and a PI of medical mechatronics in National University of Singapore (NUS). He received his
Ph.D. in Electronic Engineering from The Chinese University of Hong Kong (CUHK), and conducted postdoctoral research in the Johns Hopkins
University, Surgical Innovation Institute of Children's National Medical Center, and the Pediatric Cardiac Bioengineering Lab of Children's Hospital
Boston & Harvard Medical School. His research interests are in Computer-Integrated Surgical (CIS) systems, biomedical mechatronics, medical
robotics and sensing technologies.
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