Abstract
Current Minimally Invasive Surgery (MIS) technology, although advantageous compared to open cavity surgery in many aspects, has limitations that prevents its use for general purpose surgery. This is due to reduced dexterity, cost, and required complex training of the currently practiced technology. The main challenges in reducing cost and amount of training is to have an accurate inner body navigation advisory system to help guide the surgeon to reach the surgery location. As a first step in making minimally invasive surgery affordable and more user friendly, quality images inside the patient as well as the surgical tool location should be provided automatically and accurately in real time in a common reference frame. The objective of this paper is to build a platform to accomplish this goal. It is shown that a set of three heterogeneous asynchronous sensors is a minimum requirement for navigation inside the human body. The sensors have different data rate, different reference frames, and independent time clocks. A prerequisite for successful information fusion is to represent all the sensors data in a common reference frame. The focus of this paper is on off-line calibration of the three sensors, i.e. before the surgical device is inserted in the human body. This is a pre-requisite for real time navigation inside the human body. The proposed off-line sensor registration technique was tested using experimental laboratory data. The result of calibration was promising with an average error of 0.1081 mm and 0.0872 mm along the x and y directions, respectively, in the 2D camera image.
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Bhattarai, U., Alouani, A.T. (2020). Hybrid Navigation Information System for Minimally Invasive Surgery: Offline Sensors Registration. In: Arai, K., Kapoor, S. (eds) Advances in Computer Vision. CVC 2019. Advances in Intelligent Systems and Computing, vol 944. Springer, Cham. https://doi.org/10.1007/978-3-030-17798-0_18
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