Performing patient alignment utilizing point-cloud surface registration techniques in HoloNav

Bachelor thesis (2022)

Authors

Maarten Weyns Electrical Engineering, Mathematics and Computer Science

Contributors

Abdullah Thabit (supervisor 1)
Ricardo Marroquim Computer Graphics and Visualisation - EEMCS (supervisor 1)
A. Hanjalic Intelligent Systems (supervisor 2)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2022 Maarten Weyns
Point Cloud Registration Patient Alignment Surgical Navigation
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Published Date

22-06-2022

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

In order to be able to use the Microsoft HoloLens for surgical navigation purposes, performing good patient alignment is of utmost importance. This paper will discuss how this patient alignment can be done using different point cloud registration algorithms.
A lot of research is being conducted on point cloud registration algorithms. However, most research assumes that the point clouds to be aligned are almost identical, while patient alignment aims at aligning a very detailed pre-operative scan with a very sparse point cloud obtained by the surgeon using an optical marker.
In order to get around this problem, the HoloLens' depth camera is used to obtain a detailed point cloud so that registration algorithms can be used. Then the performance of different point cloud registration algorithms is tested on this depth sensor data to see whether using the HoloLens' depth sensor is a viable option for patient alignment.
From the results, it appears that algorithmic approaches for performing patient alignment are feasible, but the performance of these algorithms is very dependent on the quality of the input data.