Feature Based Registration of Ultrasound and CT Data of a Scaphoid
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Authors
Koslowski, Brian
Date
2010-05-28T18:30:45Z
Type
thesis
Language
eng
Keyword
Feature-Based Registration , Ultrasound , CT , Scaphoid
Alternative Title
Abstract
Computer assisted surgery uses a collection of different techniques including but not limited to: CT-guided, fluoroscopy-guided, and ultrasound-guided imaging which allows medical staff to view bony anatomy of a patient in relation to surgical tools on a computer screen. By providing this visual data to surgeons less invasive surgeries can be performed on a patient's fractured scaphoid. The data required for a surgeon to perform a minimally invasive surgery while looking only at a computer screen, and not directly at a patient's anatomy, will be provided by CT and ultrasound data. We will discuss how ultrasound and CT data can be used together to allow a minimally invasive surgery of the scaphoid to be performed.
In this thesis we will explore two techniques of registering segmented ultrasound images to CT data; an Iterative Closest Point (ICP) approach, and an Unscented Kalman Filter-based Registration (UKF). We use two different ultrasound segmentation methods; a semi-automatic segmentation, and a Bayesian segmentation technique. The segmented ultrasound data is then registered to a CT volume. The success or failure of the
registrations is measured by the error calculated in mapping the corresponding land-
marks to one another and calculating the target registration error. The results show that the Unscented Kalman Filter-based registration using the Bayesian segmentation of ultrasound images has the least registration error, and has the most robustness to error in initial alignment of the two data sets.
Description
Thesis (Master, Computing) -- Queen's University, 2010-05-28 11:17:31.934
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