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Deformable Registration using Navigator Channels and a Population Motion Model

Radiotherapy is a potential curative option for liver cancer; however, respiratory motion creates uncertainty in treatment delivery. Advances in imaging and registration techniques can provide information regarding changes in respiratory motion. Currently image registration is challenged by computation and manual intervention. A Navigator Channel (NC) technique was developed to overcome these limitations. A population motion model was generated to predict patient-specific motion, while a point motion detection technique was developed to calculate the patient-specific liver edge motion from images. An adaptation technique uses the relative difference between the population and patient calculated liver edge motion to determine the patient's liver volume motion. The NC technique was tested on patient 4D-CT images for initial validation to determine the accuracy. Accuracy was less than 0.10 mm in liver edge detection and approximately 0.25 cm in predicting patient-specific motion. This technique can be used to ensure accurate treatment delivery for liver radiotherapy.

Identiferoai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/18936
Date15 February 2010
CreatorsNguyen, Thao-Nguyen
ContributorsBrock, Kristy K.
Source SetsUniversity of Toronto
Languageen_ca
Detected LanguageEnglish
TypeThesis

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