Goodyear, BradleyMitchell, RossDang, Mong2013-04-302013-06-102013-04-302013http://hdl.handle.net/11023/651In recent years, biomarker classification using medical imaging informatics has generated significant research interest. Imaging biomarkers may provide a non-invasive method to assess important genetic characteristics of lesions and the impact of treatment. However, assessment of new imaging biomarkers in terms of measurement time, precision and accuracy, is critical for clinical acceptance. This research characterized two new imaging biomarkers in head and neck cancers: a rapid, parallel level-set for volume measurement of meningioma brain tumors; and, an image texture biomarker of an important gene in squamous cell carcinoma (SCC). Results suggest that the new volume measurement tool possesses better measurement time, precision and accuracy than an algorithm in current widespread clinical use. The image texture biomarker achieved good accuracy in predicting genetic status in SCC. These findings demonstrate the potential clinical utility of these new imaging biomarkers.engUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.OncologyRadiologyComputer ScienceImagingBiomarkerhead and necktexturevolumemaster thesis10.11575/PRISM/26448