CAMP - RT: A Patient Similarity-Based Method for Predicting Radiation Dosage in Head and Neck Radiation Oncology
Main View of Application - photo courtesy - Peter Hanula
Authors: P. Hanula
Publication: Submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science, Graduate College of the University of Illinois at Chicago
I present an automated method for computing the spatial similarity of tumor location with respect to organs at risk between multiple head and neck cancer patients and ranking the patients accordingly. I use this method and resulting metric to predict, for each patient, a radiation dose distribution across organs in the head and neck. Furthermore, I go over the design and implementation of a visual analysis tool used to help validate the method.
The resulting method and interface, CAMP-RT (Correlations Across Multiple Patients in Radiation Therapy) is continuously being evaluated by domain experts from the MD Anderson Cancer Center. I report their qualitative feedback regarding the method and interface. I further evaluate quantitatively the results of the prediction using a dataset of 101 head-and-neck cancer patients. The results indicate the method has good predictive capabilities.
Date: December 31, 2018
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