Mobile Cloud Computing Based Non Rigid Registration for Image Guided Surgery

Date of Award

Summer 8-2015

Document Type


Degree Name

Master of Science (MS)


Computer Science

Committee Director

Nikos Chrisochoides

Committee Member

Michel Audette

Committee Member

Tamer Nadeem

Call Number for Print

Special Collections LD4331.C65 B735 2015


In this thesis we present the design and implementation of a Mobile Cloud computing platform for non-rigid registration required in Image Guided Surgery (MCIGS). MCIGS contributes in flexible, portable and accurate alignment of pre-operative brain data with intra-operative MRI, for image guided diagnosis and therapy and endoscopic skull base surgery. Improved precision of image guided therapy and specifically neurosurgery procedures is known to result in the improved prognosis for brain tumor patients. MCI GS system is tested with Physics Based Non-Rigid Registration method form ITK. Our preliminary results for brain images indicate that the proposed system over Wi-Fi can be used to perform non-rigid registration over the cloud in less than a minute (about 53 seconds), i.e., within the time constraints imposed by brain surgeries. In addition, it can be used to leverage cloud computing resources to improve the accuracy of registration by 21 % over the traditional way of utilizing a single high-end workstation within or next to Operating Rooms. MCIGS is not limited to the specific Non-Rigid Registration we use to demonstrate its impact. In this thesis we also discuss a step towards topologically flexible registration of sulci extracted from the brain MR images using embedded maps based registration which can be used to build a healthy brain template.


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