Master of Engineering Science
Radical prostatectomy surgery (RP) is the gold standard for treatment of localized prostate cancer (PCa). Recently, emergence of minimally invasive techniques such as Laparoscopic Radical Prostatectomy (LRP) and Robot-Assisted Laparoscopic Radical Prostatectomy (RARP) has improved the outcomes for prostatectomy. However, it remains difficult for surgeons to make informed decisions regarding resection margins and nerve sparing since the location of the tumour within the organ is not usually visible in a laparoscopic view. While MRI enables visualization of the salient structures and cancer foci, its efficacy in LRP is reduced unless it is fused into a stereoscopic view such that homologous structures overlap. Registration of the MRI image and peri-operative ultrasound image either via visual manual alignment or using a fully automated registration can potentially be exploited to bring the pre-operative information into alignment with the patient coordinate system at the beginning of the procedure. While doing so, prostate motion needs to be compensated in real-time to synchronize the stereoscopic view with the pre-operative MRI during the prostatectomy procedure. In this thesis, two tracking methods are proposed to assess prostate rigid rotation and translation for the prostatectomy. The first method presents a 2D-to-3D point-to-line registration algorithm to measure prostate motion and translation with respect to an initial 3D TRUS image. The second method investigates a point-based stereoscopic tracking technique to compensate for rigid prostate motion so that the same motion can be applied to the pre-operative images.
Esteghamatian, Mehdi, "Real-time Prostate Motion Tracking For Robot-assisted Laparoscopic Radical Prostatectomy" (2012). University of Western Ontario - Electronic Thesis and Dissertation Repository. Paper 549.