The goal of this proposal is to improve the effectiveness of transrectal ultrasound (TRUS) in diagnosing and treating prostate diseases. Prostate boundaries in TRUS images provide the anatomical description needed for diagnosis, for treatment planning, and for follow-up. Our proposed research enables computer aided prostate delineation using """"""""just-enough interaction"""""""" with the expert. In phase I, we have embedded several segmentation algorithms within a software environment allowing interaction with the physicians. The variability in (semi-)automated prostate delineation compared to manual delineation was reduced by half. Also, the delineation time compared to manual outlining was reduced by a factor of 2. Based on the feedback from several companies and end-users, who have shown interest in our technology, we find that in the past year, emerging intraoperative clinical procedures and post-treatment monitoring techniques have necessitated further automation and generated the need for prostate specific multimodality image registration algorithms. In phase II, we aim to further reduce human interaction in prostate delineation without compromising on algorithm performance by developing and validating more advanced segmentation algorithms. We will automate post-implant monitoring by segmenting the prostate from post-implant TRUS images by developing advanced segmentation and registration algorithms. We will validate the algorithms on large clinical dataset.
Our technology is of great interest to vendors of prostate cancer treatment planning systems, be it in the area of prostate brachyltherapy or in prostate cryotherapy. The movement of radiation treatment planning systems to inter-operative settings make automated delineation technology even more valuable to these vendors. This technology is also of interest to manufacturers of ultrasound machines.
|Tutar, Ismail B; Gong, Lixin; Narayanan, Sreeram et al. (2008) Seed-based transrectal ultrasound-fluoroscopy registration method for intraoperative dosimetry analysis of prostate brachytherapy. Med Phys 35:840-8|
|Tutar, Ismail B; Pathak, Sayan D; Gong, Lixin et al. (2006) Semiautomatic 3-D prostate segmentation from TRUS images using spherical harmonics. IEEE Trans Med Imaging 25:1645-54|