Prostate boundary detection and volume estimation using TRUS images for brachytherapy applications

Objective: Authors propose a semi-automatic segmentation algorithm for three-dimensional prostate boundary detection from trans-rectal ultrasound images. As a part of brachytherapy treatment with seeds for early stage prostate cancer, a patient’s prostate is scanned using a trans-rectal ultrasound probe, its boundary is manually outlined, and its volume is estimated for dosimetry purposes. Proposed algorithm requires a reduced amount of radiologist’s input, and thus speeds up the surgical procedure. Methods: The proposed segmentation algorithm utilizes texture differences between ultrasound images of the prostate and the surrounding tissues. It is carried out in the polar coordinate system and uses three-dimensional data correlation to improve the smoothness and reliability of the segmentation. The algorithm is applied to axial trans-rectal ultrasound images and the results are compared to the “ground truth” set by manual prostate boundary outlining (by experienced radiologist). Method is validated on six patients. Results: In our tests, the proposed algorithm estimated prostate volume within 95% of the original radiologist’s estimate. Conclusions: The boundary segmentation obtained from the algorithm can reduce manual input by a factor of 3, without significantly affecting the accuracy of the segmentation. The reduction in the manual input reduces the overall brachytherapy procedure time.