title: Prostate segmentation algorithm using dyadic wavelet transform and discrete dynamic contour.
abstract: Knowing the location and the volume of the prostate is important for ultrasound-guided prostate brachytherapy, a commonly used prostate cancer treatment method. The prostate boundary must be segmented before a dose plan can be obtained. However, manual segmentation is arduous and time consuming. This paper introduces a semi-automatic segmentation algorithm based on the dyadic wavelet transform (DWT) and the discrete dynamic contour (DDC). A spline interpolation method is used to determine the initial contour based on four user-defined initial points. The DDC model then refines the initial contour based on the approximate coefficients and the wavelet coefficients generated using the DWT. The DDC model is executed under two settings. The coefficients used in these two settings are derived using smoothing functions with different sizes. A selection rule is used to choose the best contour based on the contours produced in these two settings. The accuracy of the final contour produced by the proposed algorithm is evaluated by comparing it with the manual contour outlined by an expert observer. A total of 114 2D TRUS images taken for six different patients scheduled for brachytherapy were segmented using the proposed algorithm. The average difference between the contour segmented using the proposed algorithm and the manually outlined contour is less than 3 pixels.
authors.affiliation: Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada. bchiu@imaging.robarts.ca
authors.forename: Bernard
authors.initials: B
authors.lastname: Chiu
authors.forename: George H
authors.initials: GH
authors.lastname: Freeman
authors.forename: M M A
authors.initials: MM
authors.lastname: Salama
authors.forename: Aaron
authors.initials: A
authors.lastname: Fenster
mesh_terms: D000465:Algorithms; D001918:Brachytherapy / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy*; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods; D011881:Radiotherapy, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014463:Ultrasonography