title: An automatic multi-atlas segmentation of the prostate in transrectal ultrasound images using pairwise atlas shape similarity.
abstract: Delineation of the prostate from transrectal ultrasound images is a necessary step in several computer-assisted clinical interventions, such as low dose rate brachytherapy. Current approaches to user segmentation require user intervention and therefore it is subject to user errors. It is desirable to have a fully automatic segmentation for improved segmentation consistency and speed. In this paper, we propose a multi-atlas fusion framework to automatically segment prostate transrectal ultrasound images. The framework initially registers a dataset of a priori segmented ultrasound images to a target image. Subsequently, it uses the pairwise similarity of registered prostate shapes, which is independent of the image-similarity metric optimized during the registration process, to prune the dataset prior to the fusion and consensus segmentation step. A leave-one-out cross-validation of the proposed framework on a dataset of 50 transrectal ultrasound volumes obtained from patients undergoing brachytherapy treatment shows that the proposed is clinically robust, accurate and reproducible.
authors.affiliation: Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada.
authors.forename: Saman
authors.initials: S
authors.lastname: Nouranian
authors.affiliation: Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada.
authors.forename: S Sara
authors.initials: SS
authors.lastname: Mahdavi
authors.affiliation: Vancouver Cancer Center, British Columbia Cancer Agency, Vancouver, Canada.
authors.forename: Ingrid
authors.initials: I
authors.lastname: Spadinger
authors.affiliation: Vancouver Cancer Center, British Columbia Cancer Agency, Vancouver, Canada.
authors.forename: William J
authors.initials: WJ
authors.lastname: Morris
authors.affiliation: Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada.
authors.forename: Septimiu E
authors.initials: SE
authors.lastname: Salcudean
authors.affiliation: Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada.
authors.forename: Purang
authors.initials: P
authors.lastname: Abolmaesumi
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008953:Models, Anatomic; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy*; D061089:Radiotherapy, Image-Guided / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014463:Ultrasonography / Q000379:methods*