Title :
A Multi-Atlas-Based Segmentation Framework for Prostate Brachytherapy
Author :
Nouranian, Saman ; Mahdavi, S. Sara ; Spadinger, Ingrid ; Morris, William J. ; Salcudean, Septimu E. ; Abolmaesumi, Purang
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of British Columbia, Vancouver, BC, Canada
Abstract :
Low-dose-rate brachytherapy is a radiation treatment method for localized prostate cancer. The standard of care for this treatment procedure is to acquire transrectal ultrasound images of the prostate in order to devise a plan to deliver sufficient radiation dose to the cancerous tissue. Brachytherapy planning involves delineation of contours in these images, which closely follow the prostate boundary, i.e., clinical target volume. This process is currently performed either manually or semi-automatically, which requires user interaction for landmark initialization. In this paper, we propose a multi-atlas fusion framework to automatically delineate the clinical target volume in ultrasound images. A dataset of a priori segmented ultrasound images, i.e., atlases, is registered to a target image. We introduce a pairwise atlas agreement factor that combines an image-similarity metric and similarity between a priori segmented contours. This factor is used in an atlas selection algorithm to prune the dataset before combining the atlas contours to produce a consensus segmentation. We evaluate the proposed segmentation approach on a set of 280 transrectal prostate volume studies. The proposed method produces segmentation results that are within the range of observer variability when compared to a semi-automatic segmentation technique that is routinely used in our cancer clinic.
Keywords :
biomedical ultrasonics; brachytherapy; cancer; dosimetry; image segmentation; medical image processing; tumours; a priori segmented contours; a priori segmented ultrasound images; atlas selection algorithm; brachytherapy planning; cancer clinic; cancerous tissue; clinical target volume; consensus segmentation; contour delineation; dataset; image-similarity metric; landmark initialization; localized prostate cancer; low-dose-rate brachytherapy; multi-atlas fusion framework; multiatlas-based segmentation framework; observer variability; pairwise atlas agreement factor; prostate boundary; prostate brachytherapy; radiation dose; radiation treatment method; semiautomatic segmentation technique; target image registration; transrectal prostate volume studies; transrectal ultrasound images; treatment procedure; Brachytherapy; Cancer; Image segmentation; Measurement; Protocols; Shape; Ultrasonic imaging; Brachytherapy; clinical target volume; multi-atlas-based segmentation; pairwise atlas agreement factor; prostate segmentation; transrectal ultrasound;
Journal_Title :
Medical Imaging, IEEE Transactions on
DOI :
10.1109/TMI.2014.2371823