Abstract: Segmenting the prostate boundary is essential in determining the dose plan needed for a successful bracytherapy procedure—an effective and commonly used treatment for prostate cancer. However, manual segmentation is time consuming and can introduce inter and intra-operator variability. This present invention describes an algorithm for segmenting the prostate from two dimensional ultrasound (2D US) images, which can be full-automatic, with some assumptions of image acquisition. Segmentation begins with the user assuming the center of the prostate to be at the center of the image for the fully-automatic version. The image is then filtered to identify prostate edge candidates. The next step removes most of the false edges and keeps as many true edges as possible. Then, domain knowledge is used to remove any prostate boundary candidates that are probably false edge pixels.

Abstract: Segmenting the prostate boundary is essential in determining the dose plan needed for a successful bracytherapy procedure—an effective and commonly used treatment for prostate cancer. However, manual segmentation is time consuming and can introduce inter and intra-operator variability. This present invention describes an algorithm for segmenting the prostate from two dimensional ultrasound (2D US) images, which can be full-automatic, with some assumptions of image acquisition. Segmentation begins with the user assuming the center of the prostate to be at the center of the image for the fully-automatic version. The image is then filtered to identify prostate edge candidates. The next step removes most of the false edges and keeps as many true edges as possible. Then, domain knowledge is used to remove any prostate boundary candidates that are probably false edge pixels.