Sang Bog Kim , Joo Young Chung , Yeong Geon Seo

KIPS Transactions on Software and Data Engineering, Vol. 3, No. 5, pp. 187-194, May. 2014
10.3745/KTSDE.2014.3.5.187,   PDF Download:

Abstract

Prostate cancer is a malignant tumor occurring in the prostate. Recently, the repetition rate is increasing. Image inspection methodwhich we can check the prostate structure the most correctly is MRI(Magnetic Resonance Imaging), but it is hard to apply it to allthe patients because of the cost. So, they use mostly TRUS(Transrectal Ultrasound) images acquired from prostate ultrasoundinspection and which are cheap and easy to inspect the prostate in the process of treating and diagnosing the prostate cancer.Traditionally, in the hospital the doctors saw the TRUS images by their eyes and manually segmented the boundary between theprostate and nonprostate. But the manually segmenting process not only needed too much time but also had different boundariesaccording to the doctor. To cope the problems, some automatic segmentations of the prostate have been studied to generate theconstant segmentation results and get the belief from patients. In this study, we propose an average shape model to segment theprostate boundary in TRUS prostate image. The method has 3 steps. First, it finds the probe using edge distribution. Next, it findstwo straight lines connected with the probe. Finally it puts the shape model to the image using the position of the probe and straightlines.

Statistics
Cite this article