초음파 전립선 영상에서 전립선 경계 분할을 위한 평균 형상 모델
An Average Shape Model for Segmenting Prostate Boundary of TRUS Prostate Image
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초록
전립선암은 전립선에 나타나는 악성 종양이다. 현재 그 발병률이 높아지고 있다. 전립선암의 구조를 가장 정확하게 확인할 수 있는 검사방법은 MRI를 이용하는 것이나, 그 비용 때문에 모든 환자에게 적용하기는 어려운 실정이다. 그래서 많은 환자들은 가격이 저렴한 초음파검사를 이용하여 전립선암을 진단하고 있다. 전통적으로 의사들은 영상을 눈으로 확인하여 전립선의 경계를 수동으로 분할하였다. 그러나수동으로 분할하는 과정은 시간이 많이 소요되며, 의사에 따라서 그 경계가 일정하지 않게 얻어진다. 이 문제를 해결하기 위하여 전립선의자동 분할에 관한 연구가 되었고, 환자들에게 신뢰를 줄 수 있었다. 본 연구는 초음파 전립선 영상에서 전립선의 경계를 분할하는데 평균형상 모델을 적용하는 것이다. 먼저, 에지 분포를 이용하여 프로브를 찾고, 프로브와 연결된 두 직선을 찾는다. 이 후에 이 정보를 이용하여전립선 영상 위에 평균 형상을 위치시킨다.
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.
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