Prostate cancer is one of the most frequent cancers among men. Abdominal ultrasound imaging is a very practical alternative to more precise but inconvenient transrectal ultrasound imaging for the diagnosis and treatment of prostate cancer. However, detection of the prostate region alone is very difficult for the abdominal ultrasound images. This paper presents a new prostate detection method that models the abdominal images as the classes of neighboring anatomical regions of the prostate. The proposed method has two levels: Pixel level detection assigns class scores to each pixel in the image. Model level detection uses these scores to determine the final positions of the anatomical regions in the image. The proposed approach is very effective for the specific problems of the abdominal ultrasound scans. Extensive experiments performed on real patient data with and without pathologies produce very promising results.