Ultrasound image segmentation is challenging due to speckles, depth-dependent signal attenuation, low signal-to- noise ratio, and direction-dependent edge contrast. In addition, transrectal ultrasound (TRUS) prostate images are often corrupted by acoustic shadowing caused by calcifications, bowel gas, protein deposit artifacts, etc., making segmentation difficult. In such cases, traditional edge detection algorithms without adequate preprocessing have limited success. The original sticks algorithm reduces speckles while enhancing contrast. It assumes that in a pixel neighborhood, reflectors of different orientations with respect to the incident ultrasound beam are equally likely, which is not the cast in practice. Even though some variations of the original sticks algorithm estimate poor probabilities from the image or from the imaging process, no high-level information about the geometry of the object of interest is utilized. As a result, both non-prostate structures and the true boundaries are equally enhanced. This paper presents an extension to the original sticks algorithm, which incorporates high-level knowledge of prostate shape to selectively enhance the prostate edge contrast while suppressing non-prostate structures. The improved algorithm shows that this extension preserves the prostate boundaries while providing superior noise reduction especially in the interior prostate region, which can lead to more accurate segmentation of the prostate.