Computer-aided visualization and segmentation of structures of interest in ultrasound images require speckle noise reduction typically via lowpass filtering at the cost of blurring the edges. We have found that an advanced technique called 'sticks' algorithm, the possible locations of a reflector is modeled by a set of short line segments each with a different orientation. The goal is to select a particular stick out of the many different possible stick orientations, which best describes a reflector in the neighborhood. The original 'sticks' algorithm assumes that ultrasound echo could originate from a reflector positioned in any orientation with respect to the incident ultrasound beam, which is not a 100 percent valid assumption. Instead, for every possible reflector location in the image, we calculate the prior probability of different possible stick templates. Using Bayesian decision theory, we have integrated this additional information into the original sticks algorithm. The results indicate that similar to the original sticks algorithms, the speckles are reduced while preserving the edges in the image. In addition, the new sticks algorithm is faster than the original algorithm by a factor of 4.2. This approach is one of the few attempts in ultrasound image segmentation where the knowledge of the imaging process, such as the transducer position, has been incorporated for improved contrast enhancement.