Segmentation of medical ultrasound image based on local histogram range image

Image segmentation plays an important role in both qualitative and quantitative analysis of medical ultrasound images but it is known to be a difficult task due to the relatively low resolution and reduced contrast of the images, as well as due to the discontinuity and uncertainty of segmentation boundaries caused by speckle noise. Under such conditions, useful segmentation results seem to be only achievable by means of relatively complex algorithms, which are usually computationally involved and/or require a prior learning. In this paper, we proposed a new segmental method combined local histogram range image (LHRI) model with morphological image processing. In the first step, LHRI is used to obtain a primary segmentation and morphological image processing makes the region-of-interest (ROI) complete to get a complete tissue. Experimental result on medical ultrasound images show that our proposed algorithm can correctly segment the tissue's on ultrasound images.