Multi-threshhold Ultrasound Image Segmentation Based on Potential Function Clustering (Journal of Fiber Bioengineering and Informatics, 2015)
Ultrasound image segmentation is an important task for clinical diagnosis. In this study, a multi-\rthreshhold segmentation approach was proposed to enhance ultrasound image segmentation accuracy.\rMore specifically, the proposed multi-threshhold segmentation approach, combining an opening-closing\rmorphological filter and potential function clustering theory, attempted to provide better ultrasound\rimage segmentation visibility. This proposed approach was tested using computer-simulated images and\rin vivo images. Computer simulation results demonstrated that the method significantly improved the\raccuracy of image segmentation. From in vivo images investigation, we have found that, as compared\rwith the original images, better segmentation visibility were obtained. Our initial results demonstrated\rthat this method could be useful for improving the segmentation quality of ultrasound images as a\rpost-processing tool.