Multi-threshhold Ultrasound Image Segmentation Based on Potential Function Clustering

Multi-threshhold Ultrasound Image Segmentation Based on Potential Function Clustering

Year:    2015

Journal of Fiber Bioengineering and Informatics, Vol. 8 (2015), Iss. 2 : pp. 277–284

Abstract

Ultrasound image segmentation is an important task for clinical diagnosis. In this study, a multi- threshhold segmentation approach was proposed to enhance ultrasound image segmentation accuracy. More specifically, the proposed multi-threshhold segmentation approach, combining an opening-closing morphological filter and potential function clustering theory, attempted to provide better ultrasound image segmentation visibility. This proposed approach was tested using computer-simulated images and in vivo images. Computer simulation results demonstrated that the method significantly improved the accuracy of image segmentation. From in vivo images investigation, we have found that, as compared with the original images, better segmentation visibility were obtained. Our initial results demonstrated that this method could be useful for improving the segmentation quality of ultrasound images as a post-processing tool.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/doi:10.3993/jfbim00101

Journal of Fiber Bioengineering and Informatics, Vol. 8 (2015), Iss. 2 : pp. 277–284

Published online:    2015-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    8

Keywords:    Ultrasound Image Segmentation