@Article{JFBI-8-2,
author = {},
title = {Multi-threshhold Ultrasound Image Segmentation Based on Potential Function Clustering},
journal = {Journal of Fiber Bioengineering and Informatics},
year = {2015},
volume = {8},
number = {2},
pages = {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.},
issn = {2617-8699},
doi = {https://doi.org/doi:10.3993/jfbim00101},
url = {https://global-sci.com/article/86554/multi-threshhold-ultrasound-image-segmentation-based-on-potential-function-clustering}
}