@Article{JFBI-8-4,
author = {},
title = {PSO-based Medical Image Processing for Kienbock Biomechanical Analysis},
journal = {Journal of Fiber Bioengineering and Informatics},
year = {2015},
volume = {8},
number = {4},
pages = {697--704},
abstract = {Through the lunate bone biomechanical analysis can be used for kienböck medical diagnosis and treatment.
The pressure sensitive film can reflect intuitively the stress of lunate bone's each point. This paper obtains
stress analysis of lunate bone based on PSO (Particle Swarm Optimization) algorithm's image analysis
and processing of pressure sensitive film. The paper uses the grayscale function to change a target image
into the grayscale image, and uses the PSO algorithm for function optimization to segment image with
the original image. Then we obtain remaining achieving gray value, and calculate the pressure. Through
the analysis of the experimental data, we obtain the maximum value, minimum value and average value
of the pressure. The analysis of processing results showed that the PSO algorithm could segment the
image accurately and the remaining larger pixel gray values concentrated in the three fossa of lunate
bone. The results verify the accuracy and efficiency of the method.},
issn = {2617-8699},
doi = {https://doi.org/10.3993/jfbim00167},
url = {https://global-sci.com/article/86612/pso-based-medical-image-processing-for-kienbock-biomechanical-analysis}
}