Automated Feature Description of Renal Size Using Image Processing

  • Musab Sahrim USIM
Keywords: Renal Size, Automated Feature Description, Image Processing

Abstract

Ultrasonography (US) is one of the procedures to monitor the growth of renal size in diagnose kidney disease. However considering the complexity of renal size, this procedure leads to inter-observer variability and poor repeatability. Given images from Abdominal CT scan, a level set thresholding and combination of logical and arithmetic operation based method was developed to calculate the automated feature description of renal size. This is achieved by applying 2D CT scan image into image segmentation and feature extraction where thresholding and morphological segmentation method are conducted. Then, parameters of the kidney such as perimeter, area, major axis and minor axis were measured and analyzed in classification step. As a result, analysis on the kidney size between subjects who are normal and the results from the studies has shown capability to classify correctly the size of kidneys about accuracy of 80% to 81% in terms of the kidney’s relative axis which is the ratio of right kidney and left kidneys. In addition, the method in measurement kidney size is compared between manual method and automated method and results shows that the accuracy of the automated method in terms of compactness is about 91% to 95.

Published
2018-04-30
How to Cite
Sahrim, M. (2018). Automated Feature Description of Renal Size Using Image Processing. International Journal of Integrated Engineering, 10(1). Retrieved from https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/2504
Section
Articles