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All Journal Proceeding of the Electrical Engineering Computer Science and Informatics
Ginus Partadiredja
Universitas Gadjah Mada
Computer Science & IT Electrical & Electronics Engineering

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Implementation of Unbiased Stereology Method for Organ Volume Estimation using Image Processing Mohammad Ammar Faiq; Balza Achmad; Ginus Partadiredja
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (4190.213 KB) | DOI: 10.11591/eecsi.v4.1000

Abstract

Stereology had been widely used around the globe for estimating the value of the biological structure. It interlinks the connection between the dimensions using a sample that is 2D for a quantification in 3D structure. Volume estimation using stereology method is the most common and basic quantification that shows an example of how stereology works. Stereology method has a drawback when it comes to a lot of samples, so it is common for a researcher to use the computer to help to quantify and to do repetitive work, which is known as computer-assisted stereology quantification. The purpose of this research is to develop software that can assist researchers using stereology method for estimating the volume of a sample object from its 2D digital images with point counting method. The software was built based on the manual procedure of volume estimation using stereology method performed by experienced researchers. The volume estimation using the software were then compared with the results of the manual procedure by the experts on the same samples, i.e., the kidney and trigeminal ganglion of a rat. The experimental results showed that the relative difference of the volume estimations between manual and computer assisted calculations were 0.93% for rat kidney sample and 10.81%. TA1 trigeminal ganglion sample. Based on the results, the software estimation can be used for further analysis.
Co-Authors Balza Achmad Mohammad Ammar Faiq