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Automatic ultrasound kidney's centroid detection system

Currently, kidney stone and tumor removal can be done without surgery. For this purpose, it is required imaging modalities that able to visualize kidney accurately. In order to improve the accuracy of kidney visualization in a short time, an automatic kidney centroid detection is required. This proj...

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Main Authors: Supriyanto, Eko, Tahir, Nurul Afiqah, Syed Omar, Syed Mohd. Nooh
Format: Conference or Workshop Item
Published: 2011
Subjects:
Q Science (General)
R Medicine (General)
Online Access:http://eprints.utm.my/id/eprint/45622/
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spelling my.utm.456222017-09-07T04:56:11Z http://eprints.utm.my/id/eprint/45622/ Automatic ultrasound kidney's centroid detection system Supriyanto, Eko Tahir, Nurul Afiqah Syed Omar, Syed Mohd. Nooh Q Science (General) R Medicine (General) Currently, kidney stone and tumor removal can be done without surgery. For this purpose, it is required imaging modalities that able to visualize kidney accurately. In order to improve the accuracy of kidney visualization in a short time, an automatic kidney centroid detection is required. This project developed a software to automatically detect the centroid of human kidney. The software was developed using MATLAB with smoothing filter, texture filter and morphological operators. They were used for image segmentation in order to extract important features. Test result shows the software achieve until 96.43% of accuracy in detecting the centroid. The detected centroid can be used as initial point to create ellipse model, which can be used to detect kidney's contour in further research. This software can be implemented in the most US machine that will be used as segmentation tool to reduce human errors and time. 2011 Conference or Workshop Item PeerReviewed Supriyanto, Eko and Tahir, Nurul Afiqah and Syed Omar, Syed Mohd. Nooh (2011) Automatic ultrasound kidney's centroid detection system. In: 15th WSEAS International Conference on Computers, 15-17 July 2011, Corfu Island, Greece.
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic Q Science (General)
R Medicine (General)
spellingShingle Q Science (General)
R Medicine (General)
Supriyanto, Eko
Tahir, Nurul Afiqah
Syed Omar, Syed Mohd. Nooh
Automatic ultrasound kidney's centroid detection system
description Currently, kidney stone and tumor removal can be done without surgery. For this purpose, it is required imaging modalities that able to visualize kidney accurately. In order to improve the accuracy of kidney visualization in a short time, an automatic kidney centroid detection is required. This project developed a software to automatically detect the centroid of human kidney. The software was developed using MATLAB with smoothing filter, texture filter and morphological operators. They were used for image segmentation in order to extract important features. Test result shows the software achieve until 96.43% of accuracy in detecting the centroid. The detected centroid can be used as initial point to create ellipse model, which can be used to detect kidney's contour in further research. This software can be implemented in the most US machine that will be used as segmentation tool to reduce human errors and time.
format Conference or Workshop Item
author Supriyanto, Eko
Tahir, Nurul Afiqah
Syed Omar, Syed Mohd. Nooh
author_facet Supriyanto, Eko
Tahir, Nurul Afiqah
Syed Omar, Syed Mohd. Nooh
author_sort Supriyanto, Eko
title Automatic ultrasound kidney's centroid detection system
title_short Automatic ultrasound kidney's centroid detection system
title_full Automatic ultrasound kidney's centroid detection system
title_fullStr Automatic ultrasound kidney's centroid detection system
title_full_unstemmed Automatic ultrasound kidney's centroid detection system
title_sort automatic ultrasound kidney's centroid detection system
publishDate 2011
url http://eprints.utm.my/id/eprint/45622/
_version_ 1643651794760368128
score 13.211869

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