Breast Ultrasound Automated ROI Segmentation with Region Growing

Image segmentation is an important technology used in different areas ranging from image processing to image analysis. One of the simplest methods for image segmentation that is widely implemented in medical images is the region growing method. Current researches mostly focus on using the region...

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Main Authors:	Lee, Lay-Khoon, Liew, Siau-Chuin
Format:	Conference or Workshop Item
Language:	English
Published:	IEEE 2015
Subjects:	Q Science (General) QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/10665/ http://umpir.ump.edu.my/id/eprint/10665/ http://umpir.ump.edu.my/id/eprint/10665/1/Breast%20ultrasound%20automated%20ROI%20segmentation%20with.pdf

id	ump-10665
recordtype	eprints
spelling	ump-106652016-07-21T04:33:21Z http://umpir.ump.edu.my/id/eprint/10665/ Breast Ultrasound Automated ROI Segmentation with Region Growing Lee, Lay-Khoon Liew, Siau-Chuin Q Science (General) QA76 Computer software Image segmentation is an important technology used in different areas ranging from image processing to image analysis. One of the simplest methods for image segmentation that is widely implemented in medical images is the region growing method. Current researches mostly focus on using the region growing method to automatically detect the presence of tumor in MRI (Magnetic Resonance) images instead of ultrasound images. In this paper, we present an algorithm to automatically detect tumors in ultrasound images. Inspired by SergeBeucher and Balasubramanian’s road segmentation algorithm, this paper will implement the road segmentation algorithm into medical image segmentation. Results show that, the road segmentation algorithm actually works on the segmentation of medical image. The dice coefficient was used to evaluate the accuracy of the algorithm, eventually getting a value of 0.988 ± 0.00147 as the mean and standard deviation. This value is significant, because the higher the DC value, the more accurate is the segmentation. Besides that, the DC value can use for future reference and comparison. IEEE 2015-08 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/10665/1/Breast%20ultrasound%20automated%20ROI%20segmentation%20with.pdf Lee, Lay-Khoon and Liew, Siau-Chuin (2015) Breast Ultrasound Automated ROI Segmentation with Region Growing. In: IEEE 4th International Conference on Software Engineering and Computer Systems, 19-21 August 2015 , Kuantan, Pahang, Malaysia. pp. 177-182.. ISBN 978-1-4673-6722-6 http://dx.doi.org/10.1109/ICSECS.2015.7333106
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	Q Science (General) QA76 Computer software
spellingShingle	Q Science (General) QA76 Computer software Lee, Lay-Khoon Liew, Siau-Chuin Breast Ultrasound Automated ROI Segmentation with Region Growing
description	Image segmentation is an important technology used in different areas ranging from image processing to image analysis. One of the simplest methods for image segmentation that is widely implemented in medical images is the region growing method. Current researches mostly focus on using the region growing method to automatically detect the presence of tumor in MRI (Magnetic Resonance) images instead of ultrasound images. In this paper, we present an algorithm to automatically detect tumors in ultrasound images. Inspired by SergeBeucher and Balasubramanian’s road segmentation algorithm, this paper will implement the road segmentation algorithm into medical image segmentation. Results show that, the road segmentation algorithm actually works on the segmentation of medical image. The dice coefficient was used to evaluate the accuracy of the algorithm, eventually getting a value of 0.988 ± 0.00147 as the mean and standard deviation. This value is significant, because the higher the DC value, the more accurate is the segmentation. Besides that, the DC value can use for future reference and comparison.
format	Conference or Workshop Item
author	Lee, Lay-Khoon Liew, Siau-Chuin
author_facet	Lee, Lay-Khoon Liew, Siau-Chuin
author_sort	Lee, Lay-Khoon
title	Breast Ultrasound Automated ROI Segmentation with Region Growing
title_short	Breast Ultrasound Automated ROI Segmentation with Region Growing
title_full	Breast Ultrasound Automated ROI Segmentation with Region Growing
title_fullStr	Breast Ultrasound Automated ROI Segmentation with Region Growing
title_full_unstemmed	Breast Ultrasound Automated ROI Segmentation with Region Growing
title_sort	breast ultrasound automated roi segmentation with region growing
publisher	IEEE
publishDate	2015
url	http://umpir.ump.edu.my/id/eprint/10665/ http://umpir.ump.edu.my/id/eprint/10665/ http://umpir.ump.edu.my/id/eprint/10665/1/Breast%20ultrasound%20automated%20ROI%20segmentation%20with.pdf
first_indexed	2023-09-18T22:10:31Z
last_indexed	2023-09-18T22:10:31Z
_version_	1777414996340244480

Breast Ultrasound Automated ROI Segmentation with Region Growing

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