Analysis of motion detection of breast tumor based on tissue elasticity from B mode ultrasound images using gradient method optical flow algorithm
As the effectiveness of an early detection of breast cancer using the mammography method alone is uncertain, it is crucial to provide an alternative method instead. This paper analyzes two optical flow algorithms utilizing a gradient method to aid current imaging techniques for a potential alternati...
Saved in:
Main Authors: | , , , |
---|---|
Format: | Conference Paper |
Language: | en_US |
Published: |
Institute of Electrical and Electronics Engineers Inc.
2015
|
Subjects: | |
Online Access: | http://ddms.usim.edu.my/handle/123456789/9042 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.usim-9042 |
---|---|
record_format |
dspace |
spelling |
my.usim-90422015-08-12T06:55:15Z Analysis of motion detection of breast tumor based on tissue elasticity from B mode ultrasound images using gradient method optical flow algorithm F.M.M., Shuib M., Othman K., Abdulrahim Z., Zulkifli breast cancer elastrography optical flow gradient ultrasound As the effectiveness of an early detection of breast cancer using the mammography method alone is uncertain, it is crucial to provide an alternative method instead. This paper analyzes two optical flow algorithms utilizing a gradient method to aid current imaging techniques for a potential alternative method in aiding early breast cancer detection. The gradient method is a cost effective method that has the potential to be a mass screening method for this purpose. This paper compares two optical flow algorithms that are capable to detect the motion of breast tumor on B-mode ultrasound images. An analysis of 2D images of breast cancer lesions are compared using two gradient optical flow algorithms: Horn & Schunck and Lucas & Kanade. Both algorithms successfully show the direction of the tumor motion. However, while Lucas & Kanade can handle the short motion displacement of the tumor on the tested ultrasound images, Horn & Shunck failed to do so. This implies that the Lucas & Kanade algorithm is potentially more effective in handling ultrasound images of breast tumor. The results obtained showed that the Lucas & Kanade give better accuracy compared to Horn & Schunk. 2015-08-12T06:55:15Z 2015-08-12T06:55:15Z 2014 Conference Paper 9781-4799-3251-1 http://ddms.usim.edu.my/handle/123456789/9042 en_US Institute of Electrical and Electronics Engineers Inc. |
institution |
Universiti Sains Islam Malaysia |
building |
USIM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universit Sains Islam i Malaysia |
content_source |
USIM Institutional Repository |
url_provider |
http://ddms.usim.edu.my/ |
language |
en_US |
topic |
breast cancer elastrography optical flow gradient ultrasound |
spellingShingle |
breast cancer elastrography optical flow gradient ultrasound F.M.M., Shuib M., Othman K., Abdulrahim Z., Zulkifli Analysis of motion detection of breast tumor based on tissue elasticity from B mode ultrasound images using gradient method optical flow algorithm |
description |
As the effectiveness of an early detection of breast cancer using the mammography method alone is uncertain, it is crucial to provide an alternative method instead. This paper analyzes two optical flow algorithms utilizing a gradient method to aid current imaging techniques for a potential alternative method in aiding early breast cancer detection. The gradient method is a cost effective method that has the potential to be a mass screening method for this purpose. This paper compares two optical flow algorithms that are capable to detect the motion of breast tumor on B-mode ultrasound images. An analysis of 2D images of breast cancer lesions are compared using two gradient optical flow algorithms: Horn & Schunck and Lucas & Kanade. Both algorithms successfully show the direction of the tumor motion. However, while Lucas & Kanade can handle the short motion displacement of the tumor on the tested ultrasound images, Horn & Shunck failed to do so. This implies that the Lucas & Kanade algorithm is potentially more effective in handling ultrasound images of breast tumor. The results obtained showed that the Lucas & Kanade give better accuracy compared to Horn & Schunk. |
format |
Conference Paper |
author |
F.M.M., Shuib M., Othman K., Abdulrahim Z., Zulkifli |
author_facet |
F.M.M., Shuib M., Othman K., Abdulrahim Z., Zulkifli |
author_sort |
F.M.M., Shuib |
title |
Analysis of motion detection of breast tumor based on tissue elasticity from B mode ultrasound images using gradient method optical flow algorithm |
title_short |
Analysis of motion detection of breast tumor based on tissue elasticity from B mode ultrasound images using gradient method optical flow algorithm |
title_full |
Analysis of motion detection of breast tumor based on tissue elasticity from B mode ultrasound images using gradient method optical flow algorithm |
title_fullStr |
Analysis of motion detection of breast tumor based on tissue elasticity from B mode ultrasound images using gradient method optical flow algorithm |
title_full_unstemmed |
Analysis of motion detection of breast tumor based on tissue elasticity from B mode ultrasound images using gradient method optical flow algorithm |
title_sort |
analysis of motion detection of breast tumor based on tissue elasticity from b mode ultrasound images using gradient method optical flow algorithm |
publisher |
Institute of Electrical and Electronics Engineers Inc. |
publishDate |
2015 |
url |
http://ddms.usim.edu.my/handle/123456789/9042 |
_version_ |
1645152526111080448 |
score |
13.214268 |