Cover Image

Breast boundary segmentation in thermography images based on random walkers

Breast and areola boundary detection and segmentation present the biggest challenge in breast segmentation from thermography images, as breast boundaries, especially in the upper quadrants of the breast, are nonexistent. Many segmentation approaches have been proposed for breast segmentation, such a...

Full description

Saved in:
Bibliographic Details
Main Authors: Moghbel, Mehrdad, Mashohor, Syamsiah, Mahmud, Rozi, Saripan, M. Iqbal, Ab. Hamid, Suzana, Mohamad Saini, Suraini, Abdul Rashid, Saiful Nizam
Format: Article
Language:English
Published: Scientific and Technological Research Council of Turkey 2017
Online Access:http://psasir.upm.edu.my/id/eprint/61026/1/Breast%20boundary%20segmentation%20in%20thermography%20images%20based%20on%20random%20walkers.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
id oai:psasir.upm.edu.my:61026
record_format eprints
spelling oai:psasir.upm.edu.my:61026 http://psasir.upm.edu.my/id/eprint/61026/ Breast boundary segmentation in thermography images based on random walkers Moghbel, Mehrdad Mashohor, Syamsiah Mahmud, Rozi Saripan, M. Iqbal Ab. Hamid, Suzana Mohamad Saini, Suraini Abdul Rashid, Saiful Nizam Breast and areola boundary detection and segmentation present the biggest challenge in breast segmentation from thermography images, as breast boundaries, especially in the upper quadrants of the breast, are nonexistent. Many segmentation approaches have been proposed for breast segmentation, such as active contours and snakes, circular Hough transforms, and live wires, but these methods often fail to achieve satisfactory results. With recent advances in image processing techniques, new segmentation concepts are being developed, such as random walkers, which have received high interest from the medical imaging community. In this study, 91 images acquired utilizing a FLIR A320 thermal camera are used for developing an automatic breast segmentation from thermography images based on the random walker algorithm. A series of enhancement filters are applied to the image to make areola detection more accurate. Afterwards, the areola is detected using a series of circular Hough transforms. The detected areola region is then utilized for automatic seed placement for the random walker algorithm. Based on expert radiologist evaluation, the proposed segmentation algorithm was able to achieve 81.3% success rate in breast segmentation, while there was a 37.5% increase in the detection of breast cancer-related abnormalities by radiologists utilizing the segmented images, compared to utilizing original images. Scientific and Technological Research Council of Turkey 2017 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/61026/1/Breast%20boundary%20segmentation%20in%20thermography%20images%20based%20on%20random%20walkers.pdf Moghbel, Mehrdad and Mashohor, Syamsiah and Mahmud, Rozi and Saripan, M. Iqbal and Ab. Hamid, Suzana and Mohamad Saini, Suraini and Abdul Rashid, Saiful Nizam (2017) Breast boundary segmentation in thermography images based on random walkers. Turkish Journal of Electrical Engineering & Computer Sciences, 25 (3). 1733 - 1750. ISSN 1300-0632; ESSN: 1303-6203 https://pdfs.semanticscholar.org/f5f7/5f1a26f95ba14236cc719f62bdf3091cfe2c.pdf 10.3906/elk-1601-148
institution UPM IR
collection UPM IR
language English
description Breast and areola boundary detection and segmentation present the biggest challenge in breast segmentation from thermography images, as breast boundaries, especially in the upper quadrants of the breast, are nonexistent. Many segmentation approaches have been proposed for breast segmentation, such as active contours and snakes, circular Hough transforms, and live wires, but these methods often fail to achieve satisfactory results. With recent advances in image processing techniques, new segmentation concepts are being developed, such as random walkers, which have received high interest from the medical imaging community. In this study, 91 images acquired utilizing a FLIR A320 thermal camera are used for developing an automatic breast segmentation from thermography images based on the random walker algorithm. A series of enhancement filters are applied to the image to make areola detection more accurate. Afterwards, the areola is detected using a series of circular Hough transforms. The detected areola region is then utilized for automatic seed placement for the random walker algorithm. Based on expert radiologist evaluation, the proposed segmentation algorithm was able to achieve 81.3% success rate in breast segmentation, while there was a 37.5% increase in the detection of breast cancer-related abnormalities by radiologists utilizing the segmented images, compared to utilizing original images.
format Article
author Moghbel, Mehrdad
Mashohor, Syamsiah
Mahmud, Rozi
Saripan, M. Iqbal
Ab. Hamid, Suzana
Mohamad Saini, Suraini
Abdul Rashid, Saiful Nizam
spellingShingle Moghbel, Mehrdad
Mashohor, Syamsiah
Mahmud, Rozi
Saripan, M. Iqbal
Ab. Hamid, Suzana
Mohamad Saini, Suraini
Abdul Rashid, Saiful Nizam
Breast boundary segmentation in thermography images based on random walkers
author_facet Moghbel, Mehrdad
Mashohor, Syamsiah
Mahmud, Rozi
Saripan, M. Iqbal
Ab. Hamid, Suzana
Mohamad Saini, Suraini
Abdul Rashid, Saiful Nizam
author_sort Moghbel, Mehrdad
title Breast boundary segmentation in thermography images based on random walkers
title_short Breast boundary segmentation in thermography images based on random walkers
title_full Breast boundary segmentation in thermography images based on random walkers
title_fullStr Breast boundary segmentation in thermography images based on random walkers
title_full_unstemmed Breast boundary segmentation in thermography images based on random walkers
title_sort breast boundary segmentation in thermography images based on random walkers
publisher Scientific and Technological Research Council of Turkey
publishDate 2017
url http://psasir.upm.edu.my/id/eprint/61026/1/Breast%20boundary%20segmentation%20in%20thermography%20images%20based%20on%20random%20walkers.pdf
_version_ 1782756225621950464
score 12.933938

Similar Items