Faster Image Dendrogram Creation: An Efficient Algorithm for the Detection of Tumours in Digital Mammography

Mitchell, RA; Nguyen, HT; Thornton, BS; Hung, WT; Lee, W; Rickard, M

Faster Image Dendrogram Creation: An Efficient Algorithm for the Detection of Tumours in Digital Mammography

Mitchell, RA Nguyen, HT

Thornton, BS Hung, WT

Lee, W Rickard, M

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Publication Type:: Conference Proceeding
Citation:: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, 2003, 1 pp. 714 - 716
Issue Date:: 2003-12-01

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Field	Value	Language
dc.contributor.author	Mitchell, RA	en_US
dc.contributor.author	Nguyen, HT https://orcid.org/0000-0003-3373-8178	en_US
dc.contributor.author	Thornton, BS	en_US
dc.contributor.author	Hung, WT https://orcid.org/0000-0002-0058-1680	en_US
dc.contributor.author	Lee, W	en_US
dc.contributor.author	Rickard, M	en_US
dc.date.issued	2003-12-01	en_US
dc.identifier.citation	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, 2003, 1 pp. 714 - 716	en_US
dc.identifier.issn	0589-1019	en_US
dc.identifier.uri	http://hdl.handle.net/10453/2795
dc.description.abstract	Dendronic image analysis has been shown to provide a robust technique in the detection of tumours within digital mammograms. It provides the capability of fully automated image analysis through hierarchical segmentation. However, its general acceptance in image analysis has not been realised due to computational intensity in creating the image dendrogram. We have developed an efficient technique that can create image dendrograms a great deal faster than traditional repetitive segmentation algorithms, making dendronic analysis of digital mammograms a viable tool in the detection of breast cancer.	en_US
dc.relation	http://purl.org/au-research/grants/arc/C10010018
dc.relation.ispartof	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings	en_US
dc.title	Faster Image Dendrogram Creation: An Efficient Algorithm for the Detection of Tumours in Digital Mammography	en_US
dc.type	Conference Proceeding
utslib.citation.volume	1	en_US
utslib.for	090305 Rehabilitation Engineering	en_US
utslib.for	090303 Biomedical Instrumentation	en_US
dc.location.activity	Cancun, Mexico	en_US
dc.location.activity	Cancun, MEXICO
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	1	en_US

Abstract:

Dendronic image analysis has been shown to provide a robust technique in the detection of tumours within digital mammograms. It provides the capability of fully automated image analysis through hierarchical segmentation. However, its general acceptance in image analysis has not been realised due to computational intensity in creating the image dendrogram. We have developed an efficient technique that can create image dendrograms a great deal faster than traditional repetitive segmentation algorithms, making dendronic analysis of digital mammograms a viable tool in the detection of breast cancer.

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http://hdl.handle.net/10453/2795