Automated Seed-Based Region Growing Using The Moving K-Means Clustering For The Detection Of Mammographic Microcalcifications.
Mammography is by far the proven method of early detection of breast cancer. However, mammography is not without its problems. It is amongst the most difficult of radiological images to interpret as the images are of low contrast and features indicative of abnormalities are very subtle and minute....
| Main Authors: | , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2003
|
| Subjects: | |
| Online Access: | http://eprints.usm.my/14166/ http://eprints.usm.my/14166/1/automated.pdf |
| _version_ | 1848871956236992512 |
|---|---|
| author | Ngah, Umi Kalthum Mat Isa, N A Mohd Noor, Masriah |
| author_facet | Ngah, Umi Kalthum Mat Isa, N A Mohd Noor, Masriah |
| author_sort | Ngah, Umi Kalthum |
| building | USM Institutional Repository |
| collection | Online Access |
| description | Mammography is by far the proven method of early detection of breast cancer. However, mammography is not without its problems. It is amongst the most difficult of radiological
images to interpret as the images are of low contrast and features indicative of abnormalities are very subtle and minute. In this study, a new method of automated edge
detection technique is proposed to detect the abnormalities in a region of interest in a mammogram.
|
| first_indexed | 2025-11-15T15:48:18Z |
| format | Conference or Workshop Item |
| id | usm-14166 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T15:48:18Z |
| publishDate | 2003 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-141662017-11-20T07:22:11Z http://eprints.usm.my/14166/ Automated Seed-Based Region Growing Using The Moving K-Means Clustering For The Detection Of Mammographic Microcalcifications. Ngah, Umi Kalthum Mat Isa, N A Mohd Noor, Masriah TK1-9971 Electrical engineering. Electronics. Nuclear engineering Mammography is by far the proven method of early detection of breast cancer. However, mammography is not without its problems. It is amongst the most difficult of radiological images to interpret as the images are of low contrast and features indicative of abnormalities are very subtle and minute. In this study, a new method of automated edge detection technique is proposed to detect the abnormalities in a region of interest in a mammogram. 2003 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.usm.my/14166/1/automated.pdf Ngah, Umi Kalthum and Mat Isa, N A and Mohd Noor, Masriah (2003) Automated Seed-Based Region Growing Using The Moving K-Means Clustering For The Detection Of Mammographic Microcalcifications. In: World Congress On Medical Physics And Biomedical Engineering (WC2003), 24 - 29 August 2003, Sydney, Australia. |
| spellingShingle | TK1-9971 Electrical engineering. Electronics. Nuclear engineering Ngah, Umi Kalthum Mat Isa, N A Mohd Noor, Masriah Automated Seed-Based Region Growing Using The Moving K-Means Clustering For The Detection Of Mammographic Microcalcifications. |
| title | Automated Seed-Based Region Growing Using The Moving K-Means Clustering For The Detection Of Mammographic Microcalcifications. |
| title_full | Automated Seed-Based Region Growing Using The Moving K-Means Clustering For The Detection Of Mammographic Microcalcifications. |
| title_fullStr | Automated Seed-Based Region Growing Using The Moving K-Means Clustering For The Detection Of Mammographic Microcalcifications. |
| title_full_unstemmed | Automated Seed-Based Region Growing Using The Moving K-Means Clustering For The Detection Of Mammographic Microcalcifications. |
| title_short | Automated Seed-Based Region Growing Using The Moving K-Means Clustering For The Detection Of Mammographic Microcalcifications. |
| title_sort | automated seed-based region growing using the moving k-means clustering for the detection of mammographic microcalcifications. |
| topic | TK1-9971 Electrical engineering. Electronics. Nuclear engineering |
| url | http://eprints.usm.my/14166/ http://eprints.usm.my/14166/1/automated.pdf |