Abstract
A new algorithm for the detection of masses in mammographic images is presented. The algorithm has been designed in two steps. Firstly, the regions likely to be a mass are detected by using a deformable template matching approach, where the template is constructed using the eigenimages of a set of manually detected masses. Subsequently, an algorithm adapted from the eigenfaces approach is used to assure that the detected regions really depict true masses (false positive reduction). The evaluation uses a leave-one-out methodology and is based on a database of 120 mammograms, which include 40 masses and 80 normals. ROC and FROC analysis is used to demonstrate the potential of the developed approach.
| Original language | English |
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| Pages | 71-75 |
| Number of pages | 5 |
| Publication status | Published - 04 Jul 2006 |
| Event | 10th UK Conference on Medical Image Understanding and Analysis - MIUA: 4-5 th July 2006, University of Manchester - University of Manchester, Manchester, United Kingdom of Great Britain and Northern Ireland Duration: 04 Jul 2006 → 05 Jul 2006 |
Conference
| Conference | 10th UK Conference on Medical Image Understanding and Analysis - MIUA |
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| Abbreviated title | MIUA 2006 |
| Country/Territory | United Kingdom of Great Britain and Northern Ireland |
| City | Manchester |
| Period | 04 Jul 2006 → 05 Jul 2006 |