Abstract
Appearance of breast parenchyma in mammography provides information on the risk of developing breast cancer. Wolfe was the first to show the relation between mammographic parenchymal patterns and the risk of developing cancer using four classes. Since this discovery automated classification has been investigated. The methods developed can be separated in first order statistical models and texture analysis models. A novel approach based on the percentage of glandular tissue in the breast interpolated from 2D mammographic images is presented. This model is based on the hint model introduced by Highnam et al. We investigate the effect of a number of parameters in our model and indicate that the robustness for possible clinical use depends on the uncertainty with which the parameters are determined.
| Original language | English |
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| Pages | 65-68 |
| Number of pages | 4 |
| Publication status | Published - 22 Jul 2002 |
| Externally published | Yes |
| Event | Medical Image Understanding and Analysis 2002 - University of Portsmouth, Portsmouth, United Kingdom of Great Britain and Northern Ireland Duration: 22 Jul 2002 → 23 Jul 2002 |
Conference
| Conference | Medical Image Understanding and Analysis 2002 |
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| Abbreviated title | MIUA 2002 |
| Country/Territory | United Kingdom of Great Britain and Northern Ireland |
| City | Portsmouth |
| Period | 22 Jul 2002 → 23 Jul 2002 |
