Small-size lung nodule modeling and detection with clinical evaluation
Farag, Amal; Graham, James; Hossam El DIn Hassan Abdelmunim; Elshazly, Salwa; Ei-Mogy, Mohamed; Ei-Mogy, Sabry; Falk, Robert; Farag, Aly A.;
Abstract
In this paper examination of the template modeling process using the Active Appearance Modeling (AAM) approach for automatic detection of lung nodules is investigated. A template matching approach is formulated to compute a similarity score between the AAM templates and the input lung CT slice, where the goal is to maximize the similarity measure at different image pixels to increase nodule detection. The template matching approach is implemented using nine similarity measures. Performance validation for the robustness of the generated models is tested on three clinical databases. © 2012 IEEE.
Other data
| Title | Small-size lung nodule modeling and detection with clinical evaluation | Authors | Farag, Amal; Graham, James; Hossam El DIn Hassan Abdelmunim ; Elshazly, Salwa; Ei-Mogy, Mohamed; Ei-Mogy, Sabry; Falk, Robert; Farag, Aly A. | Keywords | Data-driven;Lung nodule modeling;nodule detection | Issue Date | 1-Dec-2012 | Conference | 2012 Cairo International Biomedical Engineering Conference Cibec 2012 | ISBN | [9781467328012] | DOI | 10.1109/CIBEC.2012.6473332 | Scopus ID | 2-s2.0-84875579847 |
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