Small-size lung nodule modeling and detection with clinical evaluation

Author

Farag, Aly ; Graham, James ; Abdelmunim, Hossam ; Elshazly, Salwa ; Ei-Mogy, M. ; Ei-Mogy, S. ; Falk, Robert ; Farag, A.A.

Author_Institution

Comput. Vision & Image Process. Lab. (CVIP Lab.), Univ. of Louisville, Louisville, KY, USA

fYear

2012

fDate

20-22 Dec. 2012

Firstpage

44

Lastpage

47

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.

Keywords

computerised tomography; image matching; lung; medical image processing; pneumodynamics; AAM approach; active appearance modeling approach; automatic detection; clinical evaluation; image pixels; lung CT slice; lung detection; nodule detection; performance validation; similarity score; small-size lung nodule modeling; template matching approach; template modeling process; Computational modeling; Computed tomography; Databases; Lungs; Principal component analysis; Solid modeling; Data-driven; Lung nodule modeling; nodule detection;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering Conference (CIBEC), 2012 Cairo International

Conference_Location

Giza

ISSN

2156-6097

Print_ISBN

978-1-4673-2800-5

Type

conf

DOI

10.1109/CIBEC.2012.6473332

Filename

6473332