DocumentCode :
419845
Title :
Detection and recognition of lung abnormalities using deformable templates
Author :
Farag, Aly A. ; El-Baz, Ayman ; Farb, Georgy Gimel ; Falk, Robert
Author_Institution :
CVIP Lab., Louisville Univ., KY, USA
Volume :
3
fYear :
2004
fDate :
23-26 Aug. 2004
Firstpage :
738
Abstract :
Automatic detection and recognition of lung cancer during mass screening of spiral computer tomographic (CT) chest scans is one of the most important problems of today´s medical image analysis. We propose an algorithm for isolating lung abnormalities (nodules) from arteries, veins, bronchi, and bronchioles after all these objects have been already separated from the surrounding anatomical structures. The separation is presented elsewhere, and this paper focuses on nodule detection using deformable 3D and 2D templates describing typical geometry and gray level distribution within the nodules of the same type. The detection combines normalized cross-correlation template matching by genetic optimization and Bayesian post-classification. Experiments with 200 spiral low dose CT (LDCT) scans confirm the accuracy of our approach.
Keywords :
Bayes methods; cancer; computerised tomography; genetic algorithms; image classification; image matching; lung; medical image processing; Bayesian post classification; anatomical structures; automatic lung cancer detection; automatic lung cancer recognition; cross correlation template matching; deformable 2D templates; deformable 3D templates; genetic optimization; geometry level distribution; gray level distribution; lung abnormalities detection; lung abnormalities recognition; medical image analysis; spiral computer tomographic chest scans; Arteries; Biomedical imaging; Cancer detection; Computed tomography; Image analysis; Image recognition; Lungs; Respiratory system; Spirals; Veins;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
ISSN :
1051-4651
Print_ISBN :
0-7695-2128-2
Type :
conf
DOI :
10.1109/ICPR.2004.1334634
Filename :
1334634
Link To Document :
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