DocumentCode
1587322
Title
Nodule detection in 3D chest CT images using 2nd order autocorrelation features
Author
Hara, T. ; Hirose, M. ; Zhou, X. ; Fujita, H. ; Kiryu, T. ; Yokoyama, R. ; Hoshi, H.
Author_Institution
Dept. of Intelligent Image Information, Gifu Univ.
fYear
2006
Firstpage
6247
Lastpage
6249
Abstract
We have developed a new recognition approach using 2nd order autocorrelation and multi-regression analysis to detect a small (<7mm in diameter) lung nodules in chest 3D CT images. By combining our previous detection method of the template matching based on genetic algorithm, the detection performance was 94% true-positive rate at 2.05 false-positive marks per case using leave-one-out study
Keywords
computerised tomography; genetic algorithms; image matching; medical image processing; regression analysis; 2nd order autocorrelation features; 3D chest CT images; genetic algorithm; image recognition; multiregression analysis; nodule detection; template matching; Autocorrelation; Band pass filters; Biomedical engineering; Computed tomography; Frequency; Gaussian distribution; Image analysis; Matched filters; Shape; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location
Shanghai
Print_ISBN
0-7803-8741-4
Type
conf
DOI
10.1109/IEMBS.2005.1615924
Filename
1615924
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