A unified approach for detection, visualization, and identification of lung abnormalities in chest spiral CT scans

International Congress Series

Volumn 1256, Issue C, 2003, Pages 998-1004

  El Baz, Ayman ^a   Farag, Aly A ^a   Falk, Robert ^b   La Rocca, Renato ^c  

^a University of Louisville   (United States)

^b JEWISH HOSPITAL   (United States)

^c Kentuckiana Cancer Institute   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85015384440     PISSN: 05315131     EISSN: None     Source Type: Book Series    
DOI: 10.1016/S0531-5131(03)00475-8     Document Type: Article

References (8)

1. L Quekel A Kessels R Goei J.V Engelshoven Miss rate of lung cancer on the chest radiograph in clinical practice Chest 115 3 1999 720 724
2. S.-C Lo M Freedman J.-S Lin S Mun Automatic lung nodule detection using profile matching and back-propagation neural network techniques J. Digit. Imag. 6 1 1993 48 54
3. F Mao W Qian J Gaviria L Clarke Fragmentary window filtering for multiscale lung nodule detection Acad. Radiol. 5 4 1998 306 311
4. A El-Baz A.A Farag R Falk R La Rocca Automatic identification of lung abnormalities in chest spiral CT scans Proc. Of IEEE international Conf. On Acoustics, Speech, and Signal Processing, Hong Kong, April, 2003 2003
5. R.C Dubes A.K Jain Random field models in image analysis J. Appl. Stat. 16 2 1989 131 164
6. J Besag On the statistical analysis of the dirty pictures J. R. Stat. Soc., B (Lond.) B-48 1986 259 302
7. D.E GoldBerg Genetic Algorithms in Search, Optimization and Machine Learning 1989 Addison-Wesley Publishing
8. A. El-Baz, A.A. Farag, R. Falk, R. La Rocca, Detection, visualization, and identification of lung abnormalities in chest spiral CT scans: phase II. CVIP Research Report, February 2003.