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General Information
    • ISSN: 2301-3559
    • Frequency: Quarterly
    • DOI: 10.18178/LNSE
    • Editor-in-Chief: Prof. Jemal Antidze
    • Executive Editor: Ms. Nina Lee
    • Abstracting/ Indexing: EI (INSPEC, IET), DOAJ, Electronic Journals Library, Engineering & Technology Digital Library, Ulrich's Periodicals Directory, International Computer Science Digital Library (ICSDL), ProQuest and Google Scholar.
    • E-mail: lnse@ejournal.net
Editor-in-chief
Prof. Jemal Antidze
I. Vekua Scientific Institute of Applied Mathematics
Tbilisi State University, Georgia
I'm happy to take on the position of editor in chief of LNSE. We encourage authors to submit papers concerning any branch of Software Engineering.

LNSE 2013 Vol.1(4): 364-369 ISSN: 2301-3559
DOI: 10.7763/LNSE.2013.V1.78

Implementation of Computer Aided Diagnosis System for Lung Cancer Detection

Naveed Ejaz, Shazia Javed, and Zeeshan Sajid
Abstract—Computer Aided Diagnosis in radiology assists the radiologists in determining medical abnormalities by providing automated analysis of medical images. The clinical acceptance of Computer Aided Diagnosis systems depends on successful execution of two tasks: segmentation of organ of interest, and identification and classification of abnormalities present on the organ. In this paper we present in detail the implemented Computer Aided Diagnosis process for lung cancer detection, and a novel technique entitled “Contour Detection Method” for identification of lung cancer nodules. We describe the various algorithms employed for each step of the diagnosis process. The implemented algorithms are tested for the Lung Image Database Consortium (LIDC) comprising of CT scan images in DICOM format. The experimentation results for the same dataset reveals that the proposed technique outperforms widely employed Local Density Maximum algorithm by detecting and classifying 7% of the observed false negatives.

Index Terms—Computer aided diagnosis, multi-sliced CT, lung cancer nodules, contour detection method, local density maximum.

N. Ejaz is with Intelligent Media Lab, Department of Digital Contents, Sejong University, Seoul, Korea, on leave from the National University of Computer and Emerging Sciences (NUCES aka FAST-NU), Islamabad, 44000 Pakistan(e-mail: naveed.ejaz@ nu.edu.pk).
S. Javed was with the National University of Computer and Emerging Sciences (NUCES aka FAST-NU), Islamabad, 44000 Pakistan. She is now with the Department of Computer Science, University of Tartu, Tartu, Estonia (e-mail: shazia.javed@ut.ee).
Z. Sajid was with the National University of Computer and Emerging Sciences (NUCES aka FAST-NU), Islamabad, 44000 Pakistan. He is now with EssClaims, Cambridge, UK (e-mail: zeeshan@essclaims.com).

[PDF]

Cite: Naveed Ejaz, Shazia Javed, and Zeeshan Sajid, "Implementation of Computer Aided Diagnosis System for Lung Cancer Detection," Lecture Notes on Software Engineering vol. 1, no. 4, pp. 364-369, 2013.

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