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Lungs Nodule Detection by Using Fuzzy Morphology from CT Scan Images

Published: 17 April 2009 Publication History

Abstract

In this paper we have proposed a method for lungs nodule detection from computed tomography (CT) scanned images by using Fuzzy C-Mean (FCM) and morphological techniques. First of all, fuzzy have been used for automated segmentation of lungs. Region of interests (ROIs) have been extracted by using 8 directional searches slice by slice and then 3D ROI image have been constructed. A 3D template has been constructed and convolves with the 3D ROI image. Finally FCM have been used to extract ROI that contain nodule. The proposed system is capable to perform fully automatic segmentation and nodule detection from CT Scan Lungs images, based solely on information contained by the image itself. The technique was tested against the 50 datasets of different patients received from Aga Khan Medical University, Pakistan and Lung Image Database Consortium (LIDC) dataset.
  1. Lungs Nodule Detection by Using Fuzzy Morphology from CT Scan Images

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    Published In

    cover image Guide Proceedings
    IACSIT-SC '09: Proceedings of the 2009 International Association of Computer Science and Information Technology - Spring Conference
    April 2009
    603 pages
    ISBN:9780769536538

    Publisher

    IEEE Computer Society

    United States

    Publication History

    Published: 17 April 2009

    Author Tags

    1. computer aided diagnosis
    2. mathematical morphology
    3. segmentation

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