DocumentCode
2612096
Title
Lungs Nodule Detection by Using Fuzzy Morphology from CT Scan Images
Author
Jaffar, M. Arfan ; Hussain, Ayyaz ; Mirza, Anwar M.
Author_Institution
Dept. of Comput. Sci., FAST Nat. Univ. of Comput. & Emerging Sci., Islamabad, Pakistan
fYear
2009
fDate
17-20 April 2009
Firstpage
57
Lastpage
61
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.
Keywords
computerised tomography; fuzzy logic; image segmentation; lung; medical image processing; 3D ROI image; CT scan images; automated segmentation; computed tomography; fuzzy morphology; lungs nodule detection; Cancer detection; Computed tomography; Computer science; Data mining; Entropy; Image segmentation; Lungs; Morphology; Shape; Springs; computer aided diagnosis; mathematical morphology; segmentation;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Technology - Spring Conference, 2009. IACSITSC '09. International Association of
Conference_Location
Singapore
Print_ISBN
978-0-7695-3653-8
Type
conf
DOI
10.1109/IACSIT-SC.2009.89
Filename
5169310
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