id: 05835218
dt: j
an: 05835218
au: Jaffar, M.Arfan; Hussain, Ayyaz; Mirza, Anwar Majid
ti: Fuzzy entropy based optimization of clusters for the segmentation of lungs
    in CT scanned images.
so: Knowl. Inf. Syst. 24, No. 1, 91-111 (2010).
py: 2010
pu: Springer, London
la: EN
cc: 
ut: computer aided diagnosis; mathematical morphology; segmentation;
    thresholding
ci: 
li: doi:10.1007/s10115-009-0225-z
ab: Summary: We have proposed a method for segmentation of lungs from Computed
    Tomography (CT)-scanned images using spatial Fuzzy C-Mean and
    morphological techniques known as Fuzzy Entropy and Morphology based
    Segmentation. To determine dynamic and adaptive optimal threshold, we
    have incorporated Fuzzy Entropy. We have proposed a novel
    histogram-based background removal operator. The proposed system is
    capable to perform fully automatic segmentation of CT Scan Lung images,
    based solely on information contained by the image itself. We have used
    different cluster validity functions to find out optimal number of
    clusters. The proposed system can be used as a basic building block for
    Computer-Aided Diagnosis. The technique was tested against the 25
    datasets of different patients received from Aga Khan Medical
    University, Pakistan. The results confirm the validity of technique as
    well as enhanced performance.
rv: