3D Shape Analysis for Early Diagnosis of Malignant Lung Nodules

  • Ayman El-Baz
  • Matthew Nitzken
  • Ahmed Elnakib
  • Fahmi Khalifa
  • Georgy Gimel’farb
  • Robert Falk
  • Mohamed Abou El-Ghar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6893)

Abstract

An alternative method of diagnosing malignant lung nodules by their shape, rather than conventional growth rate, is proposed. The 3D surfaces of the detected lung nodules are delineated by spherical harmonic analysis that represents a 3D surface of the lung nodule supported by the unit sphere with a linear combination of special basis functions, called Spherical Harmonics (SHs). The proposed 3D shape analysis is carried out in five steps: (i) 3D lung nodule segmentation with a deformable 3D boundary controlled by a new prior visual appearance model; (ii) 3D Delaunay triangulation to construct a 3D mesh model of the segmented lung nodule surface; (iii) mapping this model to the unit sphere; (iv) computing the SHs for the surface; and (v) determining the number of the SHs to delineate the lung nodule. We describe the lung nodule shape complexity with a new shape index, the estimated number of the SHs, and use it for the K-nearest classification into malignant and benign lung nodules. Preliminary experiments on 327 lung nodules (153 malignant and 174 benign) resulted in a classification accuracy of 93.6%, showing that the proposed method is a promising supplement to current technologies for the early diagnosis of lung cancer.

Keywords

Unit Sphere Pulmonary Nodule Lung Nodule Malignant Nodule Benign Nodule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ayman El-Baz
    • 1
  • Matthew Nitzken
    • 1
  • Ahmed Elnakib
    • 1
  • Fahmi Khalifa
    • 1
  • Georgy Gimel’farb
    • 2
  • Robert Falk
    • 3
  • Mohamed Abou El-Ghar
    • 4
  1. 1.Bioimaging Laboratory, Bioengineering DepartmentUniversity of LouisvilleLouisvilleUSA
  2. 2.Department of Computer ScienceUniversity of AucklandAucklandNew Zealand
  3. 3.Department of RadiologyJewish HospitalLouisvilleUSA
  4. 4.Urology and Nephrology DepartmentUniversity of MansouraMansouraEgypt

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