title: 3D shape analysis for early diagnosis of malignant lung nodules.
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.
authors: Bioimaging Laboratory, Bioengineering Department, University of Louisville, Louisville, KY, USA. aselba01@louisville.edu
authors: Ayman
authors: A
authors: El-Baz
authors: Matthew
authors: M
authors: Nitzken
authors: Ahmed
authors: A
authors: Elnakib
authors: Fahmi
authors: F
authors: Khalifa
authors: Georgy
authors: G
authors: Gimel'farb
authors: Robert
authors: R
authors: Falk
authors: Mohamed Abou
authors: MA
authors: El-Ghar
mesh_terms: D000465:Algorithms; D055088:Early Detection of Cancer; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008168:Lung / Q000473:pathology; D008175:Lung Neoplasms / Q000175:diagnosis*; D008495:Medical Oncology / Q000379:methods; D015233:Models, Statistical; D012372:ROC Curve; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D003074:Solitary Pulmonary Nodule / Q000175:diagnosis*