In this paper a differential geometry based method is proposed for calculating surface speculation of solitary pulmonary nodule (SPN) in 3D from lung CT images. Spiculation present in SPN is an important shape feature to assist radiologist for measurement of malignancy. Performance of Computer Aided Diagnostic (CAD) system depends on the accurate estimation of feature like spiculation. In the proposed method, the peak of the spicules is identified using the property of Gaussian and mean curvature calculated at each surface point on segmented SPN. Once the peak point for a particular SPN is identified, the nearest valley points for the corresponding peak point are determined. The area of cross-section of the best fitted plane passing through the valley points is the base of that spicule. The solid angle subtended by the base of spicule at peak point and the distance of peak point from nodule base are taken as the measures of spiculation. The speculation index (SI) for a particular SPN is the weighted combination of all the spicules present in that SPN. The proposed method is validated on 95 SPN from Imaging Database Resources Initiative (IDRI) public database. It has achieved 87.4% accuracy in calculating quantified spiculation index compared to the spiculation index provided by radiologists in IDRI database.

Date Published: 28 February 2013
PDF: 6 pages
Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 86700K (28 February 2013); doi: 10.1117/12.2006970

Published in SPIE Proceedings Vol. 8670:
Medical Imaging 2013: Computer-Aided Diagnosis
Carol L. Novak; Stephen Aylward, Editor(s)