Title :
Classification of pulmonary nodules in thin-section CT images based on shape characterization
Author :
Kawata, Y. ; Niki, N. ; Ohmatsu, H. ; Kakinuma, R. ; Eguchi, K. ; Kaneko, M. ; Moriyama, N.
Author_Institution :
Fac. of Eng., Tokushima Univ., Japan
Abstract :
Shape characterization of small pulmonary nodules plays a significant role in differential diagnosis that discriminates malignant and benign nodules at early stages of pulmonary lesion development. This paper presents a method to characterize small pulmonary nodules based on the morphology of the development of lung lesions in thin-section CT images. The feature extraction algorithms are designed to extract the shape characteristic parameters from three-dimensional (3-D) nodule images using surface curvatures and ridge line. Experiments which show the feasibility of our method to improve the diagnostic accuracy are also demonstrated by applying the method to nodule images
Keywords :
computerised tomography; diagnostic radiography; feature extraction; image classification; image reconstruction; lung; medical image processing; 3D nodule images; benign nodules; diagnostic accuracy; differential diagnosis; experiments; feature extraction algorithms; lung lesions; malignant nodules; morphology; pulmonary lesion; pulmonary nodules classification; ridge line; shape characterization; surface curvatures; thin-section CT images; Biomedical imaging; Blood vessels; Cancer; Computed tomography; Feature extraction; Lesions; Lungs; Morphology; Respiratory system; Shape;
Conference_Titel :
Image Processing, 1997. Proceedings., International Conference on
Conference_Location :
Santa Barbara, CA
Print_ISBN :
0-8186-8183-7
DOI :
10.1109/ICIP.1997.632174