Title :
Case classification of pulmonary emphysema using shape and distribution of lesions
Author :
Yoshie, Shotaro ; Tanaka, Toshiyuki ; Shirahata, Toru ; Sugiura, Hiroaki
Author_Institution :
Dept. of Appl. Phys. & Physico-Inf., Keio Univ., Yokohama, Japan
Abstract :
Pulmonary emphysema is a kind of lung disease and doctors diagnose it referring to the lung CT images findings in. Therefore computer aided diagnosis by image processing is very useful from the quantitative and objective points of view. In this study, we focused on shape and distribution of the area of lesions in the lung CT images, and propose a method for the classification of three kinds of pulmonary emphysema. We calculated five features to classify the emphysema types. Finally, we will classify emphysema by using those features and neural network in the feature work.
Keywords :
computerised tomography; diseases; feature extraction; image classification; lung; medical diagnostic computing; medical image processing; neural nets; patient diagnosis; computer aided diagnosis; feature work; image processing; lesion distribution; lesion shape; lung CT image; lung disease; neural network; pulmonary emphysema; Computed tomography; Feature extraction; Lesions; Lungs; Medical diagnostic imaging; Shape; CT image; case classification; low attenuation area; neural network;
Conference_Titel :
SICE Annual Conference 2010, Proceedings of
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-7642-8