@inproceedings{29a506ee22e143c1b894b4205876c544,
title = "Case classification of pulmonary emphysema using shape and distribution of lesions",
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 = "CT image, Case classification, Low attenuation area, Neural network",
author = "Shotaro Yoshie and Toshiyuki Tanaka and Toru Shirahata and Hiroaki Sugiura",
year = "2010",
month = jan,
day = "1",
language = "English",
isbn = "9784907764364",
series = "Proceedings of the SICE Annual Conference",
publisher = "Society of Instrument and Control Engineers (SICE)",
pages = "1042--1045",
booktitle = "Proceedings of SICE Annual Conference 2010, SICE 2010 - Final Program and Papers",
}