@inproceedings{9071eabb1ca443609460fd635528a68c,
title = "Classification method for degree of lung adenocarcinoma differentiation",
abstract = "The number of fatalities from lung cancer accounts for 17% of that from all cancer, and is the highest ratio. Of them, the ratio of adenocarcinoma which has the highest ratio of lung cancer is increasing yearly. On the other hands, a classification of degree of differentiation is important to estimate prognosis, to determine the most suitable remedy and to investigate the relationship between smokers and patients of adenocarcinoma. Then we proposed new method for automatically classifying degree of adenocarcinoma differentiation. In this paper, we show the effectiveness of our method with results of classification.",
keywords = "case classification, image processing, lung cancer, neural network",
author = "Naoki Murakami and Toshiyuki Kanako and Toshiyuki Tanaka",
year = "2011",
language = "English",
isbn = "9784907764395",
series = "Proceedings of the SICE Annual Conference",
publisher = "Society of Instrument and Control Engineers (SICE)",
pages = "1501--1504",
booktitle = "SICE 2011 - SICE Annual Conference 2011, Final Program and Abstracts",
note = "50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011 ; Conference date: 13-09-2011 Through 18-09-2011",
}
