@article {233,
	title = {Extraction of features for diagnosing pneumoconiosis from chest radiographs obtained with a CCD scanner},
	journal = {Journal of Digital Information Management},
	volume = {8},
	year = {2010},
	note = {Cited By (since 1996):2Export Date: 10 July 2014},
	month = {2010},
	pages = {147 - 152},
	abstract = {This paper presents a computer-aided diagnosis for pneumoconiosis radiographs obtained with a common CCD scanner. Since the existing diagnosis systems for pneumo coniosis extract abnormalities of pneumoconiosis from im ages obtained with a special scanner which can appropri-ately-apply-for-chest- radiographs,-it-is-difficult-toapply the systems to images obtained with a CCD scanner due to un clear shadow and the systems are not practical for medical doctors due to high costs. In the unclear images, the ab normal levels of pneumoconiosis could depend on density distribution in each of intercostal and rib areas. Therefore, the proposed method measures the abnormalities by extract ing characteristics of the distribution in the areas. Besides, using the-abnormalities,-the-proposed-method-classifies-the-imagesinto the three categories of pneumoconiosis. Exper imental results-of-the-classifications-for- 51-right-lung-im-ages-including 6 pneumoconiosis images have shown that the proposed abnormalities are well extracted according to the standards of pneumoconiosis categories.},
	keywords = {Chest radiographs, Computer-aided diagnosis, Medical image processing, Pneumoconiosis},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-79960677554\&partnerID=40\&md5=95072c54ff5968028fd8e2985166c663},
	author = {Nakamura, M. and Abe, K. and Minami, M.}
}
