Classifying pulmonary nodules using dynamic enhanced single slice and multi slice CT images

Kazuhiro Minami; Yoshiki Kawata; Noboru Niki; Hironobu Ohmatsu; Masahiko Kusumoto; Kouzou Yamada; Ryuutaro Kakinuma D.D.S.; Kenji Eguchi; Kiyoshi Mori; Masahiro Kaneko; Noriyuki Moriyama

doi:10.1117/12.654683

13 March 2006 Classifying pulmonary nodules using dynamic enhanced single slice and multi slice CT images

Kazuhiro Minami, Yoshiki Kawata, Noboru Niki, Hironobu Ohmatsu, Masahiko Kusumoto, Kouzou Yamada, Ryuutaro Kakinuma D.D.S., Kenji Eguchi, Kiyoshi Mori, Masahiro Kaneko, Noriyuki Moriyama

Author Affiliations +

Proceedings Volume 6143, Medical Imaging 2006: Physiology, Function, and Structure from Medical Images; 614334 (2006) https://doi.org/10.1117/12.654683
Event: Medical Imaging, 2006, San Diego, California, United States

Abstract

Pulmonary nodules are classified into three types such as solid, mixed GGO, and pure GGO types on the basis of the visual assessment of CT appearance. In our current study a quantitative classification algorithm has been developed by using volumetric data sets obtained from thin-section CT images. The algorithm can classify the pulmonary nodules into five types (α, β, γ, δ, and ε) on the basis of internal features extracted from CT number histograms inside nodules. We applied dynamic enhanced single slice and multi slice CT images to this classification algorithm and we analyzed it in each type.

Citation Download Citation

Kazuhiro Minami, Yoshiki Kawata, Noboru Niki, Hironobu Ohmatsu, Masahiko Kusumoto, Kouzou Yamada, Ryuutaro Kakinuma D.D.S., Kenji Eguchi, Kiyoshi Mori, Masahiro Kaneko, and Noriyuki Moriyama "Classifying pulmonary nodules using dynamic enhanced single slice and multi slice CT images", Proc. SPIE 6143, Medical Imaging 2006: Physiology, Function, and Structure from Medical Images, 614334 (13 March 2006); https://doi.org/10.1117/12.654683

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available