Share Email Print

Proceedings Paper

Computer aided diagnosis for severity assessment of pneumoconiosis using CT images
Author(s): Hidenobu Suzuki; Mikio Matsuhiro; Yoshiki Kawata; Noboru Niki; Katsuya Kato; Takumi Kishimoto; Kazuto Ashizawa
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

240,000 participants have a screening for diagnosis of pneumoconiosis every year in Japan. Radiograph is used for staging of severity in pneumoconiosis worldwide. This paper presents a method for quantitative assessment of severity in pneumoconiosis using both size and frequency of lung nodules that detected by thin-section CT images. This method consists of three steps. First, thoracic organs (body, ribs, spine, trachea, bronchi, lungs, heart, and pulmonary blood vessels) are segmented. Second, lung nodules that have radius over 1.5mm are detected. These steps used functions of our developed computer aided detection system of chest CT images. Third, severity in pneumoconiosis is quantified using size and frequency of lung nodules. This method was applied to nine pneumoconiosis patients. The initial results showed that proposed method can assess severity in pneumoconiosis quantitatively. This paper demonstrates effectiveness of our method in diagnosis and prognosis of pneumoconiosis in CT screening.

Paper Details

Date Published: 24 March 2016
PDF: 6 pages
Proc. SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 978531 (24 March 2016); doi: 10.1117/12.2217480
Show Author Affiliations
Hidenobu Suzuki, The Univ. of Tokushima (Japan)
Mikio Matsuhiro, The Univ. of Tokushima (Japan)
Yoshiki Kawata, The Univ. of Tokushima (Japan)
Noboru Niki, The Univ. of Tokushima (Japan)
Katsuya Kato, Kawasaki Medical School (Japan)
Takumi Kishimoto, Okayama Rosai Hospital (Japan)
Kazuto Ashizawa, Nagasaki Univ. (Japan)

Published in SPIE Proceedings Vol. 9785:
Medical Imaging 2016: Computer-Aided Diagnosis
Georgia D. Tourassi; Samuel G. Armato III, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?