Paper
24 March 2016 Computer aided diagnosis for severity assessment of pneumoconiosis using CT images
Author Affiliations +
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.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hidenobu Suzuki, Mikio Matsuhiro, Yoshiki Kawata, Noboru Niki, Katsuya Kato, Takumi Kishimoto, and Kazuto Ashizawa "Computer aided diagnosis for severity assessment of pneumoconiosis using CT images", Proc. SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 978531 (24 March 2016); https://doi.org/10.1117/12.2217480
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Lung

Computer aided diagnosis and therapy

Computed tomography

Image segmentation

Chest

Computing systems

Quantitative analysis

Back to Top