Paper Info
Title
Computer aided diagnosis for severity assessment of pneumoconiosis using CT images.
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.
Year
DOI
Venue
2016
10.1117/12.2217480
Proceedings of SPIE
Keywords
Field
DocType
pneumoconiosis,computed tomography,computer aided diagnosis
Computer vision,Pneumoconiosis,Lung,Rib cage,Computer-aided diagnosis,Computer aided detection,Radiography,Artificial intelligence,Radiology,Quantitative assessment,Stage (cooking),Physics
Conference
Volume
ISSN
Citations 
9785
0277-786X
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
hajime suzuki122.39
mikio matsuhiro254.05
Yoshiki Kawata319254.44
Noboru Niki418866.10
Katsuya Kato501.35
Takumi Kishimoto600.34
K Ashizawa7358.11