Computer-aided diagnosis for pulmonary nodules based on helical CT images.
In this paper, we present a computer-assisted automatic diagnostic system for lung cancer that detects nodule candidates at an early stage from helical CT images of the thorax. Our diagnostic system consists of analytical and diagnostic procedures. In the analytical procedure, first we extract the lung and the pulmonary blood vessel regions using the fuzzy clustering algorithm, then we analyze the features of these regions using image-processing techniques. In the diagnostic procedure, we define diagnostic rules utilizing the extracted features which support the determination of the candidate nodule locations. We show the effectiveness of our system by giving the results from its application to image data for mass screening of 450 patients.
Department of Optical Science, University of Tokushima, Japan.
K
K
Kanazawa
Y
Y
Kawata
N
N
Niki
H
H
Satoh
H
H
Ohmatsu
R
R
Kakinuma
M
M
Kaneko
N
N
Moriyama
K
K
Eguchi
D000465:Algorithms; D003936:Diagnosis, Computer-Assisted; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008168:Lung / Q000000981:diagnostic imaging*; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D011857:Radiographic Image Interpretation, Computer-Assisted; D014057:Tomography, X-Ray Computed