Fast lung nodule detection in chest CT images using cylindrical nodule-enhancement filter.
OBJECTIVE
Existing computer-aided detection schemes for lung nodule detection require a large number of calculations and tens of minutes per case; there is a large gap between image acquisition time and nodule detection time. In this study, we propose a fast detection scheme of lung nodule in chest CT images using cylindrical nodule-enhancement filter with the aim of improving the workflow for diagnosis in CT examinations.


METHODS
Proposed detection scheme involves segmentation of the lung region, preprocessing, nodule enhancement, further segmentation, and false-positive (FP) reduction. As a nodule enhancement, our method employs a cylindrical shape filter to reduce the number of calculations. False positives (FPs) in nodule candidates are reduced using support vector machine and seven types of characteristic parameters.


RESULTS
The detection performance and speed were evaluated experimentally using Lung Image Database Consortium publicly available image database. A 5-fold cross-validation result demonstrates that our method correctly detects 80 % of nodules with 4.2 FPs per case, and detection speed of proposed method is also 4-36 times faster than existing methods.


CONCLUSIONS
Detection performance and speed indicate that our method may be useful for fast detection of lung nodules in CT images.
Faculty of Radiological Technology, School of Health Sciences, Fujita Health University, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake-city, Aichi 470-1192, Japan. teramoto@fujita-hu.ac.jp
Atsushi
A
Teramoto
Hiroshi
H
Fujita
D003936:Diagnosis, Computer-Assisted; D006801:Humans; D021621:Imaging, Three-Dimensional; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000295:instrumentation*; D012984:Software; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed