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PET/CT 画像における Convolutional neural network と

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THE INSTITUTE OF ELECTRONICS,
INFORMATION AND COMMUNICATION ENGINEERS
E-mail:
PET/CT,
,
IEICE Technical Report
[email protected]
,
,
Improved scheme of automated detection of pulmonary nodules
in PET/CT images using convolutional neural network
and conventional characteristic features
Atsushi TERAMOTO
Hiroshi FUJITA
Osamu YAMAMURO
and
Tsuneo TAMAKI
Faculty of Radiological Technology, School of Health Sciences, Fujita Health University
1-98 Dengakugakubo, Kutsukake-cho, Toyoake Aichi, 470-1192 Japan
Department of Intelligent Image Information, Graduate School of Medicine, Gifu University
1-1 Yanagido, Gifu, 501-1194 Japan
East Nagoya Imaging Diagnosis Center, 3-4-26 Jiyugaoka, Chikusa-ku, Nagoya, Aichi, 464-0044 Japan
E-mail:
[email protected]
Abstract In the existing method for automated detection of pulmonary nodules in PET/CT images, false positives (FPs)
are eliminated by the combination of shape feature extraction and classifier. In this study, we develop an improved scheme of
automated detection of pulmonary nodules by adding the convolutional neural network (CNN). The proposed scheme detects
pulmonary nodules using both CT and PET images. In the CT images, a massive region is first detected using an active contour
filter that we developed so far. Subsequently, high-uptake regions detected by the PET images. FP candidates are eliminated
using shape features and CNN output, followed by two support vector machines. In the experiments, we evaluated the
detection capability using 104 cases of PET/CT images. As a result, the proposed method eliminated approximately half the
FPs existing in the previous study.
Keywords PET/CT, pulmonary nodule, computer-aided detection, deep learning, convolutional neural network
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This
article is a technical report without peer review, and its polished and/or extended version may be published elsewhere.
This article is a technical report without peer review, and its polished and/or extended version may be published elsewhere.
Copyright©201
©20 6 by byIEICE
IEICE
Copyright
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