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Detection of pulmonary nodules on chest x-ray images using R-CNN
Author(s): R. Takemiya; S. Kido; Y. Hirano; S. Mabu
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Paper Abstract

Burdens of doctors for chest X-ray (CXR) examination have increased because number of X-ray images increases. Furthermore, since diagnosis is based on the experience and subjectivity of them, there is a possibility that a misdiagnosis may occur. Therefore, we performed Computer-Aided Diagnosis (CAD). In this study, we detected pulmonary nodules using R-CNN (Region with Convolutional Neural Network)[1] which is a kind of Deep Learning. First, we created CNN (Convolutional Neural Network) which classified data into classes of nodule opacities and nonnodule opacities. Next, we detected the object candidate regions from the chest X-ray images by Selective Search[2], and applied the CNN to the candidate regions to classify them and estimate the detailed position of the object. Thus, we propose a method to detect pulmonary nodules from the chest X-ray images.

Paper Details

Date Published: 27 March 2019
PDF: 6 pages
Proc. SPIE 11050, International Forum on Medical Imaging in Asia 2019, 110500W (27 March 2019); doi: 10.1117/12.2521652
Show Author Affiliations
R. Takemiya, Yamaguchi Univ. (Japan)
S. Kido, Yamaguchi Univ. (Japan)
Y. Hirano, Yamaguchi Univ. (Japan)
S. Mabu, Yamaguchi Univ. (Japan)


Published in SPIE Proceedings Vol. 11050:
International Forum on Medical Imaging in Asia 2019
Feng Lin; Hiroshi Fujita; Jong Hyo Kim, Editor(s)

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