Improved computer-aided detection of pulmonary nodules via deep learning in the sinogram domain

Computer aided detection (CADe) of pulmonary nodules plays an important role in assisting radiologists’ diagnosis and alleviating interpretation burden for lung cancer. Current CADe systems, aiming at simulating radiologists’ examination procedure, are built upon computer tomography (CT) images with...

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Bibliographic Details
Published in:	Visual computing for industry, biomedicine and art Vol. 2; no. 1; pp. 15 - 9
Main Authors:	Gao, Yongfeng, Tan, Jiaxing, Liang, Zhengrong, Li, Lihong, Huo, Yumei
Format:	Journal Article
Language:	English
Published:	Singapore Springer Singapore 22-11-2019 Springer Nature B.V SpringerOpen
Subjects:	Annotations Artificial neural networks CAE) and Design Computed tomography Computer Graphics Computer Imaging Computer Science Computer simulation Computer-aided detection Computer-Aided Engineering (CAD Consortia Data acquisition Deep learning Diagnosis Domains Feature extraction Image acquisition Image detection Image Processing and Computer Vision Image reconstruction Lung Machine learning Media Design Medical imaging Medical Imaging Modeling Nodules Original Original Article Pattern Recognition and Graphics Sinogram Vision Visual perception Deep learning Computed tomography Computer-aided detection Lung Sinogram
Online Access:	Get full text
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