Classification of moving coronary calcified plaques based on motion artifacts using convolutional neural networks: a robotic simulating study on influential factors

Classification of moving coronary calcified plaques based on motion artifacts using convolutional neural networks: a robotic simulating study on influential factors

Abstract Background Motion artifacts affect the images of coronary calcified plaques. This study utilized convolutional neural networks (CNNs) to classify the motion-contaminated images of moving coronary calcified plaques and to determine the influential factors for the classification performance....

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Bibliographic Details
Main Authors: Magdalena Dobrolińska, Niels van der Werf, Marcel Greuter, Beibei Jiang, Riemer Slart, Xueqian Xie
Format: Article
Language:English
Published: BMC 2021-10-01
Series:BMC Medical Imaging
Subjects:
Artifacts
Artificial intelligence
Imaging phantoms
X-ray computed tomography
Online Access:https://doi.org/10.1186/s12880-021-00680-7

Internet

https://doi.org/10.1186/s12880-021-00680-7

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