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Detection of Solitary Pulmonary Nodules Based on Brain-Computer Interface

Solitary pulmonary nodules are the main manifestation of pulmonary lesions. Doctors often make diagnosis by observing the lung CT images. In order to further study the brain response structure and construct a brain-computer interface, we propose an isolated pulmonary nodule detection model based on...

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Detalles Bibliográficos
Autores principales: Qiu, Shi, Li, Junjun, Cong, Mengdi, Wu, Chun, Qin, Yan, Liang, Ting
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7312740/
https://www.ncbi.nlm.nih.gov/pubmed/32617117
http://dx.doi.org/10.1155/2020/4930972
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author Qiu, Shi
Li, Junjun
Cong, Mengdi
Wu, Chun
Qin, Yan
Liang, Ting
author_facet Qiu, Shi
Li, Junjun
Cong, Mengdi
Wu, Chun
Qin, Yan
Liang, Ting
author_sort Qiu, Shi
collection PubMed
description Solitary pulmonary nodules are the main manifestation of pulmonary lesions. Doctors often make diagnosis by observing the lung CT images. In order to further study the brain response structure and construct a brain-computer interface, we propose an isolated pulmonary nodule detection model based on a brain-computer interface. First, a single channel time-frequency feature extraction model is constructed based on the analysis of EEG data. Second, a multilayer fusion model is proposed to establish the brain-computer interface by connecting the brain electrical signal with a computer. Finally, according to image presentation, a three-frame image presentation method with different window widths and window positions is proposed to effectively detect the solitary pulmonary nodules.
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spelling pubmed-73127402020-07-01 Detection of Solitary Pulmonary Nodules Based on Brain-Computer Interface Qiu, Shi Li, Junjun Cong, Mengdi Wu, Chun Qin, Yan Liang, Ting Comput Math Methods Med Research Article Solitary pulmonary nodules are the main manifestation of pulmonary lesions. Doctors often make diagnosis by observing the lung CT images. In order to further study the brain response structure and construct a brain-computer interface, we propose an isolated pulmonary nodule detection model based on a brain-computer interface. First, a single channel time-frequency feature extraction model is constructed based on the analysis of EEG data. Second, a multilayer fusion model is proposed to establish the brain-computer interface by connecting the brain electrical signal with a computer. Finally, according to image presentation, a three-frame image presentation method with different window widths and window positions is proposed to effectively detect the solitary pulmonary nodules. Hindawi 2020-06-15 /pmc/articles/PMC7312740/ /pubmed/32617117 http://dx.doi.org/10.1155/2020/4930972 Text en Copyright © 2020 Shi Qiu et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Qiu, Shi
Li, Junjun
Cong, Mengdi
Wu, Chun
Qin, Yan
Liang, Ting
Detection of Solitary Pulmonary Nodules Based on Brain-Computer Interface
title Detection of Solitary Pulmonary Nodules Based on Brain-Computer Interface
title_full Detection of Solitary Pulmonary Nodules Based on Brain-Computer Interface
title_fullStr Detection of Solitary Pulmonary Nodules Based on Brain-Computer Interface
title_full_unstemmed Detection of Solitary Pulmonary Nodules Based on Brain-Computer Interface
title_short Detection of Solitary Pulmonary Nodules Based on Brain-Computer Interface
title_sort detection of solitary pulmonary nodules based on brain-computer interface
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7312740/
https://www.ncbi.nlm.nih.gov/pubmed/32617117
http://dx.doi.org/10.1155/2020/4930972
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