Detection of Solitary Pulmonary Nodules Based on Brain-Computer Interface. (15th June 2020)
- Record Type:
- Journal Article
- Title:
- Detection of Solitary Pulmonary Nodules Based on Brain-Computer Interface. (15th June 2020)
- Main Title:
- Detection of Solitary Pulmonary Nodules Based on Brain-Computer Interface
- Authors:
- Qiu, Shi
Li, Junjun
Cong, Mengdi
Wu, Chun
Qin, Yan
Liang, Ting - Other Names:
- Huang Chenxi Guest Editor.
- Abstract:
- Abstract : 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.
- Is Part Of:
- Computational and mathematical methods in medicine. Volume 2020(2020)
- Journal:
- Computational and mathematical methods in medicine
- Issue:
- Volume 2020(2020)
- Issue Display:
- Volume 2020, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 2020
- Issue:
- 2020
- Issue Sort Value:
- 2020-2020-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-06-15
- Subjects:
- Medicine -- Computer simulation -- Periodicals
Medicine -- Mathematical models -- Periodicals
610.11 - Journal URLs:
- https://www.hindawi.com/journals/cmmm/ ↗
- DOI:
- 10.1155/2020/4930972 ↗
- Languages:
- English
- ISSNs:
- 1748-670X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3390.573000
British Library HMNTS - ELD Digital store - Ingest File:
- 14293.xml