ArticleComputational and mathematical methods in medicine2020
Detection of Solitary Pulmonary Nodules Based on Brain-Computer Interface.
Article in Computational and mathematical methods in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Alzheimer's Disease Analysis Algorithm Based on No-threshold Recurrence Plot Convolution Network.Frontiers in aging neuroscience · 2022Article
- A Pulmonary Nodule Spiculation Recognition Algorithm Based on Generative Adversarial Networks.BioMed research international · 2022Article
- MRI Image Segmentation Model with Support Vector Machine Algorithm in Diagnosis of Solitary Pulmonary Nodule.Contrast media & molecular imaging · 2021Article
- Algorithm of Pulmonary Vascular Segment and Centerline Extraction.Computational and mathematical methods in medicine · 2021Article
- Spiculation Sign Recognition in a Pulmonary Nodule Based on Spiking Neural P Systems.BioMed research international · 2020Article
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Authors and funding
6 authors.
Funding
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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.
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