Multivariate analysis of dual-point amyloid PET intended to assist the diagnosis of Alzheimer’s disease
| العنوان: | Multivariate analysis of dual-point amyloid PET intended to assist the diagnosis of Alzheimer’s disease |
|---|---|
| المؤلفون: | Manuel Gómez-Río, Diego Castillo-Barnes, Christophe Phillips, Diego Salas-Gonzalez, Javier Ramírez, J. M. Gorriz, Yudong Zhang, Fermín Segovia, Pablo Sopena-Novales |
| المساهمون: | [Segovia, F.] Univ Granada, Dept Signal Theory Networking & Commun, Granada, Spain, [Ramirez, J.] Univ Granada, Dept Signal Theory Networking & Commun, Granada, Spain, [Castillo-Barnes, D.] Univ Granada, Dept Signal Theory Networking & Commun, Granada, Spain, [Salas-Gonzalez, D.] Univ Granada, Dept Signal Theory Networking & Commun, Granada, Spain, [Gorriz, J. M.] Univ Granada, Dept Signal Theory Networking & Commun, Granada, Spain, [Gomez-Rio, M.] Virgen Las Nieves Univ Hosp, Dept Nucl Med, Granada, Spain, [Sopena-Novales, P.] 9 Octubre Hosp, Dept Nucl Med, Valencia, Spain, [Phillips, C.] Univ Liege, Cyclotron Res Ctr, Liege, Belgium, [Zhang, Y.] Univ Leicester, Dept Informat, Leicester, Leics, England, MINECO/FEDER |
| المصدر: | Neurocomputing. 417:1-9 |
| بيانات النشر: | Elsevier BV, 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | 0209 industrial biotechnology, Support vector machine, Multivariate analysis, Amyloid, Computer science, Cognitive Neuroscience, Amyloid pet, Ad, 02 engineering and technology, Disease, 020901 industrial engineering & automation, Partial least squares, Artificial Intelligence, 0202 electrical engineering, electronic engineering, information engineering, medicine, Partial least-squares, Multimodal systems, Amyloid PET imaging, Multiple kernel learning, medicine.diagnostic_test, Point (typography), business.industry, Dimensionality reduction, Pattern recognition, Biomarker, Alzheimer's disease, DUAL (cognitive architecture), Classification, Sensor fusion, Computer Science Applications, Computer aided diagnosis, Late fusion, Positron emission tomography, Images, 020201 artificial intelligence & image processing, Artificial intelligence, business, Mri |
| الوصف: | Several studies have recently suggested that amyloid Positron Emission Tomography (PET) data acquired immediately after the radiotracer injection provide information related to the brain metabolism, similar to that contained in 18 F-Fluorodeoxyglucose (FDG) PET neuroimages. If corroborated, it would allow us to acquire information about brain injury and potential brain amyloid deposits in a single examination, using a dual-point protocol. In this work we assess the equivalence between early 18 F-Florbetaben (FBB) PET and 18 F-FDG PET data using multivariate approaches based on machine learning. In addition, we propose several systems based on data fusion that take advantage of the additional information provided by dual-point amyloid PET examinations. The proposed systems perform an initial dimensionality reduction of the data using a partial-least-square-based algorithm and then combine early and standard PET acquisitions using two approaches: multiple kernel learning (intermediate fusion) or an ensemble of two Support Vector Machine classifiers (late fusion). The proposed approaches were evaluated and compared with other fusion techniques using data from 43 subjects with cognitive impairments. They achieved a good trade-off between sensitivity and specificity and higher accuracy rates than systems based on single-modality approaches such as standard 18 F-FBB PET data or 18 F-FDG PET neuroimages. |
| تدمد: | 0925-2312 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c82c0acb0f767acac0a875b223e6bdf https://doi.org/10.1016/j.neucom.2020.06.081 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....3c82c0acb0f767acac0a875b223e6bdf |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 09252312 |
|---|