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http://hdl.handle.net/10553/77069
Title: | Novel Methodology for Alzheimer's Disease Biomarker Identification in Plasma using Hyperspectral Microscopy | Authors: | Fabelo Gómez, Himar Antonio León Martín, Sonia Raquel Ortega Sarmiento, Samuel Balea Fernández, Francisco Javier Bilbao Sieyro, Cristina Marrero Callicó, Gustavo Iván Wägner, Anna Maria Claudia |
UNESCO Clasification: | 32 Ciencias médicas 320507 Neurología 320711 Neuropatología |
Keywords: | Alzheimer'S Disease Early Diagnosis Hyperspectral Microscopy Neurocognitive Disorders Spectral Unmixing |
Issue Date: | 2020 | Publisher: | Institute of Electrical and Electronics Engineers (IEEE) | Conference: | 35th Conference on Design of Circuits and Integrated Systems - DCIS 2020 | Abstract: | Alzheimer's disease (AD) is a gradually progressive neurocognitive disorder (NCD) with a preclinical phase where the patient can be asymptomatic for many years. The detection of AD in its earliest stages is one of the most active areas in Alzheimer's science. This early diagnosis could potentially allow for early intervention and improved prognosis, once effective treatment is available. This paper proposes a novel methodology based on spectral unmixing for the identification of biomarkers in plasma samples using visual and near infrared (VNIR) hyperspectral microscopy (HSM). The study was performed using ten drop plasma samples from 10 patients (5 control and 5 case subjects affected by NCD) captured with HSM at two different magnifications: 5× and 20×. This data was processed, and a statistical analysis of the abundance estimation was performed to identify relevant endmembers to differentiate case and control groups. The results suggest the potential of HSM and plasma samples as a cost-effective early diagnosis tool. | URI: | http://hdl.handle.net/10553/77069 | ISBN: | 9781728191324 | DOI: | 10.1109/DCIS51330.2020.9268654 | Source: | 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS) |
Appears in Collections: | Actas de congresos |
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