Please use this identifier to cite or link to this item: 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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