@Article{FranciscoBlanco2014,
author="Francisco Blanco
and Felipe Lumbreras
and Joan Serrat
and Roswitha Siener
and Silvia Serranti
and Giuseppe Bonifazi
and Montserrat Lopez Mesas
and Manuel Valiente",
title="Taking advantage of Hyperspectral Imaging classification of urinary stones against conventional IR Spectroscopy",
journal="Journal of Biomedical Optics",
year="2014",
volume="19",
number="12",
pages="126004-1 - 126004-9",
abstract="The analysis of urinary stones is mandatory for the best management of the disease after the stone passage in order to prevent further stone episodes. Thus the use of an appropriate methodology for an individualized stone analysis becomes a key factor for giving the patient the most suitable treatment. A recently developed hyperspectral imaging methodology, based on pixel-to-pixel analysis of near-infrared spectral images, is compared to the reference technique in stone analysis, infrared (IR) spectroscopy. The developed classification model yields >90\% correct classification rate when compared to IR and is able to precisely locate stone components within the structure of the stone with a 15 {\textmu}m resolution. Due to the little sample pretreatment, low analysis time, good performance of the model, and the automation of the measurements, they become analyst independent; this methodology can be considered to become a routine analysis for clinical laboratories.",
optnote="ADAS; 600.076",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2563), last updated on Mon, 27 Jun 2016 17:46:07 +0200",
doi="10.1117/1.JBO.19.12.126004"
}