Hyperspectral imaging based method for fast characterization of kidney stone types

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F12%3A00107018" target="_blank" >RIV/00216224:14310/12:00107018 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.spiedigitallibrary.org/journals/journal-of-biomedical-optics/volume-17/issue-7/076027/Hyperspectral-imaging-based-method-for-fast-characterization-of-kidney-stone/10.1117/1.JBO.17.7.076027.full?SSO=1" target="_blank" >https://www.spiedigitallibrary.org/journals/journal-of-biomedical-optics/volume-17/issue-7/076027/Hyperspectral-imaging-based-method-for-fast-characterization-of-kidney-stone/10.1117/1.JBO.17.7.076027.full?SSO=1</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1117/1.JBO.17.7.076027" target="_blank" >10.1117/1.JBO.17.7.076027</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Hyperspectral imaging based method for fast characterization of kidney stone types

Popis výsledku v původním jazyce

The formation of kidney stones is a common and highly studied disease, which causes intense pain and presents a high recidivism. In order to find the causes of this problem, the characterization of the main compounds is of great importance. In this sense, the analysis of the composition and structure of the stone can give key information about the urine parameters during the crystal growth. But the usual methods employed are slow, analyst dependent and the information obtained is poor. In the present work, the near infrared (NIR)-hyperspectral imaging technique was used for the analysis of 215 samples of kidney stones, including the main types usually found and their mixtures. The NIR reflectance spectra of the analyzed stones showed significant differences that were used for their classification. To do so, a method was created by the use of artificial neural networks, which showed a probability higher than 90% for right classification of the stones. The promising results, robust methodology, and the fast analytical process, without the need of an expert assistance, lead to an easy implementation at the clinical laboratories, offering the urologist a rapid diagnosis that shall contribute to minimize urolithiasis recidivism.

Název v anglickém jazyce

Hyperspectral imaging based method for fast characterization of kidney stone types

Popis výsledku anglicky

The formation of kidney stones is a common and highly studied disease, which causes intense pain and presents a high recidivism. In order to find the causes of this problem, the characterization of the main compounds is of great importance. In this sense, the analysis of the composition and structure of the stone can give key information about the urine parameters during the crystal growth. But the usual methods employed are slow, analyst dependent and the information obtained is poor. In the present work, the near infrared (NIR)-hyperspectral imaging technique was used for the analysis of 215 samples of kidney stones, including the main types usually found and their mixtures. The NIR reflectance spectra of the analyzed stones showed significant differences that were used for their classification. To do so, a method was created by the use of artificial neural networks, which showed a probability higher than 90% for right classification of the stones. The promising results, robust methodology, and the fast analytical process, without the need of an expert assistance, lead to an easy implementation at the clinical laboratories, offering the urologist a rapid diagnosis that shall contribute to minimize urolithiasis recidivism.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10608 - Biochemistry and molecular biology

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2012

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Biomedical Optics

ISSN

1083-3668

e-ISSN

1560-2281

Svazek periodika

17

Číslo periodika v rámci svazku

7

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

13

Strana od-do

1-13

Kód UT WoS článku

000307989500054

EID výsledku v databázi Scopus

2-s2.0-84873539080