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Automatic Raman spectroscopic urine crystal identification system using fluorescent image‐guided 2D scanning platform with Fe 3 O 4 crystal violet nanoclusters
Author(s) -
Lo PeiAn,
Huang YiHsiu,
Chiu YiChun,
Huang LiCi,
Bai JiaLun,
Wu ShuHan,
Huang ChihChia,
Chiang Huihua Kenny
Publication year - 2019
Publication title -
journal of raman spectroscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.748
H-Index - 110
eISSN - 1097-4555
pISSN - 0377-0486
DOI - 10.1002/jrs.5495
Subject(s) - urine , crystal (programming language) , raman spectroscopy , urinalysis , nanoclusters , chemistry , materials science , optics , nanotechnology , computer science , physics , biochemistry , programming language
Urolithiasis is a common urological disease with a very high recurrence rate, within 5 years. Urine stones are formed by urine crystals. Although the relationship between the composition of the urine stone and the type of urine crystal has been recognized, the efficient collection and accurate identification of the type of urine crystal in clinics remains a challenge. In this study, we develop an automatic Raman spectroscopic urine crystal collection and identification system. Custom‐developed Fe 3 O 4 crystal violet nanoclusters are used for (a) separating the urine crystals from the urine samples by a custom‐developed urine processing system and for (b) fluorescent labeling, image guiding, and the Raman spectroscopic measurement of the urine crystals on a 2D scanning stage. The control of the system and the Raman spectroscopic analysis are developed in a LabVIEW environment. This system is a fast and convenient method for the efficient collection and analysis of urinary crystals from urine samples, within 9 min. This automatic urine crystal identification system can enable the early prediction of the types of urine stones and the diet management for urolithiasis patients.