Algorithm Oriented to the Detection of the Level of Blood Filling in Venipuncture Tubes Based on Digital Image Processing
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Issue Date
2021-01-01Keywords
Blood drawDetection
Filling level
Image processing
Venipuncture tube
Image enhancement
Image segmentation
Pixels
Gamma correction
Pixels of interests
Metadata
Show full item recordJournal
Smart Innovation, Systems and TechnologiesDOI
10.1007/978-3-030-57566-3_1Additional Links
https://www.scopus.com/record/display.uri?eid=2-s2.0-85098193318&doi=10.1007%2f978-3-030-57566-3_1&origin=inward&txGid=0024ec4fa74e19a281c2d688d0a08978#Abstract
This article proposes an algorithm oriented to the detection of the level of blood filling in patients, with detection capacity in millimeters. The objective of the software is to detect the amount of blood stored into the venipuncture tube and avoid coagulation problems due to excess fluid. It also aims to avoid blood levels below that required, depending on the type of analysis to be performed. The algorithm acquires images from a camera positioned in a rectangular structure located within an enclosure, which has its own internal lighting to ensure adequate segmentation of the pixels of the region of interest. The algorithm consists of an image improvement stage based on gamma correction, followed by a segmentation stage of the area of pixels of interest, which is based on thresholding by HSI model, in addition to filtering to accentuate the contrast between the level of filling and staining, and as a penultimate stage, the location of the filling level due to changes in the vertical tonality of the image. Finally, the level of blood contained in the tube is obtained from the detection of the number of pixels that make up the vertical dimension of the tube filling. This number of pixels is then converted to physical dimensions expressed in millimeters. The validation results show an average percentage error of 0.96% by the proposed algorithm.Type
OtherLanguage
engDescription
El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.ISSN
21903018EISSN
21903026ae974a485f413a2113503eed53cd6c53
10.1007/978-3-030-57566-3_1
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