Color correction of baby images for cyanosis detection

Nur Fatihah Binti Azmi, Frank Delbressine, Loe Feijs, Sidarto Bambang Oetomo

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

4 Citaten (Scopus)
2 Downloads (Pure)


An accurate assessment of the bluish discoloration of cyanosis in the newborn baby’s skin is essential for the doctors when making a comprehensive evaluation or a treatment decision. To date, midwives employ the score of APGAR to note any occurrence of discoloration on skin among newborn babies. However, there is still no known general method to automatically determine a cyanosis skin color and quantifying technique in a newborn baby. Furthermore, a viable yardstick is absent for evaluation purposes in training sessions. Hence, this study proposes a cyanosis skin detection in the image of a newborn with a new algorithm for a color correction using MacBeth Color Checker. This proposed system has three steps: (i) selecting cyanosis region of interest from images, (ii) correcting color via an algorithm to calibrate images, and (iii) generating a database of cyanosis CIE L*a*b* (CIELAB) values. This proposed method calculates color error with ΔE* via comparing the actual color value of MacBeth Colorchecker especially before and after applying correction for color. This proposed method to detect cyanosis allows modification of images with minimal effect upon image quality, thus assuring the viability in detecting and ascertaining values of CIELAB for cyanosis skin. Besides, this study hopes to use the outcomes of CIELAB values of cyanosis skin in order to develop a baby manikin with cyanosis that is high in fidelity in upcoming studies. This study is not associated to clinical purposes.

Originele taal-2Engels
TitelMedical Image Understanding and Analysis - 22nd Conference, Proceedings
Subtitel22nd Conference, MIUA 2018, Southampton, UK, July 9-11, 2018, Proceedings
RedacteurenMark Nixon, Sasan Mahmoodi, Reyer Zwiggelaar
Plaats van productieCham
Aantal pagina's17
ISBN van elektronische versie978-3-319-95921-4
ISBN van geprinte versie978-3-319-95920-7
StatusGepubliceerd - 17 aug. 2018
Evenement22nd Conference on Medical Image Understanding and Analysis (MIUA 2018) - University of Southampton, Southampton, Verenigd Koninkrijk
Duur: 9 jul. 201811 jul. 2018

Publicatie series

NaamCommunications in Computer and Information Science
ISSN van geprinte versie1865-0929


Congres22nd Conference on Medical Image Understanding and Analysis (MIUA 2018)
Verkorte titelMIUA 2018
Land/RegioVerenigd Koninkrijk


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