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Annotation of the Medical Images Using Quick Response Codes

Girūta Kazakevičiūtė–Januškevičienė¹, Andrius Ušinskas², Eugenijus Januškevičius³, Jurgita Ušinskienė⁴ and Simona Letautienė⁵

1. Dept. of Graphical systems, Vilnius Gediminas Technical University
   Saulėtekio av. 11, Vilnius, Lithuania
   giruta.kazakeviciute-januskeviciene@vgtu.lt
2. Dept. of Electronic Systems, Vilnius Gediminas Technical University
   Naugarduko str. 41, Vilnius, Lithuania
   andrius.usinskas@vgtu.lt
3. Laboratory of Computer Aided Architectural Design, Vilnius Gediminas Technical University
   Pylimo str. 26/1, Vilnius, Lithuania
   eugenijus.januskevicius@vgtu.lt
4. Institute of Oncology, Vilnius University
   Santariškiu˛ str., Vilnius, Lithuania
   jurgita.usinskiene@nvi.lt
5. Institute of Oncology, Vilnius University
   Santariškiu˛ str., Vilnius, Lithuania
   simona.letautiene@nvi.lt

Abstract

The article proposes a novel annotating method of sufficient capacity and intended not only on-line but for off-line using for information preservation all advantages of two-dimensional barcodes. The semantic annotations are embedded directly into the reasonably chosen area of the image and bound by spatial identifiers with corresponding regions. The embedding method deals with the different quality requirements of the regions. Two-dimensional QR codes are used as the physical carrier of the annotation, providing the industrial grade for information detection, resilience and error correction capabilities. The annotation is distributed in a series of QR codes for efficient use of the available space. The results reveal that the spatial domain based technique is faster and has higher data embedding capacity than JPEG 2000 based. The amount of embedded information preserving the acceptable image quality in both proposed embedding cases is higher the average length of the presented original descriptions.

Key words

annotation, wavelet, JPEG 2000, DICOM, IW-SSIM

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS151217044K

Publication information

Volume 14, Issue 1 (January 2017)
Year of Publication: 2017
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

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How to cite

Kazakevičiūtė–Januškevičienė, G., Ušinskas, A., Januškevičius, E., Ušinskienė, J., Letautienė, S.: Annotation of the Medical Images Using Quick Response Codes. Computer Science and Information Systems, Vol. 14, No. 1, 175–196. (2017), https://doi.org/10.2298/CSIS151217044K