Annotation of the Medical Images Using Quick Response Codes
- Dept. of Graphical systems, Vilnius Gediminas Technical University
Saulėtekio av. 11, Vilnius, Lithuania
giruta.kazakeviciute-januskeviciene@vgtu.lt - Dept. of Electronic Systems, Vilnius Gediminas Technical University
Naugarduko str. 41, Vilnius, Lithuania
andrius.usinskas@vgtu.lt - Laboratory of Computer Aided Architectural Design, Vilnius Gediminas Technical University
Pylimo str. 26/1, Vilnius, Lithuania
eugenijus.januskevicius@vgtu.lt - Institute of Oncology, Vilnius University
Santariškiu˛ str., Vilnius, Lithuania
jurgita.usinskiene@nvi.lt - 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
Available in PDF
Portable Document Format
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