Title: Transmission and archiving of reduced MRI medical images

Authors: Hedi Amri; Med Karim Abdmouleh; Ali Khalfallah; Jean-Christophe Lapayre; Med Salim Bouhlel

Addresses: University Bourgogne – Franche-Comte UBFC, FEMTO-st CNRS Institut 16 Rte de Gray, 25030, Besancon Cedex, France; Research Unit of Sciences and Technologies of Image and Telecommunications, Higher Institute of Biotechnology, University of Sfax, Sfax, Tunisia ' Research Unit of Sciences and Technologies of Image and Telecommunications, Higher Institute of Biotechnology, University of Sfax, Sfax, Tunisia ' Research Unit of Sciences and Technologies of Image and Telecommunications, Higher Institute of Biotechnology, University of Sfax, Sfax, Tunisia ' University Bourgogne – Franche-Comte UBFC, FEMTO-st CNRS Institut 16 Rte de Gray, 25030, Besancon Cedex, France ' Research Unit of Sciences and Technologies of Image and Telecommunications, Higher Institute of Biotechnology, University of Sfax, Sfax, Tunisia

Abstract: Medical images are often large. To minimise their file sizes, different compression standards like JPEG, JPEG 2000 and TIFF have been developed, but they can affect the image quality in case of lossy compression. In this paper, we propose a compression method based on image resizing that can reduce the file size to a quarter before its transmission or archiving. When it is received or before its display, the reduced image is enlarged to ensure better visual comfort. This approach is called REPro. In this context, we have used three image reduction techniques namely square-square mesh decimation, square-square filtered mesh decimation, the square-staggered-square filtered mesh decimation. In addition, we have utilised four enlargement techniques namely zero padding, nearest neighbour interpolation, cubic spline interpolation and binterpolation to resize MRI images. The experimental results prove that the combination of the square-square mesh decimation with the B-spline interpolation ensures the minimum distortion of the original image.

Keywords: telemedicine; archiving; transmission; medical images; image reduction; image expansion.

DOI: 10.1504/IJMEI.2020.105657

International Journal of Medical Engineering and Informatics, 2020 Vol.12 No.1, pp.62 - 76

Received: 28 Dec 2017
Accepted: 01 May 2018

Published online: 06 Mar 2020 *

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