A Hybridized Methodology of Different Wavelet Transformations Targeting Medical Images in IoT Infrastructure

Tamara K. Al-Shayea , Constandinos X. Mavromoustakis , Jordi Mongay Batalla , George Mastorakis

Abstract

The Internet of Things (IoT) paradigm has become a vital part of all significant scientific sectors, including the healthcare domain. Medical images in the healthcare sector are indispensable items that are usually susceptible to distortion once they are shared and transferred via the Internet. The sector faces the distinct and constant challenge of preserving medical data, which can be manipulated by various malicious attacks, in turn potentially compromising the patients’ diagnostic data. In this situation, such medical data ought to be private, with access only granted to patients and physicians. This paper elaborates on a hybrid measurement technique for digital image watermarking that utilizes medical images (X-ray, MRA, and CT), which are an extremely robust method for protecting clinical information. The authors explore various different wavelet families, in addition to hybridization between these wavelets. These are carried out on three levels decomposition of Discrete wavelet transformation (biorthogonal 6.8 wavelets, biorthogonal 3.5 wavelets, biorthogonal 5.5 wavelets, reverse biorthogonal 6.8, reverse biorthogonal 3.5, reverse biorthogonal 5.5, discrete meyer, symlets 5, symlets 8 coiflets 4 wavelet, and coiflets 5 wavelet transform). Each level uses various types of wavelet transformation to present the watermarked image, and then extracts the medical watermark from the original watermarked image. The results of diverse types of attack have been compared, while the proposed measurement technique's performance is evaluated using statistical parameters (MSE, PSNR, SSIM, and NC). This in turn measures the quality of the image, which so far shows promising results.
Author Tamara K. Al-Shayea - University of Nicosia (UNIC) [University of Nicosia and University of Nicosia Research Foundation (UNRF)]
Tamara K. Al-Shayea,,
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, Constandinos X. Mavromoustakis - University of Nicosia (UNIC) [University of Nicosia and University of Nicosia Research Foundation (UNRF)]
Constandinos X. Mavromoustakis,,
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, Jordi Mongay Batalla (FEIT / IT)
Jordi Mongay Batalla,,
- The Institute of Telecommunications
, George Mastorakis - Technological Educational Insitute of Crete (TEI) [Hellenic Mediterranean University]
George Mastorakis,,
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Journal seriesMeasurement, [Measurement: Journal of the International Measurement Confederation], ISSN 0263-2241, e-ISSN 1873-412X
Issue year2019
Vol148
Noin press
Pages1-14
Publication size in sheets0.3
Keywords in EnglishMedical image watermarking, Biorthogonal wavelet, Reverse Biorthogonal wavelet, Discrete Meyer wavelet, Symlets wavelet, Coiflets wavele, tInternet Of Thing, Discrete wavelet transform
ASJC Classification2208 Electrical and Electronic Engineering; 2604 Applied Mathematics; 3104 Condensed Matter Physics; 3105 Instrumentation
DOIDOI:10.1016/j.measurement.2019.07.041
URL https://www.sciencedirect.com/science/article/pii/S0263224119306700?via%3Dihub
Project[e22s16] Implementation of the 5G network in the Polish economy. Project leader: Mongay Batalla Jordi, , Phone: +48 22 234-, start date 14-12-2018, planned end date 31-08-2021, IT/2019/badawczy/63, Implemented
WEiTI Projects financed by NCRD [Projekty finansowane przez NCBiR (NCBR)]
Languageen angielski
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2019 Mongay A hybridized methodology of different wavelet transformations targeting medical images in IoT infrastructure.pdf 1.29 MB
Score (nominal)200
Score sourcejournalList
ScoreMinisterial score = 200.0, 15-07-2020, ArticleFromJournal
Publication indicators Scopus Citations = 2; WoS Citations = 0; GS Citations = 3.0; Scopus SNIP (Source Normalised Impact per Paper): 2017 = 1.566; WoS Impact Factor: 2018 = 2.791 (2) - 2018=2.826 (5)
Citation count*4 (2020-08-08)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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