Title
A robust medical image watermarking against salt and pepper noise for brain MRI images.
Abstract
The ever-growing numbers of medical digital images and the need to share them among specialists and hospitals for better and more accurate diagnosis require that patients' privacy be protected. During the transmission of medical images between hospitals or specialists through the network, the main priority is to protect a patient's documents against any act of tampering by unauthorised individuals. Because of this, there is a need for medical image authentication scheme to enable proper diagnosis on patient. In addition, medical images are also susceptible to salt and pepper impulse noise through the transmission in communication channels. This noise may also be intentionally used by the invaders to corrupt the embedded watermarks inside the medical images. A common drawback of existing watermarking methods is their weakness against salt and pepper noise. The research carried out in this work addresses the issue of designing a new watermarking method that can withstand high density of salt and pepper noise for brain MRI images. For this purpose, combination of a spatial domain watermarking method, channel coding and noise filtering schemes are used. The region of non-interest (RONI) of MRI images from five different databases are used as embedding area and electronic patient record (EPR) is considered as embedded data. The quality of watermarked image is evaluated using Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM), and the accuracy of the extracted watermark is assessed in terms of Bit Error Rate (BER).
Year
DOI
Venue
2017
10.1007/s11042-016-3622-9
Multimedia Tools Appl.
Keywords
Field
DocType
Brain MRI image, Robust medical watermarking, Salt and pepper noise, Authentication, Electronic patient record, DICOM
Computer vision,Digital watermarking,DICOM,Pattern recognition,Computer science,Salt-and-pepper noise,Filter (signal processing),Digital image,Watermark,Impulse noise,Artificial intelligence,Bit error rate
Journal
Volume
Issue
ISSN
76
7
1573-7721
Citations 
PageRank 
References 
5
0.40
19
Authors
4
Name
Order
Citations
PageRank
Seyed Mojtaba Mousavi1351.52
Alireza Naghsh2361.87
Azizah Abdul Manaf3447.97
S. A. R. Abu-Bakar4799.67