NROI watermarking of medical images for content authentication

Memon, Noor Ahmed; Gilani, S.A.M.

doi:10.1109/inmic.2008.4777717

Cited by 40 publications

(23 citation statements)

References 13 publications

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“…The area other than the ROI is RONI [26]. Most of the steganographic methods use RONI for data embedding to avoid any kind of modification in the ROI [27][28][29]. For extraction of ROI and RONI in a radiographic image, both supervised and unsupervised methods are used.…”

Section: Related Workmentioning

confidence: 99%

An Algorithm for Data Hiding in Radiographic Images and ePHI/R Application

Rashid¹,

Salamat²,

Prasath³

2018

Preprint

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Abstract:Telemedicine is the use of Information and Communication Technology (ICT) for clinical health care from a distance. The exchange of radiographic images and electronic patient health information/records (ePHI/R) for diagnostic purposes has the risk of confidentiality, ownership identity, and authenticity. In this paper, a data hiding technique for ePHI/R is proposed. The color information in the cover image is used for key generation, and stego-images are produced with ideal case. As a result, the whole stego-system is perfectly secure. This method includes the features of watermarking and steganography techniques. The method is applied to radiographic images. For the radiographic images, this method resembles watermarking, which is an ePHI/R data system. Experiments show promising results for the application of this method to radiographic images in ePHI/R for both transmission and storage purpose.

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Section: Related Workmentioning

confidence: 99%

An Algorithm for Data Hiding in Radiographic Images and ePHI/R Application

Rashid¹,

Salamat²,

Prasath³

2018

Preprint

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“…The other solution is to ignore ROI during the watermarking process by having this part left without embedding any data and by concentrating on embedding data into the region of non interest (RONI) through reversible [14][15][16][17][18][19] or non-reversible methods [20][21][22][23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

“…For example, in [14,16,18,20,22,25,[31][32][33][34], the ROI is manually assigned by defining a rectangle box around it, and in [15,17,21,27,28], the polygonal ROI is specified manually. In automatic ROI partitioning [19,23,24,26,29,30], there are some problems which will be highlighted later in this paper.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, drawing the black boundary on the input image before segmentation process and finding the seed pixel in region-growing part must be done manually. The only automatic method that can work robustly with additional noise on medical images is the one suggested by Memon [23,30], in which the ROI is detected by drawing an ellipse around it. However, this method is only useful for a set of medical images with elliptical ROI located at the central part of the image.…”

Section: Introductionmentioning

confidence: 99%

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A Heuristic Automatic and Robust ROI Detection Method for Medical Image Warermarking

2015

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This paper presents an automatic region of interest (ROI) segmentation method for application of watermarking in medical images. The advantage of using this scheme is that the proposed method is robust against different attacks such as median, Wiener, Gaussian, and sharpening filters. In other words, this technique can produce the same result for the ROI before and after these attacks. The proposed algorithm consists of three main parts; suggesting an automatic ROI detection system, evaluating the robustness of the proposed system against numerous attacks, and finally recommending an enhancement part to increase the strength of the composed system against different attacks. Results obtained from the proposed method demonstrated the promising performance of the method.

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“…These medical images are exchanged between the hospitals by the medical practitioners for number of reasons. One main reason of these is the second opinion of doctor from another hospital on the same case under consideration [1]. This exchange of medical images imposes two main constraints for medical information (i) Content Authentication means image content has not been modified or tampered with during transmission from one hospital to another.…”

Section: Introductionmentioning

confidence: 99%

Dual Watermarking of CT Scan Medical Images for Content Authentication and Copyright Protection

Memon

Keerio

Abbasi

2014

Communications in Computer and Information Science

Self Cite

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Abstract. Digital CT Scan images are exchanged among the medical practitioners for consultative purposes or discussing diagnostic and therapeutic measures. This exchange of medical images imposes two main constraints for medical information: (i) the Content Authentication and (ii) Copyright protection. To address these two issues, we have proposed a technique of watermarking for medical images which embeds two watermarks in the CT scan image. The binary pattern is embedded in region of interest (ROI) for content authentication and the composite watermark is embedded in the region of non interest (RONI) for copyright protection. Initially CT Scan image is divided in ROI and RONI by segmentation process. The segmented ROI contains some holes which are first filled. The image morphology is then used and closing operation is applied on the resultant image which eliminates small holes and fills gaps in the contour. Thus binary mask is obtained which is used to separate ROI from RONI. Before embedding the binary pattern in ROI for data authentication purpose, the Least Significant Bit (LSB) information of ROI is extracted first and is saved in separate store. Also, before embedding the composite watermark, pixels in RONI are scrambled for providing the further security. The payload in both ROI and RONI is embedded with simple LSB substitution technique. The extraction procedure is the reverse of embedding process. However few steps of extraction procedure are same as embedding procedure. We have used CT scan image database obtained from Radiology Department, Ackron University Ohio USA. The experimental results show that the proposed algorithm provides better security of medical information during transmission by addressing both issues of data authentication and copyright protection.

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NROI watermarking of medical images for content authentication

Cited by 40 publications

References 13 publications

An Algorithm for Data Hiding in Radiographic Images and ePHI/R Application

An Algorithm for Data Hiding in Radiographic Images and ePHI/R Application

A Heuristic Automatic and Robust ROI Detection Method for Medical Image Warermarking

Dual Watermarking of CT Scan Medical Images for Content Authentication and Copyright Protection

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