Protection of medical images and patient related information in healthcare: Using an intelligent and reversible watermarking technique

This work presents an intelligent technique based on reversible watermarking for protecting patient and medical related information. In the proposed technique ‘IRW-Med’, the concept of companding function is exploited for reducing embedding distortion, while Integer Wavelet Transform (IWT) is used as an embedding domain for achieving reversibility. Histogram processing is employed to avoid underflow/overflow. In addition, the learning capabilities of Genetic Programming (GP) are exploited for intelligent wavelet coefficient selection. In this context, GP is used to evolve models that not only make an optimal tradeoff between imperceptibility and capacity of the watermark, but also exploit the wavelet coefficient hidden dependencies and information related to the type of sub band. The novelty of the proposed IRW-Med technique lies in its ability to generate a model that can find optimal wavelet coefficients for embedding, and also acts as a companding factor for watermark embedding. The proposed IRW-Med is thus able to embed watermark with low distortion, take out the hidden information, and also recovers the original image. The proposed IRW-Med technique is effective with respect to capacity and imperceptibility and effectiveness is demonstrated through experimental comparisons with existing techniques using standard images as well as a publically available medical image dataset

Reversible Image Watermarking Using Modified Quadratic Difference Expansion and Hybrid Optimization Technique

With increasing copyright violation cases, watermarking of digital images is a very popular solution for securing online media content. Since some sensitive applications require image recovery after watermark extraction, reversible watermarking is widely preferred. This article introduces a Modified Quadratic Difference Expansion (MQDE) and fractal encryption-based reversible watermarking for securing the copyrights of images. First, fractal encryption is applied to watermarks using Tromino's L-shaped theorem to improve security. In addition, Cuckoo Search-Grey Wolf Optimization (CSGWO) is enforced on the cover image to optimize block allocation for inserting an encrypted watermark such that it greatly increases its invisibility. While the developed MQDE technique helps to improve coverage and visual quality, the novel data-driven distortion control unit ensures optimal performance. The suggested approach provides the highest level of protection when retrieving the secret image and original cover image without losing the essential information, apart from improving transparency and capacity without much tradeoff. The simulation results of this approach are superior to existing methods in terms of embedding capacity. With an average PSNR of 67 dB, the method shows good imperceptibility in comparison to other schemes

Robust watermarking for magnetic resonance images with automatic region of interest detection

Medical image watermarking requires special considerations compared to ordinary watermarking methods. The first issue is the detection of an important area of the image called the Region of Interest (ROI) prior to starting the watermarking process. Most existing ROI detection procedures use manual-based methods, while in automated methods the robustness against intentional or unintentional attacks has not been considered extensively. The second issue is the robustness of the embedded watermark against different attacks. A common drawback of existing watermarking methods is their weakness against salt and pepper noise. The research carried out in this thesis addresses these issues of having automatic ROI detection for magnetic resonance images that are robust against attacks particularly the salt and pepper noise and designing a new watermarking method that can withstand high density salt and pepper noise. In the ROI detection part, combinations of several algorithms such as morphological reconstruction, adaptive thresholding and labelling are utilized. The noise-filtering algorithm and window size correction block are then introduced for further enhancement. The performance of the proposed ROI detection is evaluated by computing the Comparative Accuracy (CA). In the watermarking part, a combination of spatial method, channel coding and noise filtering schemes are used to increase the robustness against salt and pepper noise. 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). Based on experiments, the CA under eight different attacks (speckle noise, average filter, median filter, Wiener filter, Gaussian filter, sharpening filter, motion, and salt and pepper noise) is between 97.8% and 100%. The CA under different densities of salt and pepper noise (10%-90%) is in the range of 75.13% to 98.99%. In the watermarking part, the performance of the proposed method under different densities of salt and pepper noise measured by total PSNR, ROI PSNR, total SSIM and ROI SSIM has improved in the ranges of 3.48-23.03 (dB), 3.5-23.05 (dB), 0-0.4620 and 0-0.5335 to 21.75-42.08 (dB), 20.55-40.83 (dB), 0.5775-0.8874 and 0.4104-0.9742 respectively. In addition, the BER is reduced to the range of 0.02% to 41.7%. To conclude, the proposed method has managed to significantly improve the performance of existing medical image watermarking methods

Secure medical image watermarking based on reversible data hiding with Arnold's cat map

The process of restoring medical images to their original form after the extraction process in application watermarking is crucial for ensuring their authenticity. Inaccurate diagnoses can occur due to distortions in medical images from conventional data embedding applications. To address this issue, reversible data hiding (RDH) method has been proposed by several researchers in recent years to embed data in medical images. After the extraction process, images can be restored to their original form with a reversible data-hiding method. In the past few years, several RDH methods have been rapidly developed, which are based on the concept of difference expansion (DE). However, it is crucial to pay attention to the security of the medical image watermarking method, the embedded data with RDH method can be easily modified, accessed, and altered by unauthorized individuals if they know the employed method. This research suggests a new approach to secure the RDH method through the use of Chaotic Map-based Arnold's Cat Map algorithms on the medical images. Data embedding was performed on random medical images using a DE method. Four gray-scale medical image modalities were used to assess the proposed method's efficacy. In our approach, we can incorporate capacity up to 0.62 bpp while maintaining a visual quality up to 41.02 dB according to PSNR and 0.9900 according to SSIM. The results indicated that it can enhance the security of the RDH method while retaining the ability to embed data and preserving the visual appearance of the medical images

Digital watermarking : applicability for developing trust in medical imaging workflows state of the art review

Medical images can be intentionally or unintentionally manipulated both within the secure medical system environment and outside, as images are viewed, extracted and transmitted. Many organisations have invested heavily in Picture Archiving and Communication Systems (PACS), which are intended to facilitate data security. However, it is common for images, and records, to be extracted from these for a wide range of accepted practices, such as external second opinion, transmission to another care provider, patient data request, etc. Therefore, confirming trust within medical imaging workflows has become essential. Digital watermarking has been recognised as a promising approach for ensuring the authenticity and integrity of medical images. Authenticity refers to the ability to identify the information origin and prove that the data relates to the right patient. Integrity means the capacity to ensure that the information has not been altered without authorisation. This paper presents a survey of medical images watermarking and offers an evident scene for concerned researchers by analysing the robustness and limitations of various existing approaches. This includes studying the security levels of medical images within PACS system, clarifying the requirements of medical images watermarking and defining the purposes of watermarking approaches when applied to medical images

ROI-based reversible watermarking scheme for ensuring the integrity and authenticity of DICOM MR images

Reversible and imperceptible watermarking is recognized as a robust approach to confirm the integrity and authenticity of medical images and to verify that alterations can be detected and tracked back. In this paper, a novel blind reversible watermarking approach is presented to detect intentional and unintentional changes within brain Magnetic Resonance (MR) images. The scheme segments images into two parts; the Region of Interest (ROI) and the Region of Non Interest (RONI). Watermark data is encoded into the ROI using reversible watermarking based on the Difference Expansion (DE) technique. Experimental results show that the proposed method, whilst fully reversible, can also realize a watermarked image with low degradation for reasonable and controllable embedding capacity. This is fulfilled by concealing the data into ‘smooth’ regions inside the ROI and through the elimination of the large location map required for extracting the watermark and retrieving the original image. Our scheme delivers highly imperceptible watermarked images, at 92.18-99.94dB Peak Signal to Noise Ratio (PSNR) evaluated through implementing a clinical trial based on relative Visual Grading Analysis (relative VGA). This trial defines the level of modification that can be applied to medical images without perceptual distortion. This compares favorably to outcomes reported under current state-of-art techniques. Integrity and authenticity of medical images are also ensured through detecting subsequent changes enacted on the watermarked images. This enhanced security measure, therefore, enables the detection of image manipulations, by an imperceptible approach, that may establish increased trust in the digital medical workflow

A dual adaptive watermarking scheme in contourlet domain for DICOM images

<p>Abstract</p> <p>Background</p> <p>Nowadays, medical imaging equipments produce digital form of medical images. In a modern health care environment, new systems such as PACS (picture archiving and communication systems), use the digital form of medical image too. The digital form of medical images has lots of advantages over its analog form such as ease in storage and transmission. Medical images in digital form must be stored in a secured environment to preserve patient privacy. It is also important to detect modifications on the image. These objectives are obtained by watermarking in medical image.</p> <p>Methods</p> <p>In this paper, we present a dual and oblivious (blind) watermarking scheme in the contourlet domain. Because of importance of ROI (region of interest) in interpretation by medical doctors rather than RONI (region of non-interest), we propose an adaptive dual watermarking scheme with different embedding strength in ROI and RONI. We embed watermark bits in singular value vectors of the embedded blocks within lowpass subband in contourlet domain.</p> <p>Results</p> <p>The values of PSNR (peak signal-to-noise ratio) and SSIM (structural similarity measure) index of ROI for proposed DICOM (digital imaging and communications in medicine) images in this paper are respectively larger than 64 and 0.997. These values confirm that our algorithm has good transparency. Because of different embedding strength, BER (bit error rate) values of signature watermark are less than BER values of caption watermark. Our results show that watermarked images in contourlet domain have greater robustness against attacks than wavelet domain. In addition, the qualitative analysis of our method shows it has good invisibility.</p> <p>Conclusions</p> <p>The proposed contourlet-based watermarking algorithm in this paper uses an automatically selection for ROI and embeds the watermark in the singular values of contourlet subbands that makes the algorithm more efficient, and robust against noise attacks than other transform domains. The embedded watermark bits can be extracted without the original image, the proposed method has high PSNR and SSIM, and the watermarked image has high transparency and can still conform to the DICOM format.</p

Data hiding techniques in steganography using fibonacci sequence and knight tour algorithm

The foremost priority in the information and communication technology era, is achieving an efficient and accurate steganography system for hiding information. The developed system of hiding the secret message must capable of not giving any clue to the adversaries about the hidden data. In this regard, enhancing the security and capacity by maintaining the Peak Signal-to-Noise Ratio (PSNR) of the steganography system is the main issue to be addressed. This study proposed an improved for embedding secret message into an image. This newly developed method is demonstrated to increase the security and capacity to resolve the existing problems. A binary text image is used to represent the secret message instead of normal text. Three stages implementations are used to select the pixel before random embedding to select block of (64 × 64) pixels, follows by the Knight Tour algorithm to select sub-block of (8 × 8) pixels, and finally by the random pixels selection. For secret embedding, Fibonacci sequence is implemented to decomposition pixel from 8 bitplane to 12 bitplane. The proposed method is distributed over the entire image to maintain high level of security against any kind of attack. Gray images from the standard dataset (USC-SIPI) including Lena, Peppers, Baboon, and Cameraman are implemented for benchmarking. The results show good PSNR value with high capacity and these findings verified the worthiness of the proposed method. High complexities of pixels distribution and replacement of bits will ensure better security and robust imperceptibility compared to the existing systems in the literature