A novel robust reversible watermarking scheme for protecting authenticity and integrity of medical images

It is of great importance in telemedicine to protect authenticity and integrity of medical images. They are mainly addressed by two technologies, which are region of interest (ROI) lossless watermarking and reversible watermarking. However, the former causes biases on diagnosis by distorting region of none interest (RONI) and introduces security risks by segmenting image spatially for watermark embedding. The latter fails to provide reliable recovery function for the tampered areas when protecting image integrity. To address these issues, a novel robust reversible watermarking scheme is proposed in this paper. In our scheme, a reversible watermarking method is designed based on recursive dither modulation (RDM) to avoid biases on diagnosis. In addition, RDM is combined with Slantlet transform and singular value decomposition to provide a reliable solution for protecting image authenticity. Moreover, ROI and RONI are divided for watermark generation to design an effective recovery function under limited embedding capacity. Finally, watermarks are embedded into whole medical images to avoid the risks caused by segmenting image spatially. Experimental results demonstrate that our proposed lossless scheme not only has remarkable imperceptibility and sufficient robustness, but also provides reliable authentication, tamper detection, localization and recovery functions, which outperforms existing schemes for protecting medical image

Mobile-based Telemedicine Application using SVD and F-XoR Watermarking for Medical Images

منصة الخدمات الطبية عبارة عن تطبيق متنقل يتم من خلاله تزويد المرضى بتشخيصات الأطباء بناءً على المعلومات المستقاة من الصور الطبية. يجب ألا يتم تبديل محتوى هذه النتائج التشخيصية بشكل غير قانوني أثناء النقل ويجب إعادته إلى المريض الصحيح. في هذه المقالة، نقدم حلاً لهذه المشكلات باستخدام علامة مائية عمياء وقابلة للانعكاس وهشة استنادًا إلى مصادقة صورة المضيف. في الخوارزمية المقترحة، يتم استخدام الإصدار الثنائي من ترميز بوس_شوهوري _هوكوينجهام (BCH) للتقرير الطبي للمريض (PMR) والصورة الطبية الثنائية للمريض (PMI) بعد استخدام الغامض الحصري أو (F-XoR) لإنتاج العلامة الفريدة للمريض باستخدام مخطط المشاركة السرية (SSS). يتم استخدامه لاحقًا كعلامة مائية ليتم تضمينها في مضيف (PMI) باستخدام خوارزمية تحليل القيمة المفرد (SVD) العمياء القائمة على العلامة المائية. وهو حل جديد اقترحناه أيضًا بتطبيق SVD على صورة العلامة المائية العمياء. تحافظ الخوارزمية الخاصة بنا على مصادقة محتوى (PMI) أثناء النقل وملكية (PMR) للمريض لنقل التشخيص المصاحب فيما بعد إلى المريض الصحيح عبر تطبيق التطبيب عن بعد المحمول. يستخدم تقييم الخوارزمية لدينا علامات مائية مسترجعة توضح النتائج الواعدة لمقاييس الأداء العالية مقارنتا مع نتائج الاعمال السابقة في مقاييس الكشف عن التزوير وإمكانية الاسترداد الذاتي، مع قيمة 30NB PSNR، قيمة NC هي 0.99.A medical- service platform is a mobile application through which patients are provided with doctor’s diagnoses based on information gleaned from medical images. The content of these diagnostic results must not be illegitimately altered during transmission and must be returned to the correct patient. In this paper, we present a solution to these problems using blind, reversible, and fragile watermarking based on authentication of the host image. In our proposed algorithm, the binary version of the Bose_Chaudhuri_Hocquengham (BCH) code for patient medical report (PMR) and binary patient medical image (PMI) after fuzzy exclusive or (F-XoR) are used to produce the patient's unique mark using secret sharing schema (SSS). The patient’s unique mark is used later as a watermark to be embedded into host PMI using blind watermarking-based singular value decomposition (SVD) algorithm. This is a new solution that we also proposed to applying SVD into a blind watermarking image. Our algorithm preserves PMI content authentication during the transmission and PMR ownership to the patient for subsequently transmitting associated diagnosis to the correct patient via a mobile telemedicine application. The performance of experimental results is high compare to previous results, uses recovered watermarks demonstrating promising results in the tamper detection metrics and self-recovery capability, with 30db PSNR, NC value is 0.99

Discriminative and robust zero-watermarking scheme based on completed local binary pattern for authentication and copyright identification of medical images

Authentication and copyright identification are two critical security issues for medical images. Although zerowatermarking schemes can provide durable, reliable and distortion-free protection for medical images, the existing zerowatermarking schemes for medical images still face two problems. On one hand, they rarely considered the distinguishability for medical images, which is critical because different medical images are sometimes similar to each other. On the other hand, their robustness against geometric attacks, such as cropping, rotation and flipping, is insufficient. In this study, a novel discriminative and robust zero-watermarking (DRZW) is proposed to address these two problems. In DRZW, content-based features of medical images are first extracted based on completed local binary pattern (CLBP) operator to ensure the distinguishability and robustness, especially against geometric attacks. Then, master shares and ownership shares are generated from the content-based features and watermark according to (2,2) visual cryptography. Finally, the ownership shares are stored for authentication and copyright identification. For queried medical images, their content-based features are extracted and master shares are generated. Their watermarks for authentication and copyright identification are recovered by stacking the generated master shares and stored ownership shares. 200 different medical images of 5 types are collected as the testing data and our experimental results demonstrate that DRZW ensures both the accuracy and reliability of authentication and copyright identification. When fixing the false positive rate to 1.00%, the average value of false negative rates by using DRZW is only 1.75% under 20 common attacks with different parameters

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

Digital watermarking in medical images

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 05/12/2005.This thesis addresses authenticity and integrity of medical images using watermarking. Hospital Information Systems (HIS), Radiology Information Systems (RIS) and Picture Archiving and Communication Systems (P ACS) now form the information infrastructure for today's healthcare as these provide new ways to store, access and distribute medical data that also involve some security risk. Watermarking can be seen as an additional tool for security measures. As the medical tradition is very strict with the quality of biomedical images, the watermarking method must be reversible or if not, region of Interest (ROI) needs to be defined and left intact. Watermarking should also serve as an integrity control and should be able to authenticate the medical image. Three watermarking techniques were proposed. First, Strict Authentication Watermarking (SAW) embeds the digital signature of the image in the ROI and the image can be reverted back to its original value bit by bit if required. Second, Strict Authentication Watermarking with JPEG Compression (SAW-JPEG) uses the same principal as SAW, but is able to survive some degree of JPEG compression. Third, Authentication Watermarking with Tamper Detection and Recovery (AW-TDR) is able to localise tampering, whilst simultaneously reconstructing the original image

New Watermarking Scheme for Security and Transmission of Medical Images for PocketNeuro Project

We describe a new Watermarking system of medical information security and terminal mobile phone adaptation for PocketNeuro project. The later term refers to a Project created for the service of neurological diseases. It consists of transmitting information about patients \"Desk of Patients\" to a doctor\'s mobile phone when he is visiting or examining his patient. This system is capable of embedding medical information inside diagnostic images for security purposes. Our system applies JPEG Compression to Watermarked images to adapt them to the doctor\'s mobile phone. Experiments performed on a database of 30-256x256 pixel-sized neuronal images show that our Watermarking scheme for image security is robust against JPEG Compression. For the purpose of increasing the image Watermarking robustness against attacks for an image transmission and to perform a large data payload, we encode with Turbo-Code image-embedded bits information. Fidelity is improved by incorporation of the Relative Peak Signal-to-Noise Ratio (RPSNR) as a perceptual metric to measure image degradation

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