Background and Objective: Generally, there is problem of integrity and security of digital medical images contents for transferring from one hospital to another. There is no perfect procedure to protect and secure medical images from unauthorized users. The main objective of this study was to present a medical image watermarking system by hiding some secret codes in the medical images for verification of its integrity and ownership. Materials and Methods: The study integrated three different techniques namely the spatial domain watermarking, Least Significant Bit (LSB) and cryptographic hash functions for developing a medical image watermarking scheme. The study embedded three watermarks namely the Electronic Patient Record (EPR), index code (IDX) and doctor’s ID (DID) for developing the watermark system. The Message Authentication Code (MAC) was calculated of the center part of original image and then compared with the MAC calculated from the received watermarked image for verifying the integrity of image content. The proposed medical image watermarking method utilized the Least Significant Bit (LSB) and was compared with dual watermarking (DUALWM) technique for accuracy. Results: The proposed LSB method utilized 8064 pixels for embedding the watermark information from a CT scan image as compared to 50400 pixels used by DUALWM technique. Consequently it required less time for segmentation process and delivered high rates of PNSR ratio for watermarked images. The proposed LSB method introduced less noise in the input image resulting in the production of watermarked images of high level imperceptibility. Additionally, the bandwidth required for the proposed LSB method was low as both the text and image files are transmitted as single entity instead of two separate files. Conclusion: The proposed LSB method is preferred over DUALWM technique because it does not require either additional memory storage or time overhead. The proposed system can facilitate the public and private sectors by providing security in the medical image data base archiving and retrieving systems.
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