Telemedicine processes, seamless and maintains optimal medical data

Telemedicine emerged asone of the much identified research domain in academia-industries. TelemedicineProvides flawless processes, seamless and maintains optimal medical datasecurity. Steganography is also most effective process for medical datasecurity for image transformation schemes critical data embedding.

ButSteganography Technique’s efficiency depends on data embedding 8-12, pixeladjustment for maximum imperceptibility and efficiency percentage of imagetransformation. The techniques used in Steganography is integer wavelet transformtechniques (IWT) where used to in transform domain to develop real time dataembedding module. IWT revert backs the integer form output hence it is lessmemory consumer.Rahimi and Rabbani 13scientists experimented IWT based steganography for medical image security.They introduced blink water making techniques technique which embeds thewatermark bits in the singular value vectors within the low pass sub bands inthe contourlet transform domain of DICOM images. This method automaticallyidentifies a rectangular ROI and hides the watermark .In the experiment thescrambled medical diagnostic image will be embedded to dummy cover image towhich IWT will be applied then stego-image can be obtained fusing cover imagewith scrambled medical diagnostic image.

The drawback of this method is lessembedding rate. Tiran 16 produced a method called value difference expansionenable a high capacity reversible data embedding for image steganography. DE14 15 is to perform secret data hiding to difference the horizontal andvertical image while HAAR wavelet transformation occurs  Lou et al. 17 introduced a losslessmultiple-layer spatial data hiding scheme for medical image based onpixel-value differencing expansion.  Thismethod provides a high embedding rate and good quality stego images by usingreduced difference expansion technique to conceal the bit stream in the LSBs ofthe expanded differences. J.

Liu, G. Tang, and Y.Sun 18, focused on medical data confidentiality issue through steganography.In this method cover images was at first transformed into one-dimensionalsequence by means of Hilbert filling curve, which was then processed forsplitting into non-overlapping clusters of three pixels in each. Adaptive pixelpair match (APPM) data embedding is used here as a result causes low distortionand hence high imperceptibility. Later 19 derived a digital steganographymodel to hide Electronic Patient Records (EPR) into medical diagnosis images.Exploited edge detection 20 technique to recognize and embed secret data inspiky image-parts by applying Hamming code to embed three distinct secretmessage bits into 4 bits of the cover image. In 21 RT technique (RippletTransform Type-I) was exploited significantly to enable multimodality MedicalImage Fusion (MIF).

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Authors derived Ripplet Transform Type-I (RT) inconjunction with Pulse-Coupled Neural Network (PCNN). Authors found thatRipplet Transform can be a better alternative to perform image decomposition 2223that eventually could play vital role in medical image steganography.Above mentioned anumber of researches have been done to perform data embedding in images/medicalimage using steganography techniques. All the approaches are focused on eitherPSNR enhancement or embedding capacity enhancement using wavelet transformtechnique. The key requirement like ROI preservation, maximum imperceptibility,minimal or negligible histogram variations, statistical attack resilience,higher PSNR has not been considered much. In Quality optimized medical image information hiding algorithm thatemploys edge detection and data coding RSA based security keyEncryption, Ripplet Transform, LSB embedding has been developed. The proposedmethod over comes the limitations of existing medical image information hidingmethods like high computational cost, limited embedding rate by proposing a newdata hiding technique.

This technique achieves good balance between embeddingcapacity and quality of the stego image.