An Approach for Spread Spectrum based Data Embedding and Retrieving using Optimization Technique in Medical Image
Data embedding and retrieving plays a high-priority role in the medical image application for transferral and storage uses. The medical images with different modalities like CT, MRI, and PET with the patient attributes can be sent to the physician all over the globe for diagnosis. This paper presents a new novel technique for spread spectrum based data embedding and retrieving the patient attributes along with the DICOM images by using modified grey wolf optimization (MGWO) technique in complex contourlet transform (CCT) domain. The patient attributes are separated by using grey-level co-occurrence matrix (GLCM) features. Hence, this paper suggests that the data embedding and retrieving technique based on MGWO in CCT domain yields high peak signal-to-noise ratio (PSNR) with very low mean square error (MSE) value. Furthermore, it also provides good hiding capacity. Therefore, the proposed idea satisfies the basic peculiarities of embedding and retrieving activity.
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