Medical image watermarking based on novel encoding for EHR and fusion based morphological watershed segmentation algorithm for medical images

Advancement in the field of healthcare system, the identification of the infection with severity impact of a particular disease may be easily done with the help of scanned radiological images and thereby segmentation plays a major role in detection of presence of foreign objects or infected areas in certain parts of a human body and thereby helps in providing a clinical care to the patient with crucial state. So, precise segmentation is a key-step in the analysis of a disease at the time of radio therapy. Although many traditional segmentation techniques are available to separate region of interest from that of region of non-interest; no complete segmentation algorithm is available which is suitable for all kinds of medical images and moreover, an algorithm suitable for one kind of medical image may not be suitable for other type of medical image as each category of image differs in their characteristics; And hence, in the proposed paper, an improved segmentation algorithm based on dual tree complex wavelet transform (DTCWT) and fusion—morphological watershed algorithm for denoising is proposed for all kinds of scanned medical images and also proposes a medical image watermarking (MIW) based on encoding algorithm with hybrid embedding function for authentication in E-Health care systems. The MIW and segmentation algorithm is applied and evaluated to various modalities of medical images using various quality metrics and statistical parameters. The data integrity of the proposed system is evaluated for constructed MI and EHR and is validated by identifying tampered information in terms of decoding correct and wrong information using secret keys in the proposed system.