A Novel Fragile Zero-Watermarking Algorithm for Digital Medical Images

The wireless transmission of patients’ particulars and medical data to a specialised centre after an initial screening at a remote health facility may cause potential threats to patients’ data privacy and integrity. Although watermarking can be used to rectify such risks, it should not degrade the medical data, because any change in the data characteristics may lead to a false diagnosis. Hence, zero watermarking can be helpful in these circumstances. At the same time, the transmitted data must create a warning in case of tampering or a malicious attack. Thus, watermarking should be fragile in nature. Consequently, a novel hybrid approach using fragile zero watermarking is proposed in this study. Visual cryptography and chaotic randomness are major components of the proposed algorithm to avoid any breach of information through an illegitimate attempt. The proposed algorithm is evaluated using two datasets: the Digital Database for Screening Mammography and the Mini Mammographic Image Analysis Society database. In addition, a breast cancer detection system using a convolutional neural network is implemented to analyse the diagnosis in case of a malicious attack and after watermark insertion. The experimental results indicate that the proposed algorithm is reliable for privacy protection and data authentication.

A Blind Medical Image Watermarking for Secure E-Healthcare Application Using Crypto-Watermarking System

A reliable medical image management must provide proper security for patient information. Protecting the medical information of the patients is a major concern in all hospitals. Digital watermarking is a procedure prevalently used to secure the confidentiality of medical information and maintain them, which upgrades patient health awareness. To protect the medical information, the robust and lossless patient medical information sharing system using crypto-watermarking method is proposed. The proposed system consists of two phases: (i) embedding and (ii) extraction. In this paper, we securely share three types of patient information, medical image, electronic health record (EHR), and face image from one hospital to another hospital. Initially, all the three inputs are encrypted and the information is concordant. In order to enhance the robustness of the crypto-watermarking system, the obtained bit stream is compressed, and the compressed bit streams are embedded into the cover image. The same process is repeated for the extraction process. The experimentation result is carried out using different medical images with EHR, and the effectiveness of the proposed algorithm is analyzed with the help of peak signal to noise ratio.

Unique identification code for medical fundus images using blood vessel pattern for tele-ophthalmology applications

BACKGROUND AND OBJECTIVE

Identification of fundus images during transmission and storage in database for tele-ophthalmology applications is an important issue in modern era. The proposed work presents a novel accurate method for generation of unique identification code for identification of fundus images for tele-ophthalmology applications and storage in databases. Unlike existing methods of steganography and watermarking, this method does not tamper the medical image as nothing is embedded in this approach and there is no loss of medical information.

METHODS

Strategic combination of unique blood vessel pattern and patient ID is considered for generation of unique identification code for the digital fundus images. Segmented blood vessel pattern near the optic disc is strategically combined with patient ID for generation of a unique identification code for the image.

RESULTS

The proposed method of medical image identification is tested on the publically available DRIVE and MESSIDOR database of fundus image and results are encouraging.

CONCLUSIONS

Experimental results indicate the uniqueness of identification code and lossless recovery of patient identity from unique identification code for integrity verification of fundus images.