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Medical imaging and information management systems require transmission of medical images over the Internet. Many image watermarking techniques have been proposed in recent years to ensure the integrity and authenticity of medical images transferred over insecure networks. In this work, we propose a new medical image watermarking technique to detect tampered regions on medical images with finer accuracy by authenticating 4 × 4 blocks and without restricting region of interest (ROI) size. The proposed method can mark a 4 × 4 pixel block if it has even one tampered pixel, while similar methods (which have no ROI size restriction) mark 8 × 8, 16 × 16, and 40 × 40 pixel blocks. Modified difference expansion (MDE) and least significant bit (LSB) embedding techniques are used together first in the literature by the method to embed authentication bits into corresponding blocks. The method uses a small 4 × 4 window to mark the tampered region. Experimental results show that the proposed method detects tampered regions on medical images with high accuracy and can be used by all medical image modalities. The results also indicate that the method has finer accuracy and no ROI size restriction compared to similar works reported in the literature.

Telemedicine has gained popularity in recent years. Medical images can be transferred over the Internet to enable the telediagnosis between medical staffs and to make the patient's history accessible to medical staff from anywhere. Therefore, integrity protection of the medical image is a serious concern due to the broadcast nature of the Internet. Some watermarking techniques are proposed to control the integrity of medical images. However, they require embedding of extra information (watermark) into image before transmission. It decreases visual quality of the medical image and can cause false diagnosis. The proposed method uses passive image authentication mechanism to detect the tampered regions on medical images. Structural texture information is obtained from the medical image by using local binary pattern rotation invariant (LBPROT) to make the keypoint extraction techniques more successful. Keypoints on the texture image are obtained with scale invariant feature transform (SIFT). Tampered regions are detected by the method by matching the keypoints. The method improves the keypoint-based passive image authentication mechanism (they do not detect tampering when the smooth region is used for covering an object) by using LBPROT before keypoint extraction because smooth regions also have texture information. Experimental results show that the method detects tampered regions on the medical images even if the forged image has undergone some attacks (Gaussian blurring/additive white Gaussian noise) or the forged regions are scaled/rotated before pasting.

Telemedicine systems are used to transfer medical images between hospitals and doctors for consultation in many countries recently. It is crucial to ensure integrity of medical images transferred on unencrypted channels. Many medical image watermarking techniques have been proposed in the literature to deal with this problem. Thermal imaging to detect dense vascular regions is a new medical imaging modality gaining popularity to enhance diagnosis of breast cancer. Thermal images with large smooth areas and Region of Interest (ROI) have different characteristics compared to traditional medical images and require new image watermarking methods. A new thermal image watermarking algorithm utilizing Integer Wavelet Transform (IWT), Modified Difference Expansion (MDE) and Shamir's Secret Sharing Scheme (SSSS) has been proposed for e-healthcare applications in this paper. IWT coefficients of thermal image are expanded by the MDE to make more consecutive blocks expandable. Location Map (LM) becomes more compressible if there are many consecutive blocks. Thus, larger ROI can be watermarked by the proposed method. The method also uses SSSS to share LM into meaningless shares embedded into border regions. Sharing LM by the SSSS makes it possible to reconstruct it even if some of the thermal image borders are removed inadvertently or modified on purpose to break the watermark. Experimental results indicate that the proposed method has better embedding capacity and good imperceptibility compared to similar methods reported in the literature. Besides, it has expanded ROI size and also is the first method which considers border region attacks in medical image watermarking. [ABSTRACT FROM AUTHOR]