Department of Electronics & Communication Engineering, Amity University, Noida, India.
Int J Med Inform. 2017 Dec;108:110-124. doi: 10.1016/j.ijmedinf.2017.10.010. Epub 2017 Oct 16.
The authentication and integrity verification of medical images is a critical and growing issue for patients in e-health services. Accurate identification of medical images and patient verification is an essential requirement to prevent error in medical diagnosis. The proposed work presents an imperceptible watermarking system to address the security issue of medical fundus images for tele-ophthalmology applications and computer aided automated diagnosis of retinal diseases.
In the proposed work, patient identity is embedded in fundus image in singular value decomposition domain with adaptive quantization parameter to maintain perceptual transparency for variety of fundus images like healthy fundus or disease affected image. In the proposed method insertion of watermark in fundus image does not affect the automatic image processing diagnosis of retinal objects & pathologies which ensure uncompromised computer-based diagnosis associated with fundus image. Patient ID is correctly recovered from watermarked fundus image for integrity verification of fundus image at the diagnosis centre.
The proposed watermarking system is tested in a comprehensive database of fundus images and results are convincing.
results indicate that proposed watermarking method is imperceptible and it does not affect computer vision based automated diagnosis of retinal diseases.
Correct recovery of patient ID from watermarked fundus image makes the proposed watermarking system applicable for authentication of fundus images for computer aided diagnosis and Tele-ophthalmology applications.
在电子医疗服务中，医学图像的认证和完整性验证是患者面临的一个关键且日益严重的问题。准确识别医学图像和患者验证是防止医疗诊断错误的基本要求。本文提出了一种不可见的水印系统，以解决远程眼科应用和计算机辅助视网膜疾病自动诊断中的医学眼底图像的安全问题。
在本文提出的工作中，患者身份信息被嵌入到奇异值分解域的眼底图像中，使用自适应量化参数来保持各种眼底图像（如健康眼底或病变眼底图像）的感知透明度。在该方法中，水印的嵌入不会影响视网膜对象和病变的自动图像处理诊断，从而确保与眼底图像相关的基于计算机的诊断不受影响。在诊断中心，从带水印的眼底图像中正确恢复患者 ID，以验证眼底图像的完整性。
结果表明，所提出的水印系统在眼底图像的综合数据库中进行了测试，结果令人信服。
实验结果表明，所提出的水印方法是不可感知的，它不会影响基于计算机视觉的视网膜疾病自动诊断。
从带水印的眼底图像中正确恢复患者 ID，使得所提出的水印系统适用于计算机辅助诊断和远程眼科应用中的眼底图像认证。
