Abstract
BackgroundNowadays, medical imaging equipments produce digital form of medical images. In a modern health care environment, new systems such as PACS (picture archiving and communication systems), use the digital form of medical image too. The digital form of medical images has lots of advantages over its analog form such as ease in storage and transmission. Medical images in digital form must be stored in a secured environment to preserve patient privacy. It is also important to detect modifications on the image. These objectives are obtained by watermarking in medical image.MethodsIn this paper, we present a dual and oblivious (blind) watermarking scheme in the contourlet domain. Because of importance of ROI (region of interest) in interpretation by medical doctors rather than RONI (region of non-interest), we propose an adaptive dual watermarking scheme with different embedding strength in ROI and RONI. We embed watermark bits in singular value vectors of the embedded blocks within lowpass subband in contourlet domain.ResultsThe values of PSNR (peak signal-to-noise ratio) and SSIM (structural similarity measure) index of ROI for proposed DICOM (digital imaging and communications in medicine) images in this paper are respectively larger than 64 and 0.997. These values confirm that our algorithm has good transparency. Because of different embedding strength, BER (bit error rate) values of signature watermark are less than BER values of caption watermark. Our results show that watermarked images in contourlet domain have greater robustness against attacks than wavelet domain. In addition, the qualitative analysis of our method shows it has good invisibility.ConclusionsThe proposed contourlet-based watermarking algorithm in this paper uses an automatically selection for ROI and embeds the watermark in the singular values of contourlet subbands that makes the algorithm more efficient, and robust against noise attacks than other transform domains. The embedded watermark bits can be extracted without the original image, the proposed method has high PSNR and SSIM, and the watermarked image has high transparency and can still conform to the DICOM format.
Highlights
Nowadays, medical imaging equipments produce digital form of medical images
In the recent years, medical images are produced from a wide variety of digital imaging equipments, such as computed tomography (CT), magnetic resonance imaging (MRI), computed radiography (CR) and so forth
The second measure used in this paper is structural similarity measure (SSIM) index, which is a region-based numerical metric that places more emphasis on the human visual system (HVS) than
Summary
The proposed contourlet-based blind adaptive watermarking scheme is described . ROI [Max (bottom edges), Max (right edges)] Figure 3 A proposed test image and automatically selection of ROI and RONI. For each block Ai the adaptive quantization step value δi is computed as follows. Our proposed method only requires the size of binary vector (W), and basic quantization step (δ0) (it doesn’t require the original image or any of its characteristics). The watermarked image I0’ is converted to the contourlet domain and lowpass subband IL’ is selected for extraction. Is computed and quantized by adaptive quantization step δi that is computed alike embedding process (Si = diag(γi, γi2, ..., γiw) denotes a diagonal metric formed by the singular values of each block Ai). We selected minimum payload that can be achieved for all test images
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