scholarly journals Joint Digital Water Marking for Medical Images for Improving Security

2018 ◽  
Vol 11 (2) ◽  
pp. 863-870 ◽  
Author(s):  
Kavitha K. J ◽  
Priestly B. Shan
Keyword(s):  
Digital Watermarking ◽  
Medical Image ◽  
Medical Images ◽  
Spatial Domain ◽  
Discrete Wavelet ◽  
System Efficiency ◽  
Simple Method ◽  
Incorrect Diagnosis ◽  
Small Change ◽  
The Military

Digital watermarking is one of the most efficient techniques to provide the highest secureness to the transmission of data like images or videos over the internet. Quite over the medical data which incorporates the EHR (Electronic Health Record) and medical images and conjointly the military data are crucial whose protection and privacy is extremely a lot of essential issues. To secure this data, the Digital watermarking plays a major role so that it will guarantee authentication, integrity, confidentiality and reliability. In the case of medical images, even a small change or modifications are strictly prohibited as it might lead to the incorrect diagnosis of the disease. Therefore, securing medical image is extremely essential. So as to provide high security for each patient’s data and also the various medical scanning images, we can employ the Digital Water Marking (DWM) technique. The DWM technique may be implemented in two ways: Spatial domain technique and Frequency domain technique. Although the spatial implementation is extremely straightforward and a very simple method, most of the implementations are done using frequency or transform/remodel domain strategies since it provides additional details and high effectiveness. The DWM may be implemented using numerous transform/remodel techniques like Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), also with the combination of these remodel techniques. Nowadays the work is also extended using a combination of transforming/remodel and spatial domain techniques. In this article the Digital Water Marking is being implemented by employing a combination of a transform technique DWT and a spatial domain technique SVD to provide security to the medical images and also the system efficiency is checked for numerous attacks.

scholarly journals Parallel Digital Watermarking Process on Ultrasound Medical Images in Multicores Environment

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Hui Liang Khor ◽  
Siau-Chuin Liew ◽  
Jasni Mohd. Zain
Keyword(s):  
Digital Watermarking ◽  
Medical Image ◽  
Medical Images ◽  
Security Threats ◽  
Public Network ◽  
Elapsed Time ◽  
Single Frame ◽  
Internal Network ◽  
Speed Up ◽  
Images Processing

With the advancement of technology in communication network, it facilitated digital medical images transmitted to healthcare professionals via internal network or public network (e.g., Internet), but it also exposes the transmitted digital medical images to the security threats, such as images tampering or inserting false data in the images, which may cause an inaccurate diagnosis and treatment. Medical image distortion is not to be tolerated for diagnosis purposes; thus a digital watermarking on medical image is introduced. So far most of the watermarking research has been done on single frame medical image which is impractical in the real environment. In this paper, a digital watermarking on multiframes medical images is proposed. In order to speed up multiframes watermarking processing time, a parallel watermarking processing on medical images processing by utilizing multicores technology is introduced. An experiment result has shown that elapsed time on parallel watermarking processing is much shorter than sequential watermarking processing.

Medical Image Fusion in Spatial and Transform Domain

2017 ◽  
pp. 281-300
Author(s):  
Alka Srivastava ◽  
Ashwani Kumar Aggarwal
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
Medical Image ◽  
Medical Images ◽  
Spatial Domain ◽  
Transform Domain ◽  
Fusion Technique ◽  
Medical Image Fusion ◽  
Domain Fusion ◽  
Fused Image

Nowadays, there are a lot of medical images and their numbers are increasing day by day. These medical images are stored in the large database. To minimize the redundancy and optimize the storage capacity of images, medical image fusion is used. The main aim of medical image fusion is to combine complementary information from multiple imaging modalities (e.g. CT, MRI, PET, etc.) of the same scene. After performing medical image fusion, the resultant image is more informative and suitable for patient diagnosis. There are some fusion techniques which are described in this chapter to obtain fused image. This chapter presents two approaches to image fusion, namely spatial domain Fusion technique and transforms domain Fusion technique. This chapter describes Techniques such as Principal Component Analysis which is spatial domain technique and Discrete Wavelet Transform and Stationary Wavelet Transform which are Transform domain techniques. Performance metrics are implemented to evaluate the performance of image fusion algorithm.

scholarly journals Log-Gabor Energy Based Multimodal Medical Image Fusion in NSCT Domain

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Yong Yang ◽  
Song Tong ◽  
Shuying Huang ◽  
Pan Lin
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
High Frequency ◽  
Medical Image ◽  
Medical Images ◽  
Discrete Wavelet ◽  
Fusion Method ◽  
Complex Wavelet Transform ◽  
Medical Image Fusion ◽  
Log Gabor

Multimodal medical image fusion is a powerful tool in clinical applications such as noninvasive diagnosis, image-guided radiotherapy, and treatment planning. In this paper, a novel nonsubsampled Contourlet transform (NSCT) based method for multimodal medical image fusion is presented, which is approximately shift invariant and can effectively suppress the pseudo-Gibbs phenomena. The source medical images are initially transformed by NSCT followed by fusing low- and high-frequency components. The phase congruency that can provide a contrast and brightness-invariant representation is applied to fuse low-frequency coefficients, whereas the Log-Gabor energy that can efficiently determine the frequency coefficients from the clear and detail parts is employed to fuse the high-frequency coefficients. The proposed fusion method has been compared with the discrete wavelet transform (DWT), the fast discrete curvelet transform (FDCT), and the dual tree complex wavelet transform (DTCWT) based image fusion methods and other NSCT-based methods. Visually and quantitatively experimental results indicate that the proposed fusion method can obtain more effective and accurate fusion results of multimodal medical images than other algorithms. Further, the applicability of the proposed method has been testified by carrying out a clinical example on a woman affected with recurrent tumor images.

Privacy Protection of Patient Medical Images using Digital Watermarking Technique for E-healthcare System

2019 ◽  
Vol 15 (8) ◽  
pp. 802-809
Author(s):  
Asokan Sivaprakash ◽  
Samuel Nadar Edward Rajan ◽  
Sundaramoorthy Selvaperumal
Keyword(s):  
Health Care ◽  
Digital Watermarking ◽  
Privacy Protection ◽  
Medical Images ◽  
Search Algorithm ◽  
Research Work ◽  
Cuckoo Search ◽  
Superior Performance ◽  
Discrete Wavelet ◽  
Medical Systems

Background: Privacy protection has been a critical issue in the delivery of medical images for telemedicine, e-health care and other remote medical systems. Objective: The aim of this proposed work is to implement a secure, reversible, digital watermarking technique for the transmission of medical data remotely in health care systems. Methods: In this research work, we employed a novel optimized digital watermarking scheme using discrete wavelet transform and singular value decomposition using cuckoo search algorithm based on Lévy flight for embedding watermark into the grayscale medical images of the patient. The performance of our proposed algorithm is evaluated on four different 256 × 256 grayscale host medical images and a 32 × 32 binary logo image. Results: The performance of the proposed scheme in terms of peak signal to noise ratio was remarkably high, with an average of 55.022dB compared to other methods. Conclusion: Experimental results reveal that the proposed method is capable of achieving superior performance compared to some of the state-of-art schemes in terms of robustness, security and high embedding capacity which is required in the field of telemedicine and e-health care system.

scholarly journals An Efficient Lossless ROI Image Compression Using Wavelet-Based Modified Region Growing Algorithm

2018 ◽  
Vol 29 (1) ◽  
pp. 1063-1078
Author(s):  
P. Sreenivasulu ◽  
S. Varadarajan
Keyword(s):  
Wavelet Transform ◽  
Image Compression ◽  
Medical Image ◽  
Medical Images ◽  
Region Of Interest ◽  
Region Growing ◽  
Set Partitioning ◽  
Discrete Wavelet ◽  
Huffman Encoding ◽  
Encoding Method

Abstract Nowadays, medical imaging and telemedicine are increasingly being utilized on a huge scale. The expanding interest in storing and sending medical images brings a lack of adequate memory spaces and transmission bandwidth. To resolve these issues, compression was introduced. The main aim of lossless image compression is to improve accuracy, reduce the bit rate, and improve the compression efficiency for the storage and transmission of medical images while maintaining an acceptable image quality for diagnosis purposes. In this paper, we propose lossless medical image compression using wavelet transform and encoding method. Basically, the proposed image compression system comprises three modules: (i) segmentation, (ii) image compression, and (iii) image decompression. First, the input medical image is segmented into region of interest (ROI) and non-ROI using a modified region growing algorithm. Subsequently, the ROI is compressed by discrete cosine transform and set partitioning in hierarchical tree encoding method, and the non-ROI is compressed by discrete wavelet transform and merging-based Huffman encoding method. Finally, the compressed image combination of the compressed ROI and non-ROI is obtained. Then, in the decompression stage, the original medical image is extracted using the reverse procedure. The experimentation was carried out using different medical images, and the proposed method obtained better results compared to different other methods.

scholarly journals Hybrid multiple watermarking technique for securing medical images of modalities MRI, CT scan, and X-ray

2020 ◽  
Vol 10 (3) ◽  
pp. 2349
Author(s):  
Imane Assini ◽  
Abdelmajid Badri ◽  
Aicha Sahel ◽  
Abdennaceur Baghdad
Keyword(s):  
Medical Image ◽  
Medical Images ◽  
Singular Values ◽  
Hadamard Transform ◽  
Discrete Wavelet ◽  
Resonance Imaging ◽  
X Ray ◽  
Multiple Watermarking ◽  
Magnetic Resonance Imaging Mri ◽  
Value Decomposition

In order to contribute to the security of sharing and transferring medical images, we had presented a multiple watermarking technique for multiple protections; it was based on the combination of three transformations: the discrete wavelet transform (DWT), the fast Walsh-Hadamard transform (FWHT) and, the singular value decomposition (SVD). In this paper, three watermark images of sizes 512x 512 were inserted into a single medical image of various modalities such as magnetic resonance imaging (MRI), computed tomography (CT), and X-Radiation (X-ray). After applying DWT up to the third level on the original image, the high-resolution sub-bands were being selected subsequently to apply FWHT and then SVD. The singular values of the three watermark images were inserted into the singular values of the cover medical image. The experimental results showed the effectiveness of the proposed method in terms of quality and robustness compared to other reported techniques cited in the literature.

scholarly journals Wavelet Packets-Based Blind Watermarking for Medical Image Management

2010 ◽  
Vol 4 (1) ◽  
pp. 93-98 ◽  
Author(s):  
Salwa A.K. Mostafa ◽  
Naser El-sheimy ◽  
A.S. Tolba ◽  
F.M. Abdelkader ◽  
Hisham M. Elhindy
Keyword(s):  
Patient Information ◽  
Medical Image ◽  
Medical Images ◽  
Error Correcting Code ◽  
Healthcare Sector ◽  
Bch Code ◽  
Reference Image ◽  
Discrete Wavelet ◽  
Original Image ◽  
Wide Range

The last decade has witnessed an explosive use of medical images and Electronics Patient Record (EPR) in the healthcare sector for facilitating the sharing of patient information and exchange between networked hospitals and healthcare centers. To guarantee the security, authenticity and management of medical images and information through storage and distribution, the watermarking techniques are growing to protect the medical healthcare information. This paper presents a technique for embedding the EPR information in the medical image to save storage space and transmission overheads and to guarantee security of the shared data. In this paper a new method for protecting the patient information in which the information is embedded as a watermark in the discrete wavelet packet transform (DWPT) of the medical image using the hospital logo as a reference image. The patient information is coded by an error correcting code (ECC), BCH code, to enhance the robustness of the proposed method. The scheme is blind so that the EPR can be extracted from the medical image without the need of the original image. Therefore, this proposed technique is useful in telemedicine applications. Performance of the proposed method was tested using four modalities of medical images; MRA, MRI, Radiological, and CT. Experimental results showed no visible difference between the watermarked and the original image. Moreover, the proposed watermarking method is robust against a wide range of attacks such as JPEG coding, Gaussian noise addition, histogram equalization, gamma correction, contrast adjustment, and sharpen filter and rotation.

Watermarking berbasis Redundant Discrete Wavelet Transform dan Arnold Transform pada Citra Medis

2021 ◽  
Vol 13 (2) ◽  
pp. 48-55
Author(s):  
Ledya Novamizanti ◽  
Irma Safitri ◽  
Hafizhan Bhamakerti Arindaka ◽  
Iwan Iwut Tritoasmoro
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Medical Image ◽  
Medical Images ◽  
Image Watermarking ◽  
Singular Value ◽  
Discrete Wavelet ◽  
Arnold Transform ◽  
Image Sharpening ◽  
Redundant Discrete Wavelet Transform

In telemedicine, data transmission in digital medical images and electronic medical records through the internet is vulnerable to various threats of theft and manipulation. Image watermarking is needed to provide authentication and security to medical images. This paper proposes an image watermarking scheme based on Redundant Discrete Wavelet Transform (RDWT) and Discrete Cosine Transform (DCT) with watermark encryption using Arnold transform. First, the original host medical image was decomposed into four subbands using RDWT. Then, DCT is applied to the LH subband of the RDWT. On the other hand, the watermark is scrambled using Arnold transform to ensure identity security. The singular value of the watermarked image is obtained by modifying the singular value of the host image and the watermark. Tests were carried out on different medical images, namely X-ray, MRI, CT, and ultrasound, with a watermark in a proprietary logo. The host medical image is the same size as the watermark image. The result of this study can provide high authentication, imperceptibility and security in medical images, with an average PSNR value of 65.67 dB, SSIM 1, BER 0, NC 1. This scheme is resistant to JPEG compression, noise addition, filtering, image sharpening, image enhancement, geometric operations, motion blur, image sharpening, and histogram equalization.

scholarly journals Image Enhancement using Wavelet Fusion for Medical Image Processing

2019 ◽  
Vol 9 (1) ◽  
pp. 2663-2667
Keyword(s):  
Image Enhancement ◽  
Medical Image ◽  
Medical Images ◽  
Discrete Wavelet ◽  
Low Contrast ◽  
Adaptive Fusion ◽  
Improved Performance ◽  
Medical Image Enhancement ◽  
Contrast Image

Medical Image Enhancement Low contrast is the active study area that the obtained pictures suffer from noise and low contrast. Age of capturing equipment, bad illumination circumstances are the low contrast medical images. Thus, techniques of contrast improved performance are used before being used to enhance the contrast of medical images. Within a tiny range of pixel concentrations, contrast improvement algorithms enhance low contrast image. Low contrast image enhancement is accomplished using Equalization of Contrast Limited Adaptive Histogram. CLAHE image enhancement is used to enhance the quality of medical images with low contrast. DWT image, sub-bands such as LL, LH, HL, HH are decomposed. 2D Adaptive fusion image on discrete wavelet transformation is used to fuse the main and CLAHE output images. The efficiency of the output is calculated using merged image entropy and PSNR. It is discovered that the visual content of low contrast medical pictures is enhanced effectively on the basis of 2D DWT and adaptive Fusion.

Reversible Watermarking in Medical Images Using Sub-Sample and Multiple Histogram Modification

2020 ◽  
Vol 13 (4) ◽  
pp. 75-90
Author(s):  
Lin Gao ◽  
Yunjie Zhang ◽  
Guoyan Li
Keyword(s):  
Medical Image ◽  
Visual Masking ◽  
Medical Images ◽  
Image Watermarking ◽  
Visual Quality ◽  
Discrete Wavelet ◽  
Embedding Capacity ◽  
Histogram Modification ◽  
Watermarking Scheme ◽  
Redundant Discrete Wavelet Transform

This paper proposed a reversible medical image watermarking scheme using multiple histogram modification (MHM) and redundant discrete wavelet transform (RDWT). The MHM was introduced to the proposed scheme to enhance the embedding capacity. By embedding the watermark in the RDWT coefficients, the proposed scheme exploited the visual masking property of RDWT to guarantee the visual quality. Also, the proposed scheme has better performance on embedding capacity because the RDWT has several sub-band coefficients for embedding. The experimental results on medical images suggests that the proposed scheme could meet the demand of perceptional quality with better embedding capacity than former schemes.

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