A High-Capacity Reversible Watermarking Scheme Based on Shape Decomposition for Medical Images

2018 ◽  
Vol 33 (01) ◽  
pp. 1950001 ◽  
Author(s):  
Xin Zhong ◽  
Frank Y. Shih
Keyword(s):  
Medical Image ◽  
Medical Images ◽  
Saliency Detection ◽  
High Capacity ◽  
Detection Algorithm ◽  
Cross Sectional ◽  
Shape Decomposition ◽  
Image Fidelity ◽  
Embedded Image ◽  
Watermarking Scheme

We present a high-capacity reversible, fragile, and blind watermarking scheme for medical images in this paper. A bottom-up saliency detection algorithm is applied to automatically locate the multiple arbitrarily-shaped regions of interest (ROIs). The iterative square-production algorithm is developed to generate different sizes of squares for shape decomposition on the regions of noninterest (RONIs). This scheme of combining the frequency-domain watermarking and arbitrarily-shaped ROI methods can significantly increase the watermarking capacity, whereas the embedded image fidelity is preserved. Extensive experiments were carried out on the OASIS medical image dataset, which consists of a cross-sectional collection of 416 subjects, aged from 18 to 96 years old. The results show that the proposed scheme outperforms six existing state-of-the-art schemes in terms of watermarking capacity and embedded image fidelity.

Medical Image Analysis by Robot Kinematics

2006 ◽  
Vol 326-328 ◽  
pp. 875-878
Author(s):  
Jae Bum An ◽  
Li Li Xin
Keyword(s):  
Image Registration ◽  
Medical Image ◽  
Medical Images ◽  
Medical Image Analysis ◽  
Robot Kinematics ◽  
Surgical Robots ◽  
Cross Sectional ◽  
Registration Algorithm ◽  
Straight Line ◽  
Actual Shape

In this paper we present an analysis of medical images based on robot kinematics. One of the most important problems in robot-assisted surgeries is associated with the medical image registration of surgical tools and anatomical targets. The fundamental problems of contemporary frame-based image registration are that the registration fails in case of incomplete data in the image and the registration algorithm depends on the shape, assembly, and number of fiducials. To solve the registration problem in the situation where a cylindrical end-effector of surgical robots operates inside the patient’s body, we developed a numerical method by applying robot kinematics knowledge to cross-sectional medical images. Our method includes a 6-D registration algorithm and a cylindrical frame with four helix and one straight line fiducials. The numerical algorithm requires only a single cross-sectional image and are robust to noise and missing data, and are algorithmically invariant to the actual shape, number, and assembly of fiducials. The algorithm and frame are introduced in this paper, and simulation results are described to show the adequate accuracy and resistance to noise.

An Imperceptible Watermarking Scheme for Medical Images Tamper Detection

2022 ◽  
Vol 16 (1) ◽  
pp. 0-0
Keyword(s):  
Secure Communication ◽  
Medical Image ◽  
Medical Images ◽  
Image Watermarking ◽  
Chaotic Map ◽  
Region Of Interest ◽  
Digital Image Watermarking ◽  
Watermark Image ◽  
Speed Up ◽  
Watermarking Scheme

One of the important issues in telemedicine field refers to an advanced secure communication. Digital image watermarking is an ideal solution since it protects the electronic patient information’s from unauthorized access. This paper presents a novel blind fragile-based image watermarking scheme in spatial domain that merges Speed Up Robust Features (SURF) descriptor with the well-known Weber Descriptors (WDs) and Arnold algorithm. It provides a good way for enhancing the image quality and time complexity for medical data integrity. Firstly, the watermark image is shuffled using Arnold chaotic map. Secondly, the SURF technique is practiced to Region of Interest (ROI) of the medical image and then the blocks around the SURF points are selected to insert the watermark. Finally, the watermark is encrusted and extracted using WDs. Experimental results show good image fidelity with the shortest execution time to ensure medical images integrity.

scholarly journals Enhanced Medical Image Watermarking Scheme with CLA-HE& DWT, SVD Transforms

2018 ◽  
Vol 7 (3.12) ◽  
pp. 1281
Author(s):  
Srinivasarao Gajula ◽  
Rajesh V
Keyword(s):  
Medical Image ◽  
Medical Images ◽  
Signal To Noise Ratio ◽  
Image Watermarking ◽  
Scaling Factor ◽  
Security Requirements ◽  
Watermarking Scheme ◽  
Evaluation Parameters ◽  
Clear Information

In order to get clear information regarding patient it is necessary to enhance medical images like MRI, CT scan, ultrasound etc.  For clinical diagnosis, we have to transmit it through the communication network. During this process information must be protected from malicious users. In this process these images are manipulated, so to protect these images we have to follow some security requirements. In this paper, we are increasing the quality of the image by using enhancement with clahe technique and that enhanced image is watermarked for security purpose by using DWT, SVD transforms with a scaling factor as uniform distribution function. The performance evaluation parameters will give better results for medical as well as under water images. The obtained results are very helpful for integrity of medical images. The technique will provide better response for medical images. This method will give good results in terms of improvement in output, Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE).  

scholarly journals Artificial Neural Network Based Fast Edge Detection Algorithm for MRI Medical Images

2017 ◽  
Vol 7 (1) ◽  
pp. 123 ◽  
Author(s):  
Teddy Surya Gunawan ◽  
Iza Zayana Yaacob ◽  
Mira Kartiwi ◽  
Nanang Ismail ◽  
Nor Farahidah Za'bah ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Image Quality ◽  
Edge Detection ◽  
Medical Image ◽  
Medical Images ◽  
Detection Algorithm ◽  
Edge Detector ◽  
Edge Detection Algorithm ◽  
Canny Edge

<p>Currently, magnetic resonance imaging (MRI) has been utilized extensively to obtain high contrast medical image due to its safety which can be applied repetitively. Edges are represented as important contour features in the medical image since they are the boundaries where distinct intensity changes or discontinuities occur. Many traditional algorithms have been proposed to detect the edge, such as Canny, Sobel, Prewitt, Roberts, Zerocross, and Laplacian of Gaussian (LoG). Moreover, many researches have shown the potential of using Artificial Neural Network (ANN) for edge detection. Although many algorithms have been conducted on edge detection for medical images, however higher computational cost and subjective image quality could be further improved. Therefore, the objective of this paper is to develop a fast ANN based edge detection algorithm for MRI medical images. First, we developed features based on horizontal, vertical, and diagonal difference. Then, Canny edge detector will be used as the training output. Finally, optimized parameters will be obtained, including number of hidden layers and output threshold. Results showed that the proposed algorithm provided better image quality while it has faster processing time around three times time compared to other traditional algorithms, such as Sobel and Canny edge detector.</p>

Half Difference Expansion Based Reversible Data Hiding Scheme for Medical Image Forensics

2020 ◽  
Vol 16 (4) ◽  
pp. 383-396
Author(s):  
Vazhora Malayil Manikandan ◽  
Nelapati Lava Prasad ◽  
Masilamani Vedhanayagam
Keyword(s):  
Medical Image ◽  
Medical Images ◽  
Visual Quality ◽  
Image Forensics ◽  
Reversible Watermarking ◽  
Difference Expansion ◽  
Data Set ◽  
Watermarking Scheme ◽  
Embedding Rate

Background: Medical image authentication is an important area which attempts to establish ownership authentication and data authentication of medical images. Aims: In this paper, we propose a new reversible watermarking scheme based on a novel half difference expansion technique for medical image forensics. Methods: Conventional difference expansion based reversible watermarking scheme generates watermarked images with less visual quality, and the embedding rate was considerably less due to the high probability of overflow or underflow. In the proposed scheme, the quality of the watermarked image has been improved by modifying the traditional difference expansion based watermarking scheme, half of the difference between two pixels will be expanded during watermarking. The modification of pixels during watermarking is limited by expanding half of the pixel difference, which helps to obtain watermarked images with better visual quality and improved embedding rate due to less chance of overflow or underflow during watermarking. We also propose a tamper detection localization process to detect the tampered regions from the watermarked image. Results: Experimental study of the proposed scheme on the standard medical images from Osrix medical image data set shows that the proposed watermarking scheme outperforms the existing schemes in terms of visual quality of the watermarked image and embedding rate. Conclusion: The overhead related to location map and parity information need to be addressed in future works to improve the proposed scheme.

Medical Images Edge Detection Based on Mathematical Morphology

2013 ◽  
pp. 7-11
Author(s):  
J. Mehena
Keyword(s):  
Edge Detection ◽  
Medical Image ◽  
Medical Images ◽  
Detection Algorithm ◽  
Medical Image Segmentation ◽  
Edge Detection Algorithm ◽  
Detection Techniques ◽  
Detection Algorithms ◽  
Image Edge Detection ◽  
Image Edge

Medical images edge detection is an important work for object recognition of the human organs and it is an important pre-processing step in medical image segmentation and reconstruction. Conventionally, edge is detected according to gradient-based algorithm and template-based algorithm, but they are not so good for noise medical image edge detection. In this paper, basic mathematical morphological theory and operations are introduced, and then a novel mathematical morphological edge detection algorithm is proposed to detect the edge of medical images with salt-and-pepper noise. The simulation results shows that the novel mathematical morphological edge detection algorithm is more efficient for image denoising and edge detection than the usually used template-based edge detection algorithms and general morphological edge detection algorithms. It has been observed that the proposed morphological edge detection algorithm performs better than sobel, prewitt, roberts and canny’s edge detection algorithm. In this paper the comparative analysis of various image edge detection techniques is presented using MATLAB 8.0 .

scholarly journals A Novel Encryption Frame for Medical Image with Watermark Based on Hyperchaotic System

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Shun Zhang ◽  
Tiegang Gao ◽  
Lin Gao
Keyword(s):  
Data Hiding ◽  
Private Information ◽  
Medical Image ◽  
Medical Information ◽  
Medical Images ◽  
High Capacity ◽  
Hyperchaotic System ◽  
Similar Images ◽  
High Embedding Capacity ◽  
Difference Histogram

An encryption frame of medical image with watermark based on hyperchaotic system is proposed in this paper. Medical information, such as the patients’ private information, data needed for diagnosis, and information for authentication or protection of medical files, is embedded into the regions of interest (ROI) in medical images with a high capacity difference-histogram-based reversible data-hiding scheme. After that, the watermarked medical images are encrypted with hyperchaotic systems. In the receiving end, the receiver with encryption key can decrypt the image to get similar images for diagnosis. If the receiver has the key for data hiding at the same time, he/she can extract the embedded private information and reversibly recover the original medical image. Experiments and analyses demonstrate that high embedding capacity and low distortion have been achieved in the process of data hiding, and, at the same time, high security has been acquired in the encryption phase.

Research and Implementation of Medical Image Edge Detection Algorithm

2021 ◽  
Vol 7 (5) ◽  
pp. 3866-3877
Author(s):  
Luo Fugui ◽  
Qin Yunchu ◽  
Li Mingzhen
Keyword(s):  
Medical Imaging ◽  
Edge Detection ◽  
Medical Image ◽  
Medical Images ◽  
Small Neighborhood ◽  
Detection Algorithm ◽  
Effect Change ◽  
Edge Detection Algorithm ◽  
Image Edge Detection ◽  
Image Edge

Medical imaging has become an important reference for the diagnosis of various diseases, and the role of medical imaging will become more and more important in the future. The interpretation of medical images is of paramount importance. With the continuous development of medical imaging technology, image interpretation has become more and more important. At present, it is directly inferred by doctors that in order to solve problems more effectively and deal with fuzzy data, it is necessary to research and implement an algorithm-based medical image edge detection assistant system. The current mainstream algorithms for edge detection include: Roberts, Sobel, Prewitt, etc. Most of these algorithms construct operators for small neighborhood pixels of the original image. The problem is that the algorithm is relatively sensitive to noise in the image and does not automatically select the appropriate threshold, resulting in a result that is not as expected. This is a disadvantage of current algorithms. The thesis elaborates on the theory and algorithm of image edge detection. At the same time, from the perspective of the original edge detection algorithm, the Canny algorithm is mainly studied, and the optimized MTM algorithm and Ostu algorithm are combined to study and optimize in the filtering denoising research. Finally, the algorithm is implemented in C++ language, which realizes the automatic extraction of the edge function of medical images under noise conditions. The improved algorithm performs an edge replacement effect change complared to the conventional algorithm.

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.

Sign in / Sign up

Export Citation Format

Share Document