Secured Medical Image Hashing Based on Frequency Domain with Chaotic Map

2021 ◽  
Vol 39 (5A) ◽  
pp. 711-722
Author(s):  
Amira K. Jabbar ◽  
Ashwaq T. Hashim ◽  
Qusay F. Al-Doori
Keyword(s):  
Medical Image ◽  
Personal Information ◽  
Chaotic Map ◽  
Region Of Interest ◽  
Image Hashing ◽  
Medical Field ◽  
Hash Algorithm ◽  
Frequency Domains ◽  
Hash Code ◽  
Shift Keying

Recently, online-medicine got increased global interest, particularly during COVID19 pandemic. Data protection is important in the medical field since when promoting telemedicine applications, it is necessary to protect the patient data and personal information. A secured process is needed to transmit medical images over the Internet. In this paper hash algorithm is employed to protect the data by using powerful features from the coupled frequency domains of the Slantlet Transformation (SLT) and the Discrete Cosine Transform (DCT). The Region of Interest (ROI) is localized from an MRI image then extraction of a feature set is performed for calculating the hash code. Then, hash code is enciphered to maintain security by employing a secure Chaotic Shift Keying (CSK). The suggested method of security is ensured by the strength of the CSK and the encryption key secrecy.  A detailed analysis was conducted using 1000 uncompressed images that were chosen randomly from a publicly available AANLIB database. The proposed methodology can be useful for JPEG compression. Also, this method could resist many attacks of image processing likes filtering, noise addition, and some geometric transforms.

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.

Reliable Medical Image Communication in Healthcare IoT

2019 ◽  
pp. 1-26 ◽  
Author(s):  
Siva Janakiraman ◽  
Sundararaman Rajagopalan ◽  
Rengarajan Amirtharajan
Keyword(s):  
Secure Communication ◽  
Medical Image ◽  
Personal Information ◽  
Medical Diagnostics ◽  
Medical Field ◽  
Reliable Communication ◽  
Pixel Resolution ◽  
Image Communication ◽  
Iot Applications ◽  
Performance Validation

Images have been widely used in the medical field for various diagnostic purposes. In the field of healthcare IoT, secure communication of a medical image concerned with an individual is a crucial task. Embedding patients' personal information as an invisible watermark in their medical images helps to authenticate the ownership identification process. Reliable communication of medical image can be thereby ensured concerning authentication and integrity. Images in DICOM format with a pixel resolution of 8-bit depth are used for medical diagnostics. This chapter deals about the development of a lightweight algorithm to insert patients' identities as an invisible watermark in random edge pixels of DICOM images. This chapter describes the implementation of the proposed lightweight watermarking algorithm on a RISC microcontroller suitable for healthcare IoT applications. Imperceptibility level of the watermarked medical image was analyzed besides its lightweight performance validation on the constrained IoT platform.

scholarly journals Automatic Hip Detection in Anteroposterior Pelvic Radiographs—A Labelless Practical Framework

2021 ◽  
Vol 11 (6) ◽  
pp. 522
Author(s):  
Feng-Yu Liu ◽  
Chih-Chi Chen ◽  
Chi-Tung Cheng ◽  
Cheng-Ta Wu ◽  
Chih-Po Hsu ◽  
...  
Keyword(s):  
Medical Image ◽  
Image Annotation ◽  
Region Of Interest ◽  
Confidence Score ◽  
Heterogeneous Data ◽  
Single Shot ◽  
Hip Joints ◽  
Pelvic Radiographs ◽  
Wide Range ◽  
Average Confidence

Automated detection of the region of interest (ROI) is a critical step in the two-step classification system in several medical image applications. However, key information such as model parameter selection, image annotation rules, and ROI confidence score are essential but usually not reported. In this study, we proposed a practical framework of ROI detection by analyzing hip joints seen on 7399 anteroposterior pelvic radiographs (PXR) from three diverse sources. We presented a deep learning-based ROI detection framework utilizing a single-shot multi-box detector with a customized head structure based on the characteristics of the obtained datasets. Our method achieved average intersection over union (IoU) = 0.8115, average confidence = 0.9812, and average precision with threshold IoU = 0.5 (AP50) = 0.9901 in the independent testing set, suggesting that the detected hip regions appropriately covered the main features of the hip joints. The proposed approach featured flexible loose-fitting labeling, customized model design, and heterogeneous data testing. We demonstrated the feasibility of training a robust hip region detector for PXRs. This practical framework has a promising potential for a wide range of medical image applications.

scholarly journals Application of Ultra Narrow Band Modulation in Enhanced Loran System

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4347
Author(s):  
Boyun Lyu ◽  
Yu Hua ◽  
Jiangbin Yuan ◽  
Shifeng Li
Keyword(s):  
Narrow Band ◽  
Data Rate ◽  
Modulation Method ◽  
Phase Shift Keying ◽  
Spectrum Utilization ◽  
Frequency Domains ◽  
Shift Keying ◽  
Modulation Methods ◽  
Binary Phase Shift Keying ◽  
Signal Time

The Enhanced Loran (eLoran) system is valued for its important role in the positioning, navigation, and timing fields; however, with its current modulation methods, low data rate restricts its development. Ultra narrow band (UNB) modulation is a modulation method with extremely high spectrum utilization. If UNB modulation can be applied to the eLoran system, it will be very helpful. The extended binary phase shift keying modulation in UNB modulation is selected for a detailed study, parameters and application model are designed according to its unique characteristics of signal time and frequency domains, and it is verified through simulation that the application of this modulation not only meets the design constraints of the eLoran system but also does not affect the reception of the respective signals of both parties. Several feasible schemes are compared, analyzed, and selected. Studies have revealed that application of UNB modulation in the eLoran system is feasible, and it will increase the data rate of the system by dozens of times.

scholarly journals An Effective Framework for Chaotic Image Encryption Based on 3D Logistic Map

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Guodong Ye ◽  
Kaixin Jiao ◽  
Chen Pan ◽  
Xiaoling Huang
Keyword(s):  
Chaotic Map ◽  
Logistic Map ◽  
Security Analysis ◽  
Three Dimensional ◽  
Ecg Signal ◽  
Hash Algorithm ◽  
Plain Image ◽  
Secure Hash Algorithm ◽  
Low Sensitivity ◽  
Encryption Method

In this paper, an effective framework for chaotic encryption based on a three-dimensional logistic map is presented together with secure hash algorithm-3 (SHA-3) and electrocardiograph (ECG) signal. Following the analysis of the drawbacks, namely, fixed key and low sensitivity, of some current algorithms, this work tries to solve these two problems and includes two contributions: (1) removal of the phenomenon of summation invariance in a plain-image, for which SHA-3 is proposed to calculate the hash value for the plain-image, with the results being employed to influence the initial keys for chaotic map; (2) resolution of the problem of fixed key by using an ECG signal, that can be different for different subjects or different for same subject at different times. The Wolf algorithm is employed to produce all the control parameters and initial keys in the proposed encryption method. It is believed that combining with the classical architecture of permutation-diffusion, the summation invariance in the plain-image and shortcoming of a fixed key will be avoided in our algorithm. Furthermore, the experimental results and security analysis show that the proposed encryption algorithm can achieve confidentiality.

An efficient nested chaotic image encryption algorithm based on DNA sequence

2018 ◽  
Vol 29 (07) ◽  
pp. 1850058 ◽  
Author(s):  
Nabil Ben Slimane ◽  
Nahed Aouf ◽  
Kais Bouallegue ◽  
Mohsen Machhout
Keyword(s):  
Dna Sequence ◽  
Image Encryption ◽  
Chaotic Map ◽  
Security Analysis ◽  
Correlation Coefficients ◽  
Security Level ◽  
Encryption Scheme ◽  
Hash Algorithm ◽  
Encryption Schemes ◽  
Efficient Scheme

In this paper, an efficient scheme for image encryption based on the nested chaotic map and deoxyribonucleic acid (DNA) is introduced. In order to generate the initial condition values of the nested chaotic system, the Secure Hash Algorithm SHA-256 is used. The algorithm consists of two main layers: confusion and diffusion. In the first layer, the nested chaotic map is employed to create the scrambled image. The scrambled image is obtained through the ascending sorting of the first component of the nested chaotic index sequence. To ensure higher sensitivity, higher complexity and higher security, DNA sequence and DNA operator are employed additionally with the nested chaotic map and hash algorithm to modify the pixel values. The important advantages of our algorithm are the improvement of Number of Pixel Change Rate (NPCR), Unified Average Changing Intensity (UACI) and entropy, which improve resistivity against several attacks. Experimental results and relevant security analysis demonstrated that our proposed encryption scheme has the highest security level because it is more complicated, and it has a sufficiently large key space. The proposed method is compared to other recent image encryption schemes using different security analysis factors, including NPCR, UACI, correlation coefficients (CCs), encryption quality (EQ) and entropy. It is also resistant to noise (Salt and Pepper, Gaussian and speckle) and data loss attacks. The illustrated results demonstrated that the proposed image encryption scheme is efficient, and can be adopted for image encryption and transmission.

Region of Interest-Based Coding Technique of Medical Images Using Varying Grading of Compression

2020 ◽  
pp. 2150021
Author(s):  
Urvashi Sharma ◽  
Meenakshi Sood ◽  
Emjee Puthooran
Keyword(s):  
Medical Image ◽  
Region Of Interest ◽  
Block Size ◽  
Threshold Value ◽  
Hospital Performance ◽  
Jpeg 2000 ◽  
Compression Method ◽  
Compression Efficiency ◽  
Important Region

A region of interest (ROI)-based compression method for medical image datasets is a requirement to maintain the quality of the diagnostically important region of the image. It is always a better option to compress the diagnostic important region in a lossless manner and the remaining portion of the image with a near-lossless compression method to achieve high compression efficiency without any compromise of quality. The predictive ROI-based compression on volumetric CT medical image is proposed in this paper; resolution-independent gradient edge detection (RIGED) and block adaptive arithmetic encoding (BAAE) are employed to ROI part for prediction and encoding that reduce the interpixel and coding redundancy. For the non-ROI portion, RIGED with an optimal threshold value, quantizer with optimal [Formula: see text]-level and BAAE with optimal block size are utilized for compression. The volumetric 8-bit and 16-bit standard CT image dataset is utilized for the evaluation of the proposed technique, and results are validated on real-time CT images collected from the hospital. Performance of the proposed technique in terms of BPP outperforms existing techniques such as JPEG 2000, M-CALIC, JPEG-LS, CALIC and JP3D by 20.31%, 19.87%, 17.77%, 15.58% and 13.66%, respectively.

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