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<p>Objectives: Medical image analysis is essential for quick and accurate diagnosis and treatment. Nowadays, the uses of medical images for the treatment of patients and diagnosis purposes are sent over the internet. So, they should be protected from cyber attackers. These medical images are sensitive to any minor changes, and the data volume is rapidly increasing. Thus, security and storage costs must be considered in medical images. Traditional encryption and compression methods are ineffective for encrypting medical images due to their high execution time and algorithm complexity. Methods: This paper proposes a novel 2D chaotic map and generates the GS sequence in the multiple-order fractional quaternion Hahn moments matrix for generating encryption keys and improving security. The proposed algorithm uses the 2D chaotic map to generate the private key and diffusion process. The pixel values of the original images in the proposed schemes are shuffled using Mersenne Twister (MT) to improve the security of medical images. In this proposed scheme, the Differential Huffman Compression (DHC) method is used for lossless compression while performing XOR-based encryption. Findings: The proposed model has been tested on different color medical images, namely the Computed Tomography (CT) dataset, and Magnetic Resonance Imaging (MRI) dataset. It has been evaluated using performance metrics, such as entropy, key space, histogram analysis, key sensitivity, robustness analysis, correlation, and similarity analysis. The outcomes demonstrate that the proposed scheme is more effective than the other comparable schemes. Novelty: This research pioneers the study of innovative medical image security and compression techniques, married with methods development based on multiple-order fractional quaternion Hahn moments, 2D-Chaotic Map, and DHC for handling the storage cost of medical images. Our findings highlight a crucial aspect of healthcare namely the secure and efficient transfer of medical data, specifically between the radiology department and radiologists. This is vital for patient care, diagnostic accuracy, and maintaining data privacy.</p>

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A novel medical image security and compression based on multiple-order fractional quaternion Hahn moments and 2D-chaotic map

  • 期刊论文

  • 发表日期：

    2025年8月5日

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  • Omar El Ogri,
  • Jaouad EL-Mekkaoui,
  • Mohamed Benslimane

摘要

Objectives: Medical image analysis is essential for quick and accurate diagnosis and treatment. Nowadays, the uses of medical images for the treatment of patients and diagnosis purposes are sent over the internet. So, they should be protected from cyber attackers. These medical images are sensitive to any minor changes, and the data volume is rapidly increasing. Thus, security and storage costs must be considered in medical images. Traditional encryption and compression methods are ineffective for encrypting medical images due to their high execution time and algorithm complexity. Methods: This paper proposes a novel 2D chaotic map and generates the GS sequence in the multiple-order fractional quaternion Hahn moments matrix for generating encryption keys and improving security. The proposed algorithm uses the 2D chaotic map to generate the private key and diffusion process. The pixel values of the original images in the proposed schemes are shuffled using Mersenne Twister (MT) to improve the security of medical images. In this proposed scheme, the Differential Huffman Compression (DHC) method is used for lossless compression while performing XOR-based encryption. Findings: The proposed model has been tested on different color medical images, namely the Computed Tomography (CT) dataset, and Magnetic Resonance Imaging (MRI) dataset. It has been evaluated using performance metrics, such as entropy, key space, histogram analysis, key sensitivity, robustness analysis, correlation, and similarity analysis. The outcomes demonstrate that the proposed scheme is more effective than the other comparable schemes. Novelty: This research pioneers the study of innovative medical image security and compression techniques, married with methods development based on multiple-order fractional quaternion Hahn moments, 2D-Chaotic Map, and DHC for handling the storage cost of medical images. Our findings highlight a crucial aspect of healthcare namely the secure and efficient transfer of medical data, specifically between the radiology department and radiologists. This is vital for patient care, diagnostic accuracy, and maintaining data privacy.