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Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
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Complex entropy based encryption and decryption technique for securing medical images.

Vinod Kumar1,2, Vinay Pathak3, Neelendra Badal4

  • 1Computers Science & Engineering Department, O P Jindal University, Raigarh, Chhattisgarh 496109 India.

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|August 1, 2022
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Summary
This summary is machine-generated.

This study introduces a novel visual encryption method for securing sensitive medical images during transmission and storage. The modified Arnold Map Encryption enhances image security and confidentiality, outperforming other algorithms in speed and pixel change rate.

Keywords:
DecryptionEncryptionMedical imageModified Arnold map encryptionNPCRSecurity

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Area of Science:

  • Medical Imaging
  • Information Security
  • Cryptography

Background:

  • Medical image security is paramount during transmission and storage due to sensitive patient data.
  • Existing methods like watermarking and digital signatures offer some protection, but robust encryption is crucial.
  • Transferring medical images over public networks necessitates advanced security measures to prevent unauthorized access.

Purpose of the Study:

  • To propose a visual encryption strategy for securing medical images before transmission or cloud storage.
  • To ensure unauthorized access to medical images is prevented, maintaining confidentiality.
  • To develop an encryption technique that is reversible without loss of information.

Main Methods:

  • A pixel shuffling-based encryption technique was employed.
  • A secret key was generated from the medical image itself.
  • Modified Arnold Map Encryption was utilized for image encryption and decryption, enhancing randomness and image entropy.

Main Results:

  • The proposed method successfully encrypted and decrypted medical images, preserving original data.
  • Modified Arnold Map Encryption demonstrated increased randomness and higher image entropy, making decryption more difficult for unauthorized parties.
  • Comparative analysis showed superior performance of Modified Arnold Map Encryption over algorithms like SHA-13, Hyper Chaotic, and various chaotic maps in terms of encryption speed and Number of Pixel Change Rate (NPCR).

Conclusions:

  • The developed visual encryption strategy effectively secures medical images, ensuring confidentiality and preventing unauthorized access.
  • Modified Arnold Map Encryption offers a robust and efficient solution for medical image protection.
  • The technique provides a valuable tool for safeguarding sensitive medical information in digital healthcare environments.