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Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...

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Authentication and self-correction in sequential MRI slices.

Vassilis Fotopoulos1, Maria L Stavrinou, Athanassios N Skodras

  • 1Department of Informatics, Computer Science, School of Science and Technology, Hellenic Open University, Tsamadou 13-15, 26222 Patras, Greece. vfotop1@eap.gr

Journal of Digital Imaging
|October 15, 2010
PubMed
Summary

This study explores hiding digital data within magnetic resonance imaging (MRI) slices. Regions of interest (ROI) can be concealed in regions of non-interest (RONI) for data security and tamper detection.

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Area of Science:

  • Medical Imaging
  • Information Technology
  • Data Security

Background:

  • Protecting digital medical files, datasets, and images is a growing challenge in healthcare IT.
  • Ensuring the integrity and authenticity of sensitive medical data is paramount.

Purpose of the Study:

  • To investigate the potential of magnetic resonance imaging (MRI) slice sequences for digital data hiding.
  • To explore the use of regions of non-interest (RONI) as cover for concealing regions of interest (ROI) within MRI slices.
  • To assess the data hiding capacity of entire MRI sequences.

Main Methods:

  • Utilizing MRI slice sequences for steganography.
  • Employing regions of non-interest (RONI) as the cover medium.
  • Analyzing the hiding capacity of the complete MRI sequence.

Main Results:

  • Demonstrated the feasibility of hiding digital data, specifically ROIs, within RONI of MRI slices.
  • Showcased the ability to detect ROI-targeted tampering attempts.
  • Established conditions for self-restoration of the original image by ROI extraction from RONI.

Conclusions:

  • MRI sequences offer a viable method for secure data embedding and authentication.
  • This technique enhances the security of medical images by enabling tamper detection and data recovery.
  • The proposed approach contributes to the protection of sensitive patient information within digital medical records.