access icon free Achieving a reversible lower dimensionality transformation for picture archiving and communication system in healthcare

With the progression of picture archiving and communication systems (PACSs) over the past decade, it has become imperative that such systems be optimised in security, storage, and transmission aspects. The work presented in this Letter shows a framework for medical image compression and secure image transmission for PACSs. The work aims to achieve a lower dimensionality of input medical image signified by a high-compression ratio, a secure image transmission that can withstand adversarial attacks and provide a reversible reconstruction with minimal error. The authors illustrate that sinusoid modulated Gaussian texture maps, multi-level chaotic maps, and high-frequency image maps can be efficiently fused and utilised in a deep learning architecture. The overall analysis depicts promising results with regard to the capability of image compression, security, and transmission. The proposed framework will be a potential candidate for use in PACSs, which effectively is the backbone of the current healthcare paradigm.

Inspec keywords: neural net architecture; image texture; security of data; visual communication; data compression; PACS; image coding; medical image processing; health care; Gaussian processes; learning (artificial intelligence)

Other keywords: picture archiving and communication systems; reversible lower dimensionality transformation; transmission aspects; deep learning architecture; secure image transmission; multilevel chaotic maps; health care; medical image compression; sinusoid modulated Gaussian texture maps; reversible reconstruction; high-compression ratio; high-frequency image maps; input medical image; PACS; adversarial attacks

Subjects: Other topics in statistics; Image and video coding; Biomedical communication; Computer vision and image processing techniques; Neural computing techniques; Data security; Biology and medical computing; Other topics in statistics

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