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February 28, 2026International Journal of Image and Graphics0 citations

Efficient Compression Techniques for Medical Image Storage and Transmission: A Comprehensive Review

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BKBhavana Kaushik

Key Points

  • The aim is to evaluate various compression techniques for medical images, focusing on their effectiveness in storage and transmission.
  • Conducted a qualitative review of existing image compression techniques.
  • Analyzed methods for 2D and 3D medical images.
  • Assessed features and limitations of hybrid compression procedures.
  • Discussed practical challenges in compressing grayscale images.
  • Identified several hybrid compression techniques that improve storage efficiency.
  • Highlighted the trade-off between compression rates and image fidelity.
  • Discussed challenges faced in diagnostic accuracy due to compression.

Abstract

In the field of medical imaging, there is a strong requirement for the storage of an immense volume of digitized medical image data. The digital image must be compressed heavily before storing and transferring it because of having restricted bandwidth and scope of storage. When compression of images is done at a lower bit rate it reduces the image fidelity that results in a drop in quality but poses many challenges to overcome and prevents diagnostic miscalculations with great compression rates for reduced storage and quick transmission. To overcome this challenging issue several hybrid efficient compression procedures solely for medical digital images have been introduced in recent years. The transformation of image, quantization, and encoding is part of image compression. This paper presents a qualitative and comprehensive review of image compression techniques for two-dimensional (2D) still and three-dimensional (3D) medical images. The features and constraints associated with various compression methods for compressing grayscale images are reviewed and discussed in this paper. In-depth reviews of the practical concerns and difficulties in the medical scan compression arena are provided.

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Cite This Study

Bhavana Kaushik (2024) studied this question.

synapsesocial.com/papers/69a288590a974eb0d3c0429fhttps://doi.org/10.1142/s0219467826500245
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Context-based, adaptive, lossless image coding1997 · 987 citations
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  5. 5Diagnostically lossless medical image compression via wavelet-based background noise removal2000 · 3 citations