Literature DB >> 17128888

An overview of digital compression of medical images: can we use lossy image compression in radiology?

David A Koff1, Harry Shulman.   

Abstract

The increasing volume of data generated by new imaging modalities such as multislice computed tomography scanners and magnetic resonance imaging justifies the use of lossy compression techniques to decrease the cost of storage and improve the efficiency of transmission over networks for teleradiology or for access to electronic patient records. We summarize here the most commonly used compression techniques and compare their main features. Having conducted an extensive literature review, we present a range of average compression ratios for different modalities and body parts. This article lays the groundwork for further evaluation with standardized statistical methods to ultimately elaborate acceptable compression guidelines.

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Year:  2006        PMID: 17128888

Source DB:  PubMed          Journal:  Can Assoc Radiol J        ISSN: 0846-5371            Impact factor:   2.248


  9 in total

1.  Improved pediatric MR imaging with compressed sensing.

Authors:  Shreyas S Vasanawala; Marcus T Alley; Brian A Hargreaves; Richard A Barth; John M Pauly; Michael Lustig
Journal:  Radiology       Date:  2010-06-07       Impact factor: 11.105

Review 2.  Compressed sensing MRI: a review of the clinical literature.

Authors:  Oren N Jaspan; Roman Fleysher; Michael L Lipton
Journal:  Br J Radiol       Date:  2015-09-24       Impact factor: 3.039

3.  Four-Dimensional Cone-Beam Computed Tomography Image Compression Using Video Encoder for Radiotherapy.

Authors:  Hui Yan; Yexiong Li; Jianrong Dai
Journal:  J Digit Imaging       Date:  2020-10       Impact factor: 4.056

4.  Exploring correlation information for image compression of four-dimensional computed tomography.

Authors:  Hui Yan; Yexiong Li; Jianrong Dai
Journal:  Quant Imaging Med Surg       Date:  2019-07

5.  Determining optimal medical image compression: psychometric and image distortion analysis.

Authors:  Alexander C Flint
Journal:  BMC Med Imaging       Date:  2012-07-31       Impact factor: 1.930

6.  Do we really need standards in digital image management?

Authors:  Elm Ho
Journal:  Biomed Imaging Interv J       Date:  2008-10-01

7.  Usability of irreversible image compression in radiological imaging. A position paper by the European Society of Radiology (ESR).

Authors: 
Journal:  Insights Imaging       Date:  2011-02-14

8.  Analysis of DICOM Image Compression Alternative Using Huffman Coding.

Authors:  Romi Fadillah Rahmat; T S M Andreas; Fahmi Fahmi; Muhammad Fermi Pasha; Mohammed Yahya Alzahrani; Rahmat Budiarto
Journal:  J Healthc Eng       Date:  2019-06-17       Impact factor: 2.682

9.  Evaluation of video compression methods for cone-beam computerized tomography.

Authors:  Hui Yan; Yexiong Li; Jianrong Dai
Journal:  J Appl Clin Med Phys       Date:  2019-05-09       Impact factor: 2.102

  9 in total

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