Literature DB >> 19513963

Image data compression in diagnostic imaging: international literature review and workflow recommendation.

R Braunschweig1, I Kaden, J Schwarzer, C Sprengel, K Klose.   

Abstract

PURPOSE: Today healthcare policy is based on effectiveness. Diagnostic imaging became a "pacesetter" due to amazing technical developments (e. g. multislice CT), extensive data volumes, and especially the well defined workflow-orientated scenarios on a local and (inter)national level. To make centralized networks sufficient, image data compression has been regarded as the key to a simple and secure solution. In February 2008 specialized working groups of the DRG held a consensus conference. They designed recommended data compression techniques and ratios. MATERIAL AND
METHOD: The purpose of our paper is an international review of the literature of compression technologies, different imaging procedures (e. g. DR, CT etc.), and targets (abdomen, etc.) and to combine recommendations for compression ratios and techniques with different workflows. The studies were assigned to 4 different levels (0 - 3) according to the evidence. 51 studies were assigned to the highest level 3.
RESULTS: We recommend a compression factor of 1 : 8 (excluding cranial scans 1:5). For workflow reasons data compression should be based on the modalities (CT, etc.). PACS-based compression is currently possible but fails to maximize workflow benefits. Only the modality-based scenarios achieve all benefits.
CONCLUSION: Imaging equipment manufacturers are encouraged to improve the compression technology of their imaging devices (e. g. freely selectable compression ratios in the output filter). Double compression should be strictly avoided. Lossless compression formats should be switched off.

Mesh:

Year:  2009        PMID: 19513963     DOI: 10.1055/s-0028-1109341

Source DB:  PubMed          Journal:  Rofo        ISSN: 1438-9010


  6 in total

1.  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

2.  [Irreversible image compression in radiology. Current status].

Authors:  D Pinto dos Santos; F Jungmann; C Friese; C Düber; P Mildenberger
Journal:  Radiologe       Date:  2013-03       Impact factor: 0.635

3.  The impact of irreversible image data compression on post-processing algorithms in computed tomography.

Authors:  Daniel Pinto Dos Santos; Conrad Friese; Jan Borggrefe; Peter Mildenberger; Aline Mähringer-Kunz; Roman Kloeckner
Journal:  Diagn Interv Radiol       Date:  2020-01       Impact factor: 2.630

4.  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

5.  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

6.  Imaging file management to support international telepathology.

Authors:  Liron Pantanowitz; Jeffrey McHugh; William Cable; Chengquan Zhao; Anil V Parwani
Journal:  J Pathol Inform       Date:  2015-03-24
  6 in total

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