Literature DB >> 9268841

An analytical look at the effects of compression on medical images.

K Persons1, P Palisson, A Manduca, B J Erickson, V Savcenko.   

Abstract

This article will take an analytical look at how lossy Joint Photographic Experts Group (JPEG) and wavelet image compression techniques affect medical image content. It begins with a brief explanation of how the JPEG and wavelet algorithms work, and describes in general terms what effect they can have on image quality (removal of noise, blurring, and artifacts). It then focuses more specifically on medical image diagnostic content and explains why subtle pathologies, that may be difficult for the human eye to discern because of low contrast, are generally very well preserved by these compression algorithms. By applying a wavelet decomposition to the whole image and to specific regions of interest (ROI), and by understanding how the lossy quantization step attenuates signals in those decomposition energy subbands, much can be learned about how tolerant various anatomical structures are to compression. High-frequency anatomical structures that have their energy represented by a few large coefficients (in the wavelet domain) will be well preserved, while, those structures with high frequency energy distributed over numerous smaller coefficients are the most vulnerable to compression. Digitized films showing subtle chest nodules, a subtle stress fracture, and CT and MR images are used to show these results.

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Year:  1997        PMID: 9268841      PMCID: PMC3452822          DOI: 10.1007/bf03168659

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  5 in total

1.  Image coding using wavelet transform.

Authors:  M Antonini; M Barlaud; P Mathieu; I Daubechies
Journal:  IEEE Trans Image Process       Date:  1992       Impact factor: 10.856

2.  JPEG compression of digital echocardiographic images: impact on image quality.

Authors:  T H Karson; S Chandra; A J Morehead; W J Stewart; S E Nissen; J D Thomas
Journal:  J Am Soc Echocardiogr       Date:  1995 May-Jun       Impact factor: 5.251

3.  The effects of lossy compression on the detection of subtle pulmonary nodules.

Authors:  G G Cox; L T Cook; M F Insana; M A McFadden; T J Hall; L A Harrison; D A Eckard; N L Martin
Journal:  Med Phys       Date:  1996-01       Impact factor: 4.071

4.  Evaluation of irreversible compression of digitized posterior-anterior chest radiographs.

Authors:  B J Erickson; A Manduca; K R Persons; F Earnest; T E Hartman; G F Harms; L R Brown
Journal:  J Digit Imaging       Date:  1997-08       Impact factor: 4.056

5.  Joint photographic experts group (JPEG) compatible data compression of mammograms.

Authors:  W F Good; G S Maitz; D Gur
Journal:  J Digit Imaging       Date:  1994-08       Impact factor: 4.056

  5 in total
  13 in total

1.  Ultrasound grayscale image compression with JPEG and wavelet techniques.

Authors:  K R Persons; P M Palisson; A Manduca; W J Charboneau; E M James; N T Charboneau; N J Hangiandreou; B J Erickson
Journal:  J Digit Imaging       Date:  2000-02       Impact factor: 4.056

2.  Wavelet compression on detection of brain lesions with magnetic resonance imaging.

Authors:  S Terae; K Miyasaka; K Kudoh; T Nambu; T Shimizu; K Kaneko; H Yoshikawa; R Kishimoto; T Omatsu; N Fujita
Journal:  J Digit Imaging       Date:  2000-11       Impact factor: 4.056

3.  Quality degradation in lossy wavelet image compression.

Authors:  Tzong-Jer Chen; Keh-Shih Chuang; Jay Wu; Sharon C Chen; Ing-Ming Hwang; Meei-Ling Jan
Journal:  J Digit Imaging       Date:  2003-10-02       Impact factor: 4.056

4.  Irreversible compression of medical images.

Authors:  Bradley J Erickson
Journal:  J Digit Imaging       Date:  2002-04-30       Impact factor: 4.056

5.  Lossy JPEG compression in quantitative angiography: the role of X-ray quantum noise.

Authors:  Johannes Peter Fritsch; Rüdiger Brennecke
Journal:  J Digit Imaging       Date:  2011-06       Impact factor: 4.056

Review 6.  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

7.  A blurring index for medical images.

Authors:  Tzong-Jer Chen; Keh-Shih Chuang; Jen-Hao Chang; Ya-Hui Shiao; Chun-Chao Chuang
Journal:  J Digit Imaging       Date:  2006-06       Impact factor: 4.056

8.  Challenges for pediatric radiology using computed radiography.

Authors:  C E Willis; B R Parker; M Orand; M L Wagner
Journal:  J Digit Imaging       Date:  1998-08       Impact factor: 4.056

9.  Perceived fidelity of compressed and reconstructed radiological images: a preliminary exploration of compression, luminance, and viewing distance.

Authors:  T K Pilgram; R M Slone; E Muka; J R Cox; G J Blaine
Journal:  J Digit Imaging       Date:  1998-11       Impact factor: 4.056

10.  The effects of compression on the image quality of digital panoramic radiographs.

Authors:  Füsun Yasar; Esra Yesilova; Burcu Apaydın
Journal:  Clin Oral Investig       Date:  2011-07-06       Impact factor: 3.573

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