Literature DB >> 10342156

A comparison of wavelet and Joint Photographic Experts Group lossy compression methods applied to medical images.

T A Iyriboz1, M J Zukoski, K D Hopper, P L Stagg.   

Abstract

This presentation focuses on the quantitative comparison of three lossy compression methods applied to a variety of 12-bit medical images. One Joint Photographic Exports Group (JPEG) and two wavelet algorithms were used on a population of 60 images. The medical images were obtained in Digital Imaging and Communications in Medicine (DICOM) file format and ranged in matrix size from 256 x 256 (magnetic resonance [MR]) to 2,560 x 2,048 (computed radiography [CR], digital radiography [DR], etc). The algorithms were applied to each image at multiple levels of compression such that comparable compressed file sizes were obtained at each level. Each compressed image was then decompressed and quantitative analysis was performed to compare each compressed-then-decompressed image with its corresponding original image. The statistical measures computed were sum of absolute differences, sum of squared differences, and peak signal-to-noise ratio (PSNR). Our results verify other research studies which show that wavelet compression yields better compression quality at constant compressed file sizes compared with JPEG. The DICOM standard does not yet include wavelet as a recognized lossy compression standard. For implementers and users to adopt wavelet technology as part of their image management and communication installations, there has to be significant differences in quality and compressibility compared with JPEG to justify expensive software licenses and the introduction of proprietary elements in the standard. Our study shows that different wavelet implementations vary in their capacity to differentiate themselves from the old, established lossy JPEG.

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Mesh:

Year:  1999        PMID: 10342156      PMCID: PMC3452914          DOI: 10.1007/BF03168745

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


  6 in total

1.  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

2.  Wavelet versus JPEG (Joint Photographic Expert Group) and fractal compression. Impact on the detection of low-contrast details in computed radiographs.

Authors:  J Ricke; P Maass; E Lopez Hänninen; T Liebig; H Amthauer; C Stroszczynski; W Schauer; T Boskamp; M Wolf
Journal:  Invest Radiol       Date:  1998-08       Impact factor: 6.016

Review 3.  Wavelet compression of medical images.

Authors:  B J Erickson; A Manduca; P Palisson; K R Persons; F Earnest; V Savcenko; N J Hangiandreou
Journal:  Radiology       Date:  1998-03       Impact factor: 11.105

4.  Introduction to wavelet-based compression of medical images.

Authors:  D F Schomer; A A Elekes; J D Hazle; J C Huffman; S K Thompson; C K Chui; W A Murphy
Journal:  Radiographics       Date:  1998 Mar-Apr       Impact factor: 5.333

5.  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

6.  Application of wavelet compression to digitized radiographs.

Authors:  M A Goldberg; M Pivovarov; W W Mayo-Smith; M P Bhalla; J G Blickman; R T Bramson; G W Boland; H J Llewellyn; E Halpern
Journal:  AJR Am J Roentgenol       Date:  1994-08       Impact factor: 3.959

  6 in total
  9 in total

1.  Diagnostic accuracy of film-based, TIFF, and wavelet compressed digital temporomandibular joint images.

Authors:  C J Trapnell; W C Scarfe; J H Cook; A M Silvejra; F J Regennitter; B S Haskell
Journal:  J Digit Imaging       Date:  2000-02       Impact factor: 4.056

2.  Image compression and chest radiograph interpretation: image perception comparison between uncompressed chest radiographs and chest radiographs stored using 10:1 JPEG compression.

Authors:  D P Beall; P D Shelton; T V Kinsey; M C Horton; B J Fortman; S Achenbach; V Smirnoff; D L Courneya; B Carpenter; J T Gironda
Journal:  J Digit Imaging       Date:  2000-05       Impact factor: 4.056

3.  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

4.  Effect of digital image compression on screening for diabetic retinopathy.

Authors:  R S Newsom; A Clover; M T Costen; J Sadler; J Newton; A J Luff; C R Canning
Journal:  Br J Ophthalmol       Date:  2001-07       Impact factor: 4.638

5.  Visually lossless threshold determination for microcalcification detection in wavelet compressed mammograms.

Authors:  O Kocsis; L Costaridou; L Varaki; E Likaki; C Kalogeropoulou; S Skiadopoulos; G Panayiotakis
Journal:  Eur Radiol       Date:  2003-02-15       Impact factor: 5.315

6.  JPEG2000 for automated quantification of immunohistochemically stained cell nuclei: a comparative study with standard JPEG format.

Authors:  Marylène Lejeune; Carlos López; Ramón Bosch; Anna Korzyńska; Maria-Teresa Salvadó; Marcial García-Rojo; Urszula Neuman; Łukasz Witkowski; Jordi Baucells; Joaquín Jaén
Journal:  Virchows Arch       Date:  2010-11-18       Impact factor: 4.064

7.  Quality of compressed medical images.

Authors:  Ya-Hui Shiao; Tzong-Jer Chen; Keh-Shih Chuang; Cheng-Hsun Lin; Chun-Chao Chuang
Journal:  J Digit Imaging       Date:  2007-02-22       Impact factor: 4.056

8.  Pan-Canadian evaluation of irreversible compression ratios ("lossy" compression) for development of national guidelines.

Authors:  David Koff; Peter Bak; Paul Brownrigg; Danoush Hosseinzadeh; April Khademi; Alex Kiss; Luigi Lepanto; Tracy Michalak; Harry Shulman; Andrew Volkening
Journal:  J Digit Imaging       Date:  2008-10-18       Impact factor: 4.056

9.  JPEG2000 still image coding quality.

Authors:  Tzong-Jer Chen; Sheng-Chieh Lin; You-Chen Lin; Ren-Gui Cheng; Li-Hui Lin; Wei Wu
Journal:  J Digit Imaging       Date:  2013-10       Impact factor: 4.056

  9 in total

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