Literature DB >> 9268903

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

B J Erickson1, A Manduca, K R Persons, F Earnest, T E Hartman, G F Harms, L R Brown.   

Abstract

The purpose of this article is to assess lossy image compression of digitized chest radiographs using radiologist assessment of anatomic structures and numerical measurements of image accuracy. Forty posterior-anterior (PA) chest radiographs were digitized and compressed using an irreversible wavelet technique at 10, 20, 40, and 80:1. These were presented in a blinded fashion with an uncompressed image for A-B comparison of 11 anatomic structures as well as overall quality assessments. Mean error, root-mean square (RMS) error, maximum pixel error, and number of pixels within 1% of original value were also computed for compression ratios from ratios from 5:1 to 80:1. We found that at low compression (10:1) there was a slight preference for compressed images. There was no significant difference at 20:1 and 40:1. There was a slight preference on some structures for the original compared with 80:1 compressed images. Numerical measures showed high image faithfulness, both in terms of number of pixels that were within 1% of their original value, and by the average error for all pixels. Our findings suggest that lossy compression at 40:1 or more can be used without perceptible loss in the representation of anatomic structures. On this finding, we will do a receiver-operator characteristic (ROC) analysis of nodule detection in lossy compressed images using 40:1 compression.

Mesh:

Year:  1997        PMID: 9268903      PMCID: PMC3452954          DOI: 10.1007/bf03168595

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


  6 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.  Irreversible data compression in chest imaging using computed radiography: an evaluation.

Authors:  T Mori; H Nakata
Journal:  J Thorac Imaging       Date:  1994       Impact factor: 3.000

3.  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

4.  The effect of irreversible image compression on diagnostic accuracy in thoracic imaging.

Authors:  D R Aberle; F Gleeson; J W Sayre; K Brown; P Batra; D A Young; B K Stewart; B K Ho; H K Huang
Journal:  Invest Radiol       Date:  1993-05       Impact factor: 6.016

5.  Clinical evaluation of irreversible image compression: analysis of chest imaging with computed radiography.

Authors:  T Ishigaki; S Sakuma; M Ikeda; Y Itoh; M Suzuki; S Iwai
Journal:  Radiology       Date:  1990-06       Impact factor: 11.105

6.  A new asymmetric screen-film combination for conventional chest radiography: evaluation in 50 patients.

Authors:  S J Swensen; J E Gray; L R Brown; G L Aughenbaugh; G F Harms; J Stears
Journal:  AJR Am J Roentgenol       Date:  1993-03       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.  A comparison of wavelet and Joint Photographic Experts Group lossy compression methods applied to medical images.

Authors:  T A Iyriboz; M J Zukoski; K D Hopper; P L Stagg
Journal:  J Digit Imaging       Date:  1999-05       Impact factor: 4.056

5.  Irreversible compression of medical images.

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

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

Authors:  K Persons; P Palisson; A Manduca; B J Erickson; V Savcenko
Journal:  J Digit Imaging       Date:  1997-08       Impact factor: 4.056

7.  Computed Tomography Image Compressibility and Limitations of Compression Ratio-Based Guidelines.

Authors:  Jean-François Pambrun; Rita Noumeir
Journal:  J Digit Imaging       Date:  2015-12       Impact factor: 4.056

8.  Performance and function of a desktop viewer at Mayo Clinic Scottsdale.

Authors:  W G Eversman; W Pavlicek; B Zavalkovskiy; B J Erickson
Journal:  J Digit Imaging       Date:  2000-05       Impact factor: 4.056

9.  Effect of CT image compression on computer-assisted lung nodule volume measurement.

Authors:  Jane P Ko; Jeffrey Chang; Elan Bomsztyk; James S Babb; David P Naidich; Henry Rusinek
Journal:  Radiology       Date:  2005-08-26       Impact factor: 11.105

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.