Literature DB >> 10845617

Methods and limits of digital image compression of retinal images for telemedicine.

R H Eikelboom1, K Yogesan, C J Barry, I J Constable, M L Tay-Kearney, L Jitskaia, P H House.   

Abstract

PURPOSE: To investigate image compression of digital retinal images and the effect of various levels of compression on the quality of the images.
METHODS: JPEG (Joint Photographic Experts Group) and Wavelet image compression techniques were applied in five different levels to 11 eyes with subtle retinal abnormalities and to 4 normal eyes. Image quality was assessed by four different methods: calculation of the root mean square (RMS) error between the original and compressed image, determining the level of arteriole branching, identification of retinal abnormalities by experienced observers, and a subjective assessment of overall image quality. To verify the techniques used and findings, a second set of retinal images was assessed by calculation of RMS error and overall image quality.
RESULTS: Plots and tabulations of the data as a function of the final image size showed that when the original image size of 1.5 MB was reduced to 29 KB using JPEG compression, there was no serious degradation in quality. The smallest Wavelet compressed images in this study (15 KB) were generally still of acceptable quality.
CONCLUSIONS: For situations where digital image transmission time and costs should be minimized, Wavelet image compression to 15 KB is recommended, although there is a slight cost of computational time. Where computational time should be minimized, and to remain compatible with other imaging systems, the use of JPEG compression to 29 KB is an excellent alternative.

Entities:  

Mesh:

Year:  2000        PMID: 10845617

Source DB:  PubMed          Journal:  Invest Ophthalmol Vis Sci        ISSN: 0146-0404            Impact factor:   4.799


  6 in total

1.  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

2.  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

3.  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

4.  Concordance between SIVA, IVAN, and VAMPIRE Software Tools for Semi-Automated Analysis of Retinal Vessel Caliber.

Authors:  Thibaud Mautuit; Pierre Cunnac; Carol Y Cheung; Tien Y Wong; Stephen Hogg; Emanuele Trucco; Vincent Daien; Thomas J MacGillivray; José Labarère; Christophe Chiquet
Journal:  Diagnostics (Basel)       Date:  2022-05-25

5.  Retinal video recordings at different compression levels: a novel video-based imaging technology for diabetic retinopathy screening.

Authors:  D S W Ting; M L Tay-Kearney; I Constable; J Vignarajan; Y Kanagasingam
Journal:  Eye (Lond)       Date:  2013-05-10       Impact factor: 3.775

6.  Mutual Information Correlation with Human Vision in Medical Image Compression.

Authors:  Li-Hui Lin; Tzong-Jer Chen
Journal:  Curr Med Imaging Rev       Date:  2018-02
  6 in total

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