Literature DB >> 11423452

Effect of digital image compression on screening for diabetic retinopathy.

R S Newsom1, A Clover, M T Costen, J Sadler, J Newton, A J Luff, C R Canning.   

Abstract

BACKGROUND/AIMS: Digital imaging is widely used for diabetic retinopathy screening. The storage and transmission of digital images can be facilitated by image compression. The authors aimed to assess the effect of image compression on the accuracy of grading diabetic retinopathy.
METHODS: Forty nine 35 mm transparencies (17 with no retinopathy, eight with background, five with preproliferative, and 19 with proliferative retinopathy) were digitised and subjected to JPEG compression by 90%, 80%, 70%, and 0%. The 196 images were randomised and graded on a portable computer. Two masked graders assessed the images for grade of retinopathy and image quality (0-10). The sensitivity and specificity of retinopathy grading were calculated with a weighted kappa for grading agreement between levels of compression.
RESULTS: The sensitivity of retinopathy grading was reduced by JPEG compression. At 90%, 80%, 70%, and 0% compression the sensitivities were 0.38, 0.50, 0.65, and 0.72, respectively; the specificity results were 1.00, 1.00, 0.83, and 0.84, respectively; and the weighted kappa scores were 0.60, 0.75, 0.77, and 0.84, respectively. The quality scores for 90%, 80%, 70%, 0% compression were 2.9 (SD 1.1, 95% CI; 2.7-3.2), 4.6 (SD 1.1, 95% CI; 3.0-5.6), 5.8 (SD1.5, 95% CI 5.0-6.6), 6.3 (SD1.4, 95% CI; 5.4-7.2) (p<0.01 for each intergroup comparison).
CONCLUSION: The results demonstrate significant loss of sensitivity to the features of diabetic retinopathy with JPEG compression; this was compounded by the thin film transistor (TFT) screen. The authors found the quality of uncompressed images on TFT screens too poor to give grading sensitivities which reach current guidelines for diabetic retinopathy screening.

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Year:  2001        PMID: 11423452      PMCID: PMC1724040          DOI: 10.1136/bjo.85.7.799

Source DB:  PubMed          Journal:  Br J Ophthalmol        ISSN: 0007-1161            Impact factor:   4.638


  19 in total

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4.  Resolution of retinal digital colour images.

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

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6.  JPEG quality transcoding using neural networks trained with a perceptual error measure.

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7.  World Wide Web interface to digital imaging and communication in medicine-capable image servers.

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8.  Towards the automatic interpretation of retinal images.

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9.  The use of digital cameras in a mobile retinal screening environment.

Authors:  D J Taylor; J Fisher; J Jacob; J E Tooke
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10.  Automatic detection of diabetic retinopathy using an artificial neural network: a screening tool.

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Journal:  Br J Ophthalmol       Date:  1996-11       Impact factor: 4.638

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  4 in total

1.  The effect of digital image resolution and compression on anterior eye imaging.

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2.  Technical and imaging factors influencing performance of deep learning systems for diabetic retinopathy.

Authors:  Michelle Y T Yip; Gilbert Lim; Zhan Wei Lim; Quang D Nguyen; Crystal C Y Chong; Marco Yu; Valentina Bellemo; Yuchen Xie; Xin Qi Lee; Haslina Hamzah; Jinyi Ho; Tien-En Tan; Charumathi Sabanayagam; Andrzej Grzybowski; Gavin S W Tan; Wynne Hsu; Mong Li Lee; Tien Yin Wong; Daniel S W Ting
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3.  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

4.  Technical and imaging factors influencing performance of deep learning systems for diabetic retinopathy.

Authors:  Michelle Y T Yip; Gilbert Lim; Zhan Wei Lim; Quang D Nguyen; Crystal C Y Chong; Marco Yu; Valentina Bellemo; Yuchen Xie; Xin Qi Lee; Haslina Hamzah; Jinyi Ho; Tien-En Tan; Charumathi Sabanayagam; Andrzej Grzybowski; Gavin S W Tan; Wynne Hsu; Mong Li Lee; Tien Yin Wong; Daniel S W Ting
Journal:  NPJ Digit Med       Date:  2020-03-23
  4 in total

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