Literature DB >> 20921928

Grading diabetic retinopathy severity from compressed digital retinal images compared with uncompressed images and film.

Helen K Li1, Jose F Florez-Arango, Larry D Hubbard, Adol Esquivel, Ronald P Danis, Elizabeth A Krupinski.   

Abstract

PURPOSE: To compare research grading of diabetic retinopathy (DR) severity level from compressed digital images versus uncompressed images and film.
METHODS: Compressed (JPEG2000, 37:1) digital images (C) were compared with uncompressed digital (U) and film (F) stereoscopic photographs from a 152-eye cohort with full-spectrum Early Treatment Diabetic Retinopathy Study severity levels for agreement on severity level, DR presence with ascending severity threshold, presence of DR index lesions, and repeatability of grading.
RESULTS: Classification of Early Treatment Diabetic Retinopathy Study severity levels from C images agreed substantially with results from F images (κ = 0.60, κ(w) [linear weighted] = 0.86) and uncompressed digital images (κ = 0.76, κ(w) = 0.92). For agreement of uncompressed digital versus F images, κ = 0.62 and κ(w) = 0.86. Distribution of Early Treatment Diabetic Retinopathy Study levels was not significantly different between C and F images (P = 0.09, Bhapkar's test for marginal homogeneity). For presence/absence of DR at 8 ascending severity thresholds, agreement between C and F was "almost perfect" (κ ≥ 0.8). Agreement on severity level between readers with C images was at least as good as that with uncompressed digital image or F. Repeatability of severity threshold grading between readers was similar using C or F images. For identifying individual DR lesions, agreement between C and F ranged from "moderate" to "perfect." Agreement of grading venous beading from C was slightly lower than from F.
CONCLUSION: Full Early Treatment Diabetic Retinopathy Study scale DR severity level grading using C images is comparable to that using U images or film.

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Year:  2010        PMID: 20921928     DOI: 10.1097/IAE.0b013e3181e3790b

Source DB:  PubMed          Journal:  Retina        ISSN: 0275-004X            Impact factor:   4.256


  7 in total

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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
Journal:  NPJ Digit Med       Date:  2020-03-23

3.  Imaging of diabetic retinopathy and diabetic macular edema.

Authors:  Ronald P Danis; Larry D Hubbard
Journal:  Curr Diab Rep       Date:  2011-08       Impact factor: 4.810

4.  Three principles for determining the relevancy of store-and-forward and live interactive telemedicine: reinterpreting two telemedicine research reviews and other research.

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Review 5.  Telemedicine for detecting diabetic retinopathy: a systematic review and meta-analysis.

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Review 6.  The English National Screening Programme for diabetic retinopathy 2003-2016.

Authors:  Peter H Scanlon
Journal:  Acta Diabetol       Date:  2017-02-22       Impact factor: 4.280

7.  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
  7 in total

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