Literature DB >> 23794433

Validating retinal fundus image analysis algorithms: issues and a proposal.

Emanuele Trucco1, Alfredo Ruggeri, Thomas Karnowski, Luca Giancardo, Edward Chaum, Jean Pierre Hubschman, Bashir Al-Diri, Carol Y Cheung, Damon Wong, Michael Abràmoff, Gilbert Lim, Dinesh Kumar, Philippe Burlina, Neil M Bressler, Herbert F Jelinek, Fabrice Meriaudeau, Gwénolé Quellec, Tom Macgillivray, Bal Dhillon.   

Abstract

This paper concerns the validation of automatic retinal image analysis (ARIA) algorithms. For reasons of space and consistency, we concentrate on the validation of algorithms processing color fundus camera images, currently the largest section of the ARIA literature. We sketch the context (imaging instruments and target tasks) of ARIA validation, summarizing the main image analysis and validation techniques. We then present a list of recommendations focusing on the creation of large repositories of test data created by international consortia, easily accessible via moderated Web sites, including multicenter annotations by multiple experts, specific to clinical tasks, and capable of running submitted software automatically on the data stored, with clear and widely agreed-on performance criteria, to provide a fair comparison.

Keywords:  fundus image analysis; reference standards; validation

Mesh:

Year:  2013        PMID: 23794433      PMCID: PMC4597487          DOI: 10.1167/iovs.12-10347

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


  81 in total

1.  Evaluation of a portable fundus camera for use in the teleophthalmologic diagnosis of glaucoma.

Authors:  K Yogesan; I J Constable; C J Barry; R H Eikelboom; W Morgan; M L Tay-Kearney; L Jitskaia
Journal:  J Glaucoma       Date:  1999-10       Impact factor: 2.503

2.  Automated segmentation of optic disc region on retinal fundus photographs: Comparison of contour modeling and pixel classification methods.

Authors:  Chisako Muramatsu; Toshiaki Nakagawa; Akira Sawada; Yuji Hatanaka; Takeshi Hara; Tetsuya Yamamoto; Hiroshi Fujita
Journal:  Comput Methods Programs Biomed       Date:  2010-05-23       Impact factor: 5.428

3.  Image structure clustering for image quality verification of color retina images in diabetic retinopathy screening.

Authors:  Meindert Niemeijer; Michael D Abràmoff; Bram van Ginneken
Journal:  Med Image Anal       Date:  2006-12       Impact factor: 8.545

4.  Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification.

Authors:  João V B Soares; Jorge J G Leandro; Roberto M Cesar Júnior; Herbert F Jelinek; Michael J Cree
Journal:  IEEE Trans Med Imaging       Date:  2006-09       Impact factor: 10.048

5.  Accuracy of ROPtool vs individual examiners in assessing retinal vascular tortuosity.

Authors:  David K Wallace; Sharon F Freedman; Zheen Zhao; Sin-Ho Jung
Journal:  Arch Ophthalmol       Date:  2007-11

6.  The efficacy of automated "disease/no disease" grading for diabetic retinopathy in a systematic screening programme.

Authors:  S Philip; A D Fleming; K A Goatman; S Fonseca; P McNamee; G S Scotland; G J Prescott; P F Sharp; J A Olson
Journal:  Br J Ophthalmol       Date:  2007-05-15       Impact factor: 4.638

7.  Computerized analysis of retinal vessel width and tortuosity in premature infants.

Authors:  Clare M Wilson; Kenneth D Cocker; Merrick J Moseley; Carl Paterson; Simon T Clay; William E Schulenburg; Monte D Mills; Anna L Ells; Kim H Parker; Graham E Quinn; Alistair R Fielder; Jeffrey Ng
Journal:  Invest Ophthalmol Vis Sci       Date:  2008-04-11       Impact factor: 4.799

8.  Automated detection and differentiation of drusen, exudates, and cotton-wool spots in digital color fundus photographs for diabetic retinopathy diagnosis.

Authors:  Meindert Niemeijer; Bram van Ginneken; Stephen R Russell; Maria S A Suttorp-Schulten; Michael D Abràmoff
Journal:  Invest Ophthalmol Vis Sci       Date:  2007-05       Impact factor: 4.799

9.  Level-set based automatic cup-to-disc ratio determination using retinal fundus images in ARGALI.

Authors:  D K Wong; J Liu; J H Lim; X Jia; F Yin; H Li; T Y Wong
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2008

10.  Evaluation of a system for automatic detection of diabetic retinopathy from color fundus photographs in a large population of patients with diabetes: response to Abramoff et al.

Authors:  John A Olson; Peter F Sharp; Alan Fleming; Sam Philip
Journal:  Diabetes Care       Date:  2008-08       Impact factor: 19.112

View more
  28 in total

1.  Automated segmentation of geographic atrophy of the retinal epithelium via random forests in AREDS color fundus images.

Authors:  Albert K Feeny; Mongkol Tadarati; David E Freund; Neil M Bressler; Philippe Burlina
Journal:  Comput Biol Med       Date:  2015-07-09       Impact factor: 4.589

2.  Quality evaluation of digital fundus images through combined measures.

Authors:  Diana Veiga; Carla Pereira; Manuel Ferreira; Luís Gonçalves; João Monteiro
Journal:  J Med Imaging (Bellingham)       Date:  2014-04-23

3.  Modulation of retinal image vasculature analysis to extend utility and provide secondary value from optical coherence tomography imaging.

Authors:  James R Cameron; Lucia Ballerini; Clare Langan; Claire Warren; Nicholas Denholm; Katie Smart; Thomas J MacGillivray
Journal:  J Med Imaging (Bellingham)       Date:  2016-05-02

4.  DR HAGIS-a fundus image database for the automatic extraction of retinal surface vessels from diabetic patients.

Authors:  Sven Holm; Greg Russell; Vincent Nourrit; Niall McLoughlin
Journal:  J Med Imaging (Bellingham)       Date:  2017-02-09

5.  Similarity regularized sparse group lasso for cup to disc ratio computation.

Authors:  Jun Cheng; Zhuo Zhang; Dacheng Tao; Damon Wing Kee Wong; Jiang Liu; Mani Baskaran; Tin Aung; Tien Yin Wong
Journal:  Biomed Opt Express       Date:  2017-07-20       Impact factor: 3.732

Review 6.  Crowdsourcing and Automated Retinal Image Analysis for Diabetic Retinopathy.

Authors:  Lucy I Mudie; Xueyang Wang; David S Friedman; Christopher J Brady
Journal:  Curr Diab Rep       Date:  2017-09-23       Impact factor: 4.810

7.  Tracking and diameter estimation of retinal vessels using Gaussian process and Radon transform.

Authors:  Masoud Elhami Asl; Navid Alemi Koohbanani; Alejandro F Frangi; Ali Gooya
Journal:  J Med Imaging (Bellingham)       Date:  2017-09-12

8.  Comparing humans and deep learning performance for grading AMD: A study in using universal deep features and transfer learning for automated AMD analysis.

Authors:  Philippe Burlina; Katia D Pacheco; Neil Joshi; David E Freund; Neil M Bressler
Journal:  Comput Biol Med       Date:  2017-01-27       Impact factor: 4.589

9.  Automated Grading of Age-Related Macular Degeneration From Color Fundus Images Using Deep Convolutional Neural Networks.

Authors:  Philippe M Burlina; Neil Joshi; Michael Pekala; Katia D Pacheco; David E Freund; Neil M Bressler
Journal:  JAMA Ophthalmol       Date:  2017-11-01       Impact factor: 7.389

Review 10.  Retinal imaging as a source of biomarkers for diagnosis, characterization and prognosis of chronic illness or long-term conditions.

Authors:  T J MacGillivray; E Trucco; J R Cameron; B Dhillon; J G Houston; E J R van Beek
Journal:  Br J Radiol       Date:  2014-06-17       Impact factor: 3.039

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.