Validating Retinal Fundus Image Analysis Algorithms: Issues and a Proposal

被引:112
作者
Trucco, Emanuele [1 ]
Ruggeri, Alfredo [2 ]
Karnowski, Thomas [3 ]
Giancardo, Luca [4 ]
Chaum, Edward [5 ]
Hubschman, Jean Pierre [6 ]
al-Diri, Bashir [7 ]
Cheung, Carol Y. [8 ]
Wong, Damon [9 ]
Abramoff, Michael [10 ,11 ,12 ,13 ]
Lim, Gilbert [14 ]
Kumar, Dinesh [15 ]
Burlina, Philippe [16 ]
Bressler, Neil M. [17 ]
Jelinek, Herbert F. [18 ]
Meriaudeau, Fabrice [19 ]
Quellec, Gwenole [20 ]
MacGillivray, Tom [21 ]
Dhillon, Bal [22 ]
机构
[1] Univ Dundee, Sch Comp, VAMPIRE Project, Dundee, Scotland
[2] Univ Padua, Dept Informat Engn, Padua, Italy
[3] Oak Ridge Natl Lab, Oak Ridge, TN USA
[4] Ist Italiano Tecnol, Genoa, Italy
[5] Univ Tennessee, Ctr Hlth Sci, Memphis, TN 38163 USA
[6] Jules Stein Eye Inst, Los Angeles, CA 90024 USA
[7] Lincoln Univ, REVIEW Grp, Lincoln, England
[8] Singapore Eye Res Inst, Singapore, Singapore
[9] ASTAR, Inst Infocomm Res, Singapore, Singapore
[10] Univ Iowa, Dept Ophthalmol & Visual Sci, Iowa City, IA USA
[11] Univ Iowa, Dept Elect & Comp Engn, Iowa City, IA 52242 USA
[12] Univ Iowa, Dept Biomed Engn, Iowa City, IA 52242 USA
[13] Iowa City VA Med Ctr, Dept Vet Affairs, Iowa City, IA USA
[14] Natl Univ Singapore, Sch Comp, Singapore 117548, Singapore
[15] RMIT Univ, Melbourne, Vic, Australia
[16] Johns Hopkins Univ, Appl Phys Lab, Laurel, MD USA
[17] Johns Hopkins Univ, Wilmer Eye Inst, Baltimore, MD 21218 USA
[18] Charles Sturt Univ, Albury, NSW, Australia
[19] Univ Burgundy, Le2i, Le Creusot, France
[20] INSERM, U1101, SFR ScInBioS, Brest, France
[21] Univ Edinburgh, Clin Res Imaging Ctr, VAMPIRE Project, Edinburgh, Midlothian, Scotland
[22] Univ Edinburgh, NHS Princess Alexandra Eye Pavil, VAMPIRE Project, Edinburgh, Midlothian, Scotland
基金
美国国家卫生研究院;
关键词
validation; fundus image analysis; reference standards; DIABETIC-RETINOPATHY; AUTOMATED DETECTION; MICROANEURYSM DETECTION; VESSEL SEGMENTATION; COST-EFFECTIVENESS; GLAUCOMA ANALYSIS; OPTIC DISK; CUP; DIAGNOSIS; PHOTOGRAPHS;
D O I
10.1167/iovs.12-10347
中图分类号
R77 [眼科学];
学科分类号
100212 ;
摘要
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.
引用
收藏
页码:3546 / 3559
页数:14
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