FEEDBACK ON A PUBLICLY DISTRIBUTED IMAGE DATABASE: THE MESSIDOR DATABASE

Authors

  • Etienne Decencière MINES ParisTech
  • Xiwei Zhang MINES ParisTech
  • Guy Cazuguel Télécom Bretagne
  • Bruno Lay ADCIS
  • Béatrice Cochener Brest University Hospital
  • Caroline Trone University Hospital of Saint-Etienne
  • Philippe Gain University Hospital of Saint-Etienne
  • Richard Ordonez MINES ParisTech
  • Pascale Massin Hôpital Lariboisière
  • Ali Erginay Hôpital Lariboisière
  • Béatrice Charton Centre de Ressources Informatiques de Haute-Normandie
  • Jean-Claude Klein MINES ParisTech

DOI:

https://doi.org/10.5566/ias.1155

Keywords:

diabetic retinopathy, image database, image processing, Messidor

Abstract

The Messidor database, which contains hundreds of eye fundus images, has been publicly distributed since 2008. It was created by the Messidor project in order to evaluate automatic lesion segmentation and diabetic retinopathy grading methods. Designing, producing and maintaining such a database entails significant costs. By publicly sharing it, one hopes to bring a valuable resource to the public research community. However, the real interest and benefit of the research community is not easy to quantify. We analyse here the feedback on the Messidor database, after more than 6 years of diffusion. This analysis should apply to other similar research databases.

References

bibitem[{Carmona emph{et~al.}(2008)Carmona, Rincón, García-Feijoó, and

Martínez-de-la Casa}]{carmona_identification_2008}

Carmona EJ, Rincón M, García-Feijoó J, Martínez-de-la Casa JM (2008).

newblock Identification of the optic nerve head with genetic algorithms.

newblock Artificial Intelligence in Medicine 43:243--59.

bibitem[{Decencière emph{et~al.}(2013)Decencière, Cazuguel, Zhang,

Thibault, Klein, Meyer, Marcotegui, Quellec, Lamard, Danno, Elie, Massin,

Viktor, Erginay, Laÿ, and Chabouis}]{decenciere_teleophta:_2013}

Decencière E, Cazuguel G, Zhang X, Thibault G, Klein JC, Meyer F, Marcotegui

B, Quellec G, Lamard M, Danno R, Elie D, Massin P, Viktor Z, Erginay A, Laÿ

B, Chabouis A (2013).

newblock {TeleOphta:} machine learning and image processing methods for

teleophthalmology.

newblock IRBM 34:196--203.

bibitem[{Giancardo emph{et~al.}(2012)Giancardo, Meriaudeau, Karnowski, Li,

Garg, Tobin~Jr., and Chaum}]{giancardo_exudate-based_2012}

Giancardo L, Meriaudeau F, Karnowski TP, Li Y, Garg S, Tobin~Jr. KW, Chaum E

(2012).

newblock Exudate-based diabetic macular edema detection in fundus images using

publicly available datasets.

newblock Medical Image Analysis 16:216--26.

bibitem[{Hoover emph{et~al.}(2000)Hoover, Kouznetsova, and

Goldbaum}]{hoover_locating_2000}

Hoover A, Kouznetsova V, Goldbaum M (2000).

newblock Locating blood vessels in retinal images by piecewise threshold

probing of a matched filter response.

newblock IEEE Transactions on Medical Imaging 19:203--10.

bibitem[{Kauppi emph{et~al.}(2007)Kauppi, Kalesnykiene, Kamarainen, Lensu,

Sorri, Raninen, Voutilainen, Uusitalo, Kälviäinen, and

Pietilä}]{kauppi_diaretdb1_2007}

Kauppi T, Kalesnykiene V, Kamarainen JK, Lensu L, Sorri I, Raninen A,

Voutilainen R, Uusitalo H, Kälviäinen H, Pietilä J (2007).

newblock The {DIARETDB1} diabetic retinopathy database and evaluation

protocol.

newblock In: British Machine Vision Conference.

bibitem[{Niemeijer emph{et~al.}(2010)Niemeijer, van Ginneken, Cree, Mizutani,

Quellec, Sanchez, Zhang, Hornero, Lamard, Muramatsu, Wu, Cazuguel, You, Mayo,

Li, Hatanaka, Cochener, Roux, Karray, Garcia, Fujita, and

Abramoff}]{niemeijer_retinopathy_2010}

Niemeijer M, van Ginneken B, Cree M, Mizutani A, Quellec G, Sanchez C, Zhang B,

Hornero R, Lamard M, Muramatsu C, Wu X, Cazuguel G, You J, Mayo A, Li Q,

Hatanaka Y, Cochener B, Roux C, Karray F, Garcia M, Fujita H, Abramoff M

(2010).

newblock Retinopathy online challenge: Automatic detection of microaneurysms

in digital color fundus photographs.

newblock IEEE Transactions on Medical Imaging 29:185--95.

bibitem[{Staal emph{et~al.}(2004)Staal, Abramoff, Niemeijer, Viergever, and

van Ginneken}]{staal_ridge-based_2004}

Staal J, Abramoff M, Niemeijer M, Viergever M, van Ginneken B (2004).

newblock Ridge-based vessel segmentation in color images of the retina.

newblock IEEE Transactions on Medical Imaging 23:501--9.

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Published

2014-08-26

Issue

Section

Short Research Communication

How to Cite

Decencière, E., Zhang, X., Cazuguel, G., Lay, B., Cochener, B., Trone, C., Gain, P., Ordonez, R., Massin, P., Erginay, A., Charton, B., & Klein, J.-C. (2014). FEEDBACK ON A PUBLICLY DISTRIBUTED IMAGE DATABASE: THE MESSIDOR DATABASE. Image Analysis and Stereology, 33(3), 231-234. https://doi.org/10.5566/ias.1155

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