Computer Aided Design for Diabetic Retinopathy

Fabrice Meriaudeau (1) , Désiré Sidibé (1) , Kedir Adal (1) , Sharib Ali (1) , Luca Giancardo (1) , T.P. Karnowski (2) , Edward Chaum (3)

1 Le2i - Laboratoire Electronique, Informatique et Image [UMR6306]
2 ORNL - Oak Ridge National Laboratory [Oak Ridge]
3 The Neuroscience Institute

Computer aided diagnosis and follow up can help in prevention and treatment of diabetes and its related complications. This paper presents a summary of the results we obtained over the last few years regarding the development of a CAD system for diabetic retinopathy. We present a methodology for diagnosis of DME based on exudates segmentation, as well as an automated detection of micro-aneurysm (MA) and DR diagnosis; Our approach uses standard available public database and shows a high power of generalization through cross database experiments.

Mots clés: retina imaging; blob detection; machine learning

Domaines: Traitement des images [eess.IV]

Fabrice Meriaudeau, Désiré Sidibé, Kedir Adal, Sharib Ali, Luca Giancardo, et al.. Computer Aided Design for Diabetic Retinopathy. QCAV2013, 11th International Conference on Quality Control by Artificial Vision, May 2013, Fukuoka, Japan. pp.241-247. ⟨hal-00831486⟩