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Proceedings Paper

Microaneurysms detection with the radon cliff operator in retinal fundus images
Author(s): Luca Giancardo; Fabrice Mériaudeau; Thomas P. Karnowski; Kenneth W. Tobin; Yaqin Li; Edward Chaum
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Paper Abstract

Diabetic Retinopathy (DR) is one of the leading causes of blindness in the industrialized world. Early detection is the key in providing effective treatment. However, the current number of trained eye care specialists is inadequate to screen the increasing number of diabetic patients. In recent years, automated and semi-automated systems to detect DR with color fundus images have been developed with encouraging, but not fully satisfactory results. In this study we present the initial results of a new technique for the detection and localization of microaneurysms, an early sign of DR. The algorithm is based on three steps: candidates selection, the actual microaneurysms detection and a final probability evaluation. We introduce the new Radon Cliff operator which is our main contribution to the field. Making use of the Radon transform, the operator is able to detect single noisy Gaussian-like circular structures regardless of their size or strength. The advantages over existing microaneurysms detectors are manifold: the size of the lesions can be unknown, it automatically distinguishes lesions from the vasculature and it provides a fair approach to microaneurysm localization even without post-processing the candidates with machine learning techniques, facilitating the training phase. The algorithm is evaluated on a publicly available dataset from the Retinopathy Online Challenge.

Paper Details

Date Published: 13 March 2010
PDF: 8 pages
Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 76230U (13 March 2010); doi: 10.1117/12.844442
Show Author Affiliations
Luca Giancardo, Oak Ridge National Lab. (United States)
Univ. de Bourgogne (France)
Fabrice Mériaudeau, Univ. de Bourgogne (France)
Thomas P. Karnowski, Oak Ridge National Lab. (United States)
Kenneth W. Tobin, Oak Ridge National Lab. (United States)
Yaqin Li, The Univ. of Tennessee Health Science Ctr. (United States)
Edward Chaum, The Univ. of Tennessee Health Science Ctr. (United States)


Published in SPIE Proceedings Vol. 7623:
Medical Imaging 2010: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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