Detección automática de vasos en retinografías

  1. S. Jiménez
  2. P. Alemany
  3. I. Fondón
  4. A. Foncubierta
  5. B. Acha
  6. C. Serrano
Revista:
Archivos de la Sociedad Española de Oftalmologia

ISSN: 0365-6691

Any de publicació: 2010

Volum: 85

Número: 3

Pàgines: 103-109

Tipus: Article

DOI: 10.4321/S0365-66912010000300003 DIALNET GOOGLE SCHOLAR lock_openAccés obert editor

Altres publicacions en: Archivos de la Sociedad Española de Oftalmologia

Resum

Purpose: The main purpose of the paper is to evaluate an automated method for blood vessels segmentation in color fundus images, due to its important role in the diagnosis of several pathologies such as diabetes. The final objective is to introduce the algorithm into a Computer Aided Diagnosis (CAD) tool that would be available in those local medical centers without specialists. Method: An automated method for blood vessels segmentation in color fundus images was implemented and tested. The algorithm starts with the extraction of vessel centerlines, which are used as guidelines for the subsequent vessel filling phase. The outputs of four directional differential operators are processed in order to select connected sets of candidate points to be further classified as centerline pixels using vessel derived features. The final segmentation is obtained using an iterative region growing method that integrates the contents of several binary images, resulting from vessel width dependent morphological filters. The method was evaluated using the images of two publicly available databases (STARE and DRIVE) and a database with 24 images. Results: The algorithm outperforms other published algorithms and approximates the average accuracy of a human observer without a significant degradation of sensitivity and specificity. In addition, results have been subject to the experts´ valuation that they think that retinal vessels remain represented with valuable accuracy on having analyzed the test´s images. Conclusion: Due to the good segmentation results, the algorithm proposed could be implemented as part of a complete CAD tool in the local medical centers. This would reduce cost and diagnosis time.

Referències bibliogràfiques

  • Fong, DS, Aiello, L, Gardner, TW, King, GL, Blankenship, G, Cavallerano, JD. (2003). Diabetic retinopathy. Diabetes Care. 26. 226
  • Wilson, C, Horton, M, Cavallerano, J, Aiello, LM. (2005). Addition of primary care-based retinal imaging technology to an existing eye care professional referral program increased the rate of surveillance and treatment of diabetic retinopathy. Diabetes Care. 28. 318
  • Wilkinson, CP, Ferris, FL III, Klein, RE, Lee, PP, Agardh, CD, Davis, M. (2003). Proposed International Clinical Diabetic Retinopathy and Diabetic Macular Edema Disease Severity Scales. Ophthalmology.. 110. 1677
  • Niemeijer, M, Abramoff, MD, Van Ginneken, B. (2009). Information Fusion for Diabetic Retinopathy CAD in Digital Color Fundus Photographs. IEEE Transactions on Medical Imaging. 28. 775
  • Mendonça, AM, Campilho, A. (2006). Segmentation of Retinal Blood Vessels by Combining the Detection of Centerlines and Morphological Reconstruction. IEEE Transactions On Medical Imaging. 25. 1200
  • Staal, JJ, Abramoff, MD, Niemeijer, M, Viergever, MA, Van Ginneken, B. (2004). Ridge based vessel segmentation in color images of the retina. IEEE Transactions on Medical Imaging. 23. 501
  • Hoover, A. (2000). Locating Blood Vessels in Retinal Images by Piecewise Threhsold Probing of a Matched Filter Response. IEEE Transactions on Medical Imaging. 19. 203
  • Chaudhuri, S, Chatterjee, S, Katz, N, Nelson, M, Goldbaum, M. (1989). Detection of blood vessels in retinal images using two-dimensional matched filters. IEEE Transactions on Medical Imaging. 8. 263
  • Jiang, X, Mojon, D. (2003). Adaptive local thresholding by verification-based multithreshold probing with application to vessel detection in retinal images. IEEE Transactions on Pattern Analysis and Machine Intelligence. 25. 131
  • Martínez-Pérez, M, Hughes, A, Stanton, A, Thom, S, Bharath, A, Parker, K. (1999). Scale-space analysis for the characterisation of retinal blood vessels: Medical Image Computing and Computer-Assisted Intervention - MICCAI´99. 90
  • Niemeijer, M, Staal, JJ, Van Ginneken, B, Loog, M, Abramoff, MD. (2004). Comparative study of retinal vessel segmentation methods on a new publicly available database. SPIE Medical Imaging SPIE.. 5370. 648
Fuente de los datos: Dialnet