A new deep learning method for blood vessel segmentation in retinal images based on convolutional kernels and modified U-Net model.

Journal: Computer methods and programs in biomedicine
Published Date: Apr 8, 2021

Abstract

BACKGROUND AND OBJECTIVE: Automatic monitoring of retinal blood vessels proves very useful for the clinical assessment of ocular vascular anomalies or retinopathies. This paper presents an efficient and accurate deep learning-based method for vessel segmentation in eye fundus images.

Authors

  • Manuel E Gegundez-Arias
    Vision, Prediction, Optimisation and Control Systems Department, Science and Technology Research Centre, University of Huelva, Avenida de las Fuerzas Armadas s/n, 21007, Huelva, Spain. Electronic address: gegundez@uhu.es.
  • Diego Marin-Santos
    Vision, Prediction, Optimisation and Control Systems Department, Science and Technology Research Centre, University of Huelva, Avenida de las Fuerzas Armadas s/n, 21007, Huelva, Spain. Electronic address: diego.marin@diesia.uhu.es.
  • Isaac Perez-Borrero
    Vision, Prediction, Optimisation and Control Systems Department, Science and Technology Research Centre, University of Huelva, Avenida de las Fuerzas Armadas s/n, 21007, Huelva, Spain. Electronic address: isaac.perez@dci.uhu.es.
  • Manuel J Vasallo-Vazquez
    Vision, Prediction, Optimisation and Control Systems Department, Science and Technology Research Centre, University of Huelva, Avenida de las Fuerzas Armadas s/n, 21007, Huelva, Spain. Electronic address: manuel.vasallo@diesia.uhu.es.

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