A New Supervised Method for Blood Vessel Segmentation in Retinal Images by Using Gray-Level and Moment Invariants-Based Features

@article{Marin2011ANS,
  title={A New Supervised Method for Blood Vessel Segmentation in Retinal Images by Using Gray-Level and Moment Invariants-Based Features},
  author={Diego Marin and Arturo Aquino and Manuel Emilio Geg{\'u}ndez-Arias and Jos{\'e} Manuel Bravo},
  journal={IEEE Transactions on Medical Imaging},
  year={2011},
  volume={30},
  pages={146-158}
}
This paper presents a new supervised method for blood vessel detection in digital retinal images. This method uses a neural network (NN) scheme for pixel classification and computes a 7-D vector composed of gray-level and moment invariants-based features for pixel representation. The method was evaluated on the publicly available DRIVE and STARE databases, widely used for this purpose, since they contain retinal images where the vascular structure has been precisely marked by experts. Method… CONTINUE READING

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SHOWING 1-10 OF 57 REFERENCES

Retinal Blood Vessel Segmentation Using Line Operators and Support Vector Classification

  • IEEE Transactions on Medical Imaging
  • 2007
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