A New Supervised Method for Blood Vessel Segmentation in Retinal Images by Using Gray-Level and Moment Invariants-Based Features
Indexed incrossrefpubmed
Abstract
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 performance on both sets of test images is better than other existing solutions in literature. The method proves especially accurate for vessel detection in STARE images. Its application to this database (even when the NN…
Citation impact
936
total citations
- FWCI
- 20.14
- Percentile
- 100%
- References
- 57
Citations per year
Authors
4Topics & keywords
Topics
Keywords
- Artificial intelligence
- Computer science
- Segmentation
- Robustness (evolution)
- Computer vision
- Pixel
- Pattern recognition (psychology)
- Image segmentation
UN Sustainable Development Goals
- Good health and well-being
No related works found for this paper.