Comparative study of retinal vessel segmentation methods on a new publicly available database
University Medical Center Utrecht · Vrije Universiteit Amsterdam · +2 more institutions
Abstract
In this work we compare the performance of a number of vessel segmentation algorithms on a newly constructed retinal vessel image database. Retinal vessel segmentation is important for the detection of numerous eye diseases and plays an important role in automatic retinal disease screening systems. A large number of methods for retinal vessel segmentation have been published, yet an evaluation of these methods on a common database of screening images has not been performed. To compare the performance of retinal vessel segmentation methods we have constructed a large database of retinal images. The database contains forty images in which the vessel trees have been manually segmented. For twenty of those forty…
Citation impact
- FWCI
- 11.23
- Percentile
- 100%
- References
- 14
Authors
5- MNMeindert NiemeijerCorresponding
University Medical Center Utrecht, Vrije Universiteit Amsterdam
- JSJoes Staal
University Medical Center Utrecht, Utrecht University
- BVBram van Ginneken
University Medical Center Utrecht, Utrecht University
- MLMarco Loog
Utrecht University, University Medical Center Utrecht
- MDMichael D. Abràmoff
Vrije Universiteit Amsterdam, University of Iowa, University Medical Center Utrecht
Topics & keywords
- Computer science
- Segmentation
- Artificial intelligence
- Upload
- Image segmentation
- Computer vision
- Pixel
- Pattern recognition (psychology)