IEEE transactions on medical imaging, 2008-02, Vol.27 (2), p.237-246
2008
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Details
- Autor(en) / Beteiligte
- Titel
- A Novel Vessel Segmentation Algorithm for Pathological Retina Images Based on the Divergence of Vector Fields
- Ist Teil von
- IEEE transactions on medical imaging, 2008-02, Vol.27 (2), p.237-246
- Ort / Verlag
- United States: IEEE
- Erscheinungsjahr
- 2008
- Quelle
- IEEE Electronic Library (IEL)
- Beschreibungen/Notizen
- In this paper, a method is proposed for detecting blood vessels in pathological retina images. In the proposed method, blood vessel-like objects are extracted using the Laplacian operator and noisy objects are pruned according to the centerlines, which are detected using the normalized gradient vector field. The method has been tested with all the pathological retina images in the publicly available STARE database. Experiment results show that the method can avoid detecting false vessels in pathological regions and can produce reliable results for healthy regions.
- Sprache
- Englisch
- Identifikatoren
- ISSN: 0278-0062eISSN: 1558-254XDOI: 10.1109/TMI.2007.909827Titel-ID: cdi_pubmed_primary_18334445
- Format
- –
- Schlagworte
- Algorithms, Artificial Intelligence, Biomedical imaging, Biomedical optical imaging, Blood vessel segmentation, Blood vessels, Cluster Analysis, gradient vector field, Humans, Image Enhancement - methods, Image Interpretation, Computer-Assisted - methods, Image segmentation, Imaging, Three-Dimensional - methods, Laplace equations, Matched filters, Object detection, Optical noise, Pathology, Pattern Recognition, Automated - methods, Reproducibility of Results, Retina, retina image analysis, Retinal Diseases - pathology, Retinal Vessels - pathology, Retinoscopy - methods, Sensitivity and Specificity