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Cited by 389

The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.

Optic Nerve Head Segmentation

Open access
Lowell, J., Hunter, A., Steel, D., Basu, A., Ryder, R., Fletcher, E., Kennedy, L.·2004·IEEE Transactions on Medical Imaging

Abstract

Reliable and efficient optic disk localization and segmentation are important tasks in automated retinal screening. General-purpose edge detection algorithms often fail to segment the optic disk due to fuzzy boundaries, inconsistent image contrast or missing edge features. This paper presents an algorithm for the localization and segmentation of the optic nerve head boundary in low-resolution images (about 20 microns/pixel). Optic disk localization is achieved using specialized template matching, and segmentation by a deformable contour model. The latter uses a global elliptical model and a local deformable model with variable edge-strength dependent stiffness. The algorithm is evaluated against a randomly selected database of 100 images from a diabetic screening programme. Ten images were classified as unusable; the others were of variable quality. The localization algorithm succeeded on all bar one usable image; the contour estimation algorithm was qualitatively assessed by an ophthalmologist as having Excellent-Fair performance in 83% of cases, and performs well even on blurred images.

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Crossref · 10.1109/tmi.2003.823261

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Metadata

Authors
Lowell, J., Hunter, A., Steel, D., Basu, A., Ryder, R., Fletcher, E., & Kennedy, L.
Venue
IEEE Transactions on Medical Imaging
Published
2004-02
Volume
23
Issue
2
Pages
256-264
ISSN
0278-0062 (ISSN-L)
OpenAlex
W2170203892
Cited by
389
References
16
FWCI
6.15
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Optic Nerve Head Segmentation. https://app.cochat.ai/papers/10.1109/tmi.2003.823261
The paper
Lowell, J., Hunter, A., Steel, D., Basu, A., Ryder, R., Fletcher, E., & Kennedy, L. (2004). Optic Nerve Head Segmentation. IEEE Transactions on Medical Imaging. https://doi.org/10.1109/tmi.2003.823261

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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