Optic Nerve Head Segmentation
| Autor: | Eric Fletcher, Lee Kennedy, Andrew Hunter, J. Lowell, R. Ryder, David H. W. Steel, Ansu Basu |
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| Rok vydání: | 2004 |
| Předmět: |
G740 Computer Vision
Computer science Optic Disk ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Optic disk Sensitivity and Specificity Edge detection Pattern Recognition Automated Ophthalmoscopy Image Interpretation Computer-Assisted medicine Humans Segmentation Computer vision Electrical and Electronic Engineering Diabetic Retinopathy Radiological and Ultrasound Technology Pixel medicine.diagnostic_test business.industry Template matching Reproducibility of Results Signal Processing Computer-Assisted Image segmentation Diabetic retinopathy medicine.disease Computer Science Applications Computer Science::Computer Vision and Pattern Recognition Head segmentation Optic nerve Artificial intelligence business Algorithms Software |
| Zdroj: | IEEE Transactions on Medical Imaging. 23:256-264 |
| ISSN: | 0278-0062 |
| Popis: | 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 /spl mu//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. |
| Databáze: | OpenAIRE |
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