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Automatic segmentation of corneal dystrophy on photographic images based on texture analysis
- Source :
- International Ophthalmology. 41:2695-2703
- Publication Year :
- 2021
- Publisher :
- Springer Science and Business Media LLC, 2021.
-
Abstract
- To develop an automatic algorithm to analyze dystrophic lesions on photographic images of corneal dystrophy. The dataset included 32 images of corneal dystrophy. The dystrophic area was manually segmented twice. Manually labeled dystrophy areas were compared with automatically segmented images. First, we manually removed the light reflex from the image of the cornea. Using an automatic approach, we extracted the brown color of the iris. Then, the program detected the circular region of the pupil and the corneal surface. A whitish dystrophy area was defined based on the image intensity on the iris and the pupil. The sliding square kernel was applied to clearly define the dystrophic region. For the manual analysis and the twice automatic approach, the Dice similarity was 0.804 and 0.801, respectively. The Pearson correlation coefficient was 0.807 and 0.806, respectively. The total number of distinct dystrophic areas showed no significant difference between the manual and automatic approaches according to the Wilcoxon signed-rank test (p
- Subjects :
- genetic structures
Iris
Corneal dystrophy
Texture (music)
Pupil
Cornea
03 medical and health sciences
symbols.namesake
0302 clinical medicine
medicine
Humans
Iris (anatomy)
Corneal Dystrophies, Hereditary
business.industry
Dystrophy
Pattern recognition
medicine.disease
eye diseases
Pearson product-moment correlation coefficient
Ophthalmology
medicine.anatomical_structure
030221 ophthalmology & optometry
symbols
Automatic segmentation
sense organs
Artificial intelligence
business
Algorithms
030217 neurology & neurosurgery
Subjects
Details
- ISSN :
- 15732630 and 01655701
- Volume :
- 41
- Database :
- OpenAIRE
- Journal :
- International Ophthalmology
- Accession number :
- edsair.doi.dedup.....ad30714b1a8d3d538d45f644020f87d2