Abstract | ||
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Hyperaemia is an excess of blood in a tissue that causes the appearance of an unusual red hue in the affected area. It is a common occurrence in the bulbar conjunctiva, where it can be related to multiple pathologies, such as conjunctivitis or dry eye syndrome. Specialists grade hyperaemia by means of a tedious, subjective, non-repeatable and time-consuming process. These drawbacks can be solved with the automatisation of the process by means of image processing techniques. The automatic segmentation of the conjunctiva is an important part of the process, as it ensures the absence of noise in posterior stages of the methodology. However, there are several issues of illumination and focus in the input videos that difficult the process. In this work, several segmentation algorithms are proposed and compared in order to obtain an accurate location of the bulbar conjunctiva. |
Year | DOI | Venue |
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2018 | 10.1007/s10044-017-0658-z | Pattern Anal. Appl. |
Keywords | Field | DocType |
Image processing,Medical imaging,Optometry,Dry eye syndrome,Hyperaemia grading | Hyperaemia,Multiple pathologies,Pattern recognition,Conjunctiva,Segmentation,Medical imaging,Image processing,Hue,Bulbar conjunctiva,Artificial intelligence,Mathematics | Journal |
Volume | Issue | ISSN |
21 | 2 | 1433-7541 |
Citations | PageRank | References |
0 | 0.34 | 12 |
Authors | ||
5 |
Name | Order | Citations | PageRank |
---|---|---|---|
L Sánchez | 1 | 0 | 1.35 |
Noelia Barreira-Rodríguez | 2 | 1 | 1.38 |
Antonio Mosquera González | 3 | 115 | 16.72 |
Hugo Pena-Verdeal | 4 | 3 | 2.52 |
E. Yebra-Pimentel | 5 | 23 | 4.64 |