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Use of iris pattern recognition to evaluate ocular torsional changes associated with head tilt

PURPOSE: To describe the use of enhanced iris images and a computer software program to quantify ocular torsional changes associated with head tilt. METHODS: Pixel coordinates of the pupil and different iris landmarks were obtained manually using paint program from digital images of the right and le...

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Detalles Bibliográficos
Autores principales: Hussein, Mohamed, Coats, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6202744/
https://www.ncbi.nlm.nih.gov/pubmed/30377680
http://dx.doi.org/10.1177/2515841418806492
Descripción
Sumario:PURPOSE: To describe the use of enhanced iris images and a computer software program to quantify ocular torsional changes associated with head tilt. METHODS: Pixel coordinates of the pupil and different iris landmarks were obtained manually using paint program from digital images of the right and left iris of 3 subjects with normal extraocular motility. Photographs of the right eye and of the left eye were taken in the straight-ahead position and at various degrees of right and left head tilt. A computer software program converted the x- and y-pixel coordinates into angles of rotation after averaging multiple points and determining the degree and the direction of torsion for each eye. The degree of head tilt was mathematically calculated from the digital images. The degree and the direction of ocular torsion were correlated with the degree and the direction of head tilt. RESULTS: The average degree of head tilt was 27.5 degrees (from 8 to 43 degrees). The average intorsion of the lower eye per degree of head tilt was 0.61 degrees (from 0.54 to 0.65 degrees). The average extorsion of the higher eye per degree of head tilt was 0.56 degrees (from 0.43 to 0.60 degrees). The average ocular torsional changes strongly correlated with the degree of head tilt (correlation coefficient = 0.92). CONCLUSIONS: Computer-assisted iris pattern recognition and analysis of the ocular torsional changes associated with head tilt may provide a useful and objective means of assessing ocular torsion.