title: Quantitative assessment of corneal vibrations during intraocular pressure measurement with the air-puff method in patients with keratoconus.
abstract: BACKGROUND
  One of the current methods for measuring intraocular pressure is the air-puff method. A tonometer which uses this method is the Corvis device. With the ultra-high-speed (UHS) Scheimpflug camera, it is also possible to observe corneal deformation during measurement. The use of modern image analysis and processing methods allows for analysis of higher harmonics of corneal deflection above 100 Hz.
  
  
  METHODS
  493 eyes of healthy subjects and 279 eyes of patients with keratoconus were used in the measurements. For each eye, 140 corneal deformation images were recorded during intraocular pressure measurement. Each image was recorded every 230 µs and had a resolution of 200 × 576 pixels. A new, original algorithm for image analysis and processing has been proposed. It enables to separate the eyeball reaction as well as low-frequency and high-frequency corneal deformations from the eye response to an air puff. Furthermore, a method for classification of healthy subjects and patients with keratoconus based on decision trees has been proposed.
  
  
  RESULTS
  The obtained results confirm the possibility to distinguish between patients with keratoconus and healthy subjects. The features used in this classification are directly related to corneal vibrations. They are only available in the proposed software and provide specificity of 98%, sensitivity-85%, and accuracy-92%. This confirms the usefulness of the proposed method in this type of classification that uses corneal vibrations during intraocular pressure measurement with the Corvis tonometer.
  
  
  CONCLUSIONS
  With the new proposed algorithm for image analysis and processing allowing for the separation of individual features from a corneal deformation image, it is possible to: automatically measure corneal vibrations in a few characteristic points of the cornea, obtain fully repeatable measurement of vibrations for the same registered sequence of images and measure vibration parameters for large inter-individual variability in patients.
authors.affiliation: Department of Biomedical Computer Systems, University of Silesia, Faculty of Computer Science and Materials Science, Institute of Computer Science, ul. Bedzińska 39, Sosnowiec 41-200, Poland. Electronic address: robert.koprowski@us.edu.pl.
authors.forename: Robert
authors.initials: R
authors.lastname: Koprowski
authors.affiliation: Department of Ophthalmology of the Federal University of São Paulo & Rio de Janeiro Corneal Tomography and Biomechanics Study, Group of the Instituto de Olhos Renato Ambrósio, Rua Conde de Bonfim 211 / 712, Rio de Janeiro CEP 20520-050, RJ, Brazil.
authors.forename: Renato
authors.initials: R
authors.lastname: Ambrósio
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D003315:Cornea / Q000473:pathology*; D016002:Discriminant Analysis; D004867:Equipment Design; D005189:False Positive Reactions; D064368:Healthy Volunteers; D006801:Humans; D007429:Intraocular Pressure; D007640:Keratoconus / Q000175:diagnosis*; D008875:Middle Aged; D015233:Models, Statistical; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014065:Tonometry, Ocular / Q000379:methods*; D014732:Vibration; D055815:Young Adult
keywords: Air-puff; Corvis ST tonometer; High-speed deformation; Image processing; Keratoconus; Vibrations; measurement automation