Melanie C. Corbett , John Marshall , David P.S. O'Brart , Emanuel S. Rosen
{"title":"New and Future Technology in Corneal Topography","authors":"Melanie C. Corbett , John Marshall , David P.S. O'Brart , Emanuel S. Rosen","doi":"10.1016/S0955-3681(13)80394-2","DOIUrl":null,"url":null,"abstract":"<div><p>Techniques for assessing corneal topography have been developed and improved over the last four centuries in response to changing demand. In recent years, there has been an escalation in the number, type and complexity of the systems available, following a trend which may continue into the future.</p><p>Most widely-available topography systems are based on the principle of reflection (videokeratoscopy), although there is now an increasing number of systems based on the principle of projection (rasterstereography, moiré interference and laser interferometry). Each technique has its own inherent advantages and limitations. For example, those based on projection can directly measure true corneal height and be used in the individualized treatment of irregular corneal astigmatism.</p><p>Most systems rely upon computer algorithms to convert recorded images into topographic information. New algorithms incorporating fewer estimates and assumptions are being developed, in order to improve the accuracy with which the corneal surface can be reconstructed.</p><p>The topographic data of individual patients can be displayed visually in the form of maps, but the need to analyse grouped data has lead to the development of quantitative descriptors of corneal shape, and indices predicting visual function. Classifications of normal and abnormal topography based on pattern recognition have been described, but await improvements in artificial neural networks before they can be automated. Advanced computing is also needed before data analysis is sufficiently rapid for real-time topography to become a reality. Future developments in corneal topography need to target the differing requirements of research and clinical practice.</p></div>","PeriodicalId":100500,"journal":{"name":"European Journal of Implant and Refractive Surgery","volume":"7 6","pages":"Pages 371-385"},"PeriodicalIF":0.0000,"publicationDate":"1995-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0955-3681(13)80394-2","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Implant and Refractive Surgery","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0955368113803942","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Techniques for assessing corneal topography have been developed and improved over the last four centuries in response to changing demand. In recent years, there has been an escalation in the number, type and complexity of the systems available, following a trend which may continue into the future.
Most widely-available topography systems are based on the principle of reflection (videokeratoscopy), although there is now an increasing number of systems based on the principle of projection (rasterstereography, moiré interference and laser interferometry). Each technique has its own inherent advantages and limitations. For example, those based on projection can directly measure true corneal height and be used in the individualized treatment of irregular corneal astigmatism.
Most systems rely upon computer algorithms to convert recorded images into topographic information. New algorithms incorporating fewer estimates and assumptions are being developed, in order to improve the accuracy with which the corneal surface can be reconstructed.
The topographic data of individual patients can be displayed visually in the form of maps, but the need to analyse grouped data has lead to the development of quantitative descriptors of corneal shape, and indices predicting visual function. Classifications of normal and abnormal topography based on pattern recognition have been described, but await improvements in artificial neural networks before they can be automated. Advanced computing is also needed before data analysis is sufficiently rapid for real-time topography to become a reality. Future developments in corneal topography need to target the differing requirements of research and clinical practice.