Characterization of Soft Contact Lens Edge Fitting Using Ultra-High Resolution and Ultra-Long Scan Depth Optical Coherence Tomography

Meixiao Shen; Lele Cui; Colleen Riley; Michael R Wang; Jianhua Wang

doi:10.1167/iovs.10-6507

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Characterization of Soft Contact Lens Edge Fitting Using Ultra-High Resolution and Ultra-Long Scan Depth Optical Coherence Tomography

Journal article

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Peer reviewed

Characterization of Soft Contact Lens Edge Fitting Using Ultra-High Resolution and Ultra-Long Scan Depth Optical Coherence Tomography

Meixiao Shen, Lele Cui, Colleen Riley, Michael R Wang and Jianhua Wang

Investigative ophthalmology & visual science, Vol.52(7), pp.4091-4097

2011-06

DOI: https://doi.org/10.1167/iovs.10-6507

PMCID: PMC3175978

PMID: 21372023

Abstract

The authors characterized the edge fitting of soft contact lenses and predicted mismatches between the lens and the ocular surface using UHR-OCT and UL-OCT. This technology may open new methods for lens design and fitting evaluation.

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Collaboration types: Industry collaboration; Domestic collaboration
Citation topics: 1 Clinical & Life Sciences; 1.36 Ophthalmology; 1.36.686 Dry Eye
Web Of Science research areas: Ophthalmology
ESI research areas: Clinical Medicine

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Details

Title: Characterization of Soft Contact Lens Edge Fitting Using Ultra-High Resolution and Ultra-Long Scan Depth Optical Coherence Tomography
Creators: Meixiao Shen - From the Departments of
Lele Cui - From the Departments of
Colleen Riley - Vistakon, Johnson & Johnson, Jacksonville, Florida
Michael R Wang - Electrical and Computer Engineering, University of Miami, Miami, Florida; and
Jianhua Wang - From the Departments of
Publication Details: Investigative ophthalmology & visual science, Vol.52(7), pp.4091-4097
Publisher: Association for Research in Vision and Ophthalmology, Inc
Grant note: P30 EY014801 / National Institutes of Health
Academic Unit: Miller School of Medicine; College of Engineering; UMMG Department of Ophthalmology; CoE - Electrical & Computer Engineering
Language: English
Resource Type: Journal article
PMID: 21372023
PMCID: PMC3175978
Record Identifier: 991031559072902976