Mean curvature mapping for detection of corneal shape abnormality

Maolong Tang, Raj Shekhar, David Huang

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


Corneal topography is used to measure the anterior surface of the cornea. It is conventionally represented as radial slope, radial curvature, and elevation. In this paper, we introduce the application of mean curvature mapping as an alternative representation of the corneal topography. The purpose is to improve the detection of keratoconus and other diseases characterized by local increase in corneal curvature. Both simulated keratoconic cornea and real keratoconus data exported from the corneal topography system were analyzed. Four representations of corneal topography were generated and compared. It was found that mean curvature mapping provided the most precise cone location in simulated keratoconus. In both actual and simulated keratoconus cases, the appearance of the cone-like distortion is more consistent on mean curvature maps. Mean curvature mapping may improve the detection and localization of corneal shape abnormalities.

Original languageEnglish (US)
Pages (from-to)424-428
Number of pages5
JournalIEEE Transactions on Medical Imaging
Issue number2
StatePublished - Mar 2005
Externally publishedYes


  • Cornea
  • Corneal topography
  • Keratoconus
  • Mean curvature

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering


Dive into the research topics of 'Mean curvature mapping for detection of corneal shape abnormality'. Together they form a unique fingerprint.

Cite this