Literature DB >> 17946260

Analysis of corneal images for the recognition of nerve structures.

Alfredo Ruggeri1, Fabio Scarpa, Enrico Grisan.   

Abstract

The recognition of nerve structures in the cornea appears to be an important clinical issue, e.g. to investigate about damages from surgical interventions (LASIK/PRK) or severity of diabetic neuropathy. We addressed the problem of recognizing and tracing corneal nerves in confocal microscopy images. After image luminosity and contrast are normalized, the nerve tracking procedure is run. After nerve segments are recognized, a post-processing procedure removes false recognitions and links sparse segments. A prototype of the algorithm was implemented in the Matlab language and run on a personal computer. An evaluation was performed on a data set containing 12 images. The percent of tracked nerves (with respect to manual tracing) was on average 87%; the rate of false positive recognitions (with respect to total tracing) was on average 9%. Running times of the prototype were 4-5 minutes per image.

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Year:  2006        PMID: 17946260     DOI: 10.1109/IEMBS.2006.259805

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  3 in total

1.  Dual-model automatic detection of nerve-fibres in corneal confocal microscopy images.

Authors:  M A Dabbah; J Graham; I Petropoulos; M Tavakoli; R A Malik
Journal:  Med Image Comput Comput Assist Interv       Date:  2010

Review 2.  Corneal Confocal Microscopy as a Quantitative Imaging Biomarker of Diabetic Peripheral Neuropathy: A Review.

Authors:  Eleonora Cosmo; Giulia Midena; Luisa Frizziero; Marisa Bruno; Michela Cecere; Edoardo Midena
Journal:  J Clin Med       Date:  2022-08-31       Impact factor: 4.964

3.  Reproducibility of In Vivo Corneal Confocal Microscopy Using an Automated Analysis Program for Detection of Diabetic Sensorimotor Polyneuropathy.

Authors:  Ilia Ostrovski; Leif E Lovblom; Mohammed A Farooqi; Daniel Scarr; Genevieve Boulet; Paul Hertz; Tong Wu; Elise M Halpern; Mylan Ngo; Eduardo Ng; Andrej Orszag; Vera Bril; Bruce A Perkins
Journal:  PLoS One       Date:  2015-11-05       Impact factor: 3.240

  3 in total

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