Scholars@Duke

Automatic detection of pathological myopia using variational level set.

Publication ,  Journal Article
Tan, NM; Liu, J; Wong, DK; Lim, JH; Zhang, Z; Lu, S; Li, H; Saw, SM; Tong, L; Wong, TY
Published in: Annu Int Conf IEEE Eng Med Biol Soc
2009
Published version (DOI) Link to item

Pathological myopia, the seventh leading cause of legal blindness in United States, is a condition caused by pathological axial elongation and eyes that deviates from the normal distribution curve of axial length, resulting in impaired vision. Studies have shown that ocular risks associated with myopia should not be underestimated, and there is a public health need to prevent the onset or progression of myopia. Peripapillary atrophy (PPA) is one of the clinical indicators for pathological myopia. In this paper, we introduce a novel method, to detect pathological myopia via peripapaillary atrophy feature by means of variational level set. This method is a core algorithm of our system, PAMELA, an automated system for the detection of pathological myopia. The proposed method has been tested on 40 images from Singapore Cohort study Of the Risk factors for Myopia (SCORM), producing a 95% accuracy of correct assessment, and a sensitivity and specificity of 0.9 and 1 respectively. The results highlight the potential of PAMELA as a possible clinical tool for objective mass screening of pathological myopia.

Duke Scholars

Tien Yin Wong
Author Tien Yin Wong Ophthalmology

Published In

Annu Int Conf IEEE Eng Med Biol Soc

DOI

10.1109/IEMBS.2009.5333517

ISSN

2375-7477

Publication Date

2009

Volume

2009

Start / End Page

3609 / 3612

Location

United States

Related Subject Headings

  • Software
  • Risk Factors
  • Retinal Diseases
  • Reproducibility of Results
  • Pattern Recognition, Automated
  • Optic Nerve
  • Myopia, Degenerative
  • Models, Statistical
  • Models, Anatomic
  • Humans
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Tan, N. M., Liu, J., Wong, D. K., Lim, J. H., Zhang, Z., Lu, S., … Wong, T. Y. (2009). Automatic detection of pathological myopia using variational level set. Annu Int Conf IEEE Eng Med Biol Soc, 2009, 3609–3612. https://doi.org/10.1109/IEMBS.2009.5333517
Tan, N. M., J. Liu, D. K. Wong, J. H. Lim, Z. Zhang, S. Lu, H. Li, S. M. Saw, L. Tong, and T. Y. Wong. “Automatic detection of pathological myopia using variational level set.” Annu Int Conf IEEE Eng Med Biol Soc 2009 (2009): 3609–12. https://doi.org/10.1109/IEMBS.2009.5333517.
Tan NM, Liu J, Wong DK, Lim JH, Zhang Z, Lu S, et al. Automatic detection of pathological myopia using variational level set. Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:3609–12.
Tan, N. M., et al. “Automatic detection of pathological myopia using variational level set.” Annu Int Conf IEEE Eng Med Biol Soc, vol. 2009, 2009, pp. 3609–12. Pubmed, doi:10.1109/IEMBS.2009.5333517.
Tan NM, Liu J, Wong DK, Lim JH, Zhang Z, Lu S, Li H, Saw SM, Tong L, Wong TY. Automatic detection of pathological myopia using variational level set. Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:3609–3612.

Published In

Annu Int Conf IEEE Eng Med Biol Soc

DOI

10.1109/IEMBS.2009.5333517

ISSN

2375-7477

Publication Date

2009

Volume

2009

Start / End Page

3609 / 3612

Location

United States

Related Subject Headings

  • Software
  • Risk Factors
  • Retinal Diseases
  • Reproducibility of Results
  • Pattern Recognition, Automated
  • Optic Nerve
  • Myopia, Degenerative
  • Models, Statistical
  • Models, Anatomic
  • Humans