Segmentation and interpolation of optic nerves in MR images

Sharmin Liaquat Urme, Li Sze Chow, Raveendran Paramesran

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

2 Citations (Scopus)


The measurement of human optic nerve is a difficult task because of its small structure. The goal of this work is to find the most suitable segmentation and interpolation models for the optic nerves in MR images, in order to improve the precision in the optic nerves area measurement. In this study, we have chosen Level Set Method (LSM) segmentation and Contrast-Guided (CG) interpolation models. We use the integrated LSM-CG model to produce distinct circular edge for the optic nerves prior the area measurement. It was found that the mean area of the optic nerve is 13.07 ± 1.29 mm2 from original images, and 12.20 ± 1.01 mm2 from the LSM-CG processed images, which are within the range of the reported literature values. These measurement were obtained from Proton Density (PD) images from five healthy volunteers on both 1.5T and 3.0T MRI scanners. The integrated LSM-CG model is suitable for processing optic nerve images to achieve higher resolution edges and allow more accurate area measurement.

Original languageEnglish
Title of host publicationIECBES 2016 - IEEE-EMBS Conference on Biomedical Engineering and Sciences
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages3
ISBN (Electronic)9781467377911
Publication statusPublished - 2016
Externally publishedYes
EventIEEE-EMBS International Conference on Biomedical Engineering and Sciences (IECBES) 2016 - Kuala Lumpur, Malaysia
Duration: 4 Dec 20168 Dec 2016 (Proceedings)


ConferenceIEEE-EMBS International Conference on Biomedical Engineering and Sciences (IECBES) 2016
Abbreviated titleIECBES 2016
CityKuala Lumpur
Internet address


  • interpolation
  • MRI
  • optic nerve
  • segmentation

Cite this