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The aim was to produce sharp edges of the optic nerves for cross\u2010sectional area measurement. Lanczos\u2010mFCM was identified as the best combination in terms of: image quality; Dice similarity coefficient; a similar area compared with measurements from raw images but with higher reproducibility; and the highest signal\u2010to\u2010noise and contrast\u2010to\u2010noise ratios. It was then applied to ten normal datasets. The mean cross\u2010sectional areas were 12.57 \u00b1 1.92mm<jats:sup>2<\/jats:sup>from proton density images, 12.98 \u00b1 2.18mm<jats:sup>2<\/jats:sup>from T2\u2010weighted (T2W) images including the optic nerve sheath, and 1.68 \u00b1 0.69mm<jats:sup>2<\/jats:sup>from the T2W images of the optic nerve only. The Lanczos\u2010mFCM method is recommended for future quantitative studies on optic nerve MRI.<\/jats:p>","DOI":"10.1002\/ima.23030","type":"journal-article","created":{"date-parts":[[2024,1,31]],"date-time":"2024-01-31T07:34:25Z","timestamp":1706686465000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Evaluation of optimal interpolation and segmentation of the optic nerves on magnetic resonance images for cross\u2010sectional area measurement"],"prefix":"10.1002","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3877-4434","authenticated-orcid":false,"given":"Li Sze","family":"Chow","sequence":"first","affiliation":[{"name":"Department of Electrical and Electronic Engineering, Faculty of Engineering Technology and Built Environment UCSI University Kuala Lumpur Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Martyn N. 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