Automatic estimation of the cross-sectional area of the waist of the nerve fiber layer at the optic nerve head

• PurposeGlaucoma leads to pathological loss of axons in the retinal nerve fibre layer at the optic nerve head (ONH). This study aimed to develop a strategy for the estimation of the cross-sectional area of the axons in the ONH. Furthermore, improving the estimation of the thickness of the nerve fibre layer, as compared to a method previously published by us.MethodsIn the 3D-OCT image of the ONH, the central limit of the pigment epithelium and the inner limit of the retina, respectively, were identified with deep learning algorithms. The minimal distance was estimated at equidistant angles around the circumference of the ONH. The cross-sectional area was estimated by the computational algorithm. The computational algorithm was applied on 16 non-glaucomatous subjects.ResultsThe mean cross-sectional area of the waist of the nerve fibre layer in the ONH was 1.97 ± 0.19 mm2. The mean difference in minimal thickness of the waist of the nerve fibre layer between our previous and the current strategies was estimated as CIμ (0.95) 0 ± 1 μm (d.f. = 15).ConclusionsThe developed algorithm demonstrated an undulating cross-sectional area of the nerve fibre layer at the ONH. Compared to studies using radial scans, our algorithm resulted in slightly higher values for cross-sectional area, taking the undulations of the nerve fibre layer at the ONH into account. The new algorithm for estimation of the thickness of the waist of the nerve fibre layer in the ONH yielded estimates of the same order as our previous algorithm.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Oftalmologi (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Ophthalmology (hsv//eng)

Nyckelord

artificial intelligence

cross-sectional area

deep learning

minimal thickness

nerve fibre layer

optic nerve head

optical coherence tomography

surface area

waist

Medicinsk vetenskap

Medical Science

Ophtalmology

Oftalmiatrik

Publikations- och innehållstyp

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