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Estimation of the c...
Estimation of the cross-sectional surface area of the waist of the nerve fiber layer at the optic nerve head
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- Kisonaite, Konstancija (författare)
- Uppsala universitet,Institutionen för kirurgiska vetenskaper,Per Söderberg
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- Yu, Zhaohua, 1983- (författare)
- Uppsala universitet,Institutionen för kirurgiska vetenskaper,Per Söderberg
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- Raeme, Faisal (författare)
- Uppsala universitet,Institutionen för kirurgiska vetenskaper,Per Söderberg
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- Bendazzoli, Simone (författare)
- KTH,Medicinteknik och hälsosystem,KTH Royal Inst Technol, Dept Biomed Engn & Hlth Syst, Stockholm, Sweden.
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- Wang, Chunliang, 1980- (författare)
- KTH,Medicinsk avbildning,KTH Royal Inst Technol, Dept Biomed Engn & Hlth Syst, Stockholm, Sweden.
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- Söderberg, Per, 1956- (författare)
- Uppsala universitet,Oftalmiatrik,Per Söderberg
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(creator_code:org_t)
- SPIE-Intl Soc Optical Eng, 2022
- 2022
- Engelska.
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Ingår i: Progress in Biomedical Optics and Imaging. - : SPIE-Intl Soc Optical Eng.
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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https://urn.kb.se/re...
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Abstract
Ämnesord
Stäng
- Glaucoma is a global disease that leads to blindness due to pathological loss of retinal ganglion cell axons in the optic nerve head (ONH). The presented project aims at improving a computational algorithm for estimating the thickness and surface area of the waist of the nerve fiber layer in the ONH. Our currently developed deep learning AI algorithm meets the need for a morphometric parameter that detects glaucomatous change earlier than current clinical follow-up methods. In 3D OCT image volumes, two different AI algorithms identify the Optic nerve head Pigment epithelium Central Limit (OPCL) and the Inner limit of the Retina Closest Point (IRCP) in a 3D grid. Our computational algorithm includes the undulating surface area of the waist of the ONH, as well as waist thickness. In 16 eyes of 16 non-glaucomatous subjects aged [20;30] years, the mean difference in minimal thickness of the waist of the nerve fiber layer between our previous and the current post-processing strategies was estimated as CIμ(0.95) 0 ±1 μm (D.f. 15). The mean surface area of the waist of the nerve fiber layer in the optic nerve head was 1.97 ± 0.19 mm2. Our computational algorithm results in slightly higher values for surface areas compared to published work, but as expected, this may be due to surface undulations of the waist being considered. Estimates of the thickness of the waist of the ONH yields estimates of the same order as our previous computational algorithm.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Oftalmologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Ophthalmology (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
Nyckelord
- OCT
- optic nerve head
- nerve fiber layer
- waist
- cross-sectional area
- surface area
- minimal thickness
- deep learning
- AI
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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