Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Wide-field corneal subbasal nerve plexus mosaics in age-controlled healthy and type 2 diabetes populations
Linkoping Univ, Inst Clin & Expt Med, Dept Ophthalmol, S-58183 Linkoping, Sweden.ORCID iD: 0000-0003-1079-4361
Karlsruhe Inst Technol, Inst Appl Comp Sci, D-76131 Karlsruhe, Germany.
Univ Padua, Dept Informat Engn, I-35122 Padua, Italy.
Univ Coll Southeast Norway, Fac Hlth Sci, N-3045 Drammen, Norway;Oslo Univ Hosp, Unit Regenerat Med, Dept Med Biochem, N-0407 Oslo, Norway;Univ Oslo, N-0407 Oslo, Norway.
Show others and affiliations
2018 (English)In: Scientific Data, E-ISSN 2052-4463, Vol. 5, article id 180075Article in journal (Refereed) Published
Abstract [en]

A dense nerve plexus in the clear outer window of the eye, the cornea, can be imaged in vivo to enable non-invasive monitoring of peripheral nerve degeneration in diabetes. However, a limited field of view of corneal nerves, operator-dependent image quality, and subjective image sampling methods have led to difficulty in establishing robust diagnostic measures relating to the progression of diabetes and its complications. Here, we use machine-based algorithms to provide wide-area mosaics of the cornea's subbasal nerve plexus (SBP) also accounting for depth (axial) fluctuation of the plexus. Degradation of the SBP with age has been mitigated as a confounding factor by providing a dataset comprising healthy and type 2 diabetes subjects of the same age. To maximize reuse, the dataset includes bilateral eye data, associated clinical parameters, and machine-generated SBP nerve density values obtained through automatic segmentation and nerve tracing algorithms. The dataset can be used to examine nerve degradation patterns to develop tools to non-invasively monitor diabetes progression while avoiding narrow-field imaging and image selection biases.

Place, publisher, year, edition, pages
2018. Vol. 5, article id 180075
National Category
Endocrinology and Diabetes
Identifiers
URN: urn:nbn:se:uu:diva-354955DOI: 10.1038/sdata.2018.75ISI: 000430690900003PubMedID: 29688226OAI: oai:DiVA.org:uu-354955DiVA, id: diva2:1223550
Funder
German Research Foundation (DFG), KO 5003/1-1Available from: 2018-06-25 Created: 2018-06-25 Last updated: 2018-06-25Bibliographically approved

Open Access in DiVA

fulltext(1160 kB)2 downloads
File information
File name FULLTEXT01.pdfFile size 1160 kBChecksum SHA-512
a249be91f34f3fee7b82856ba800b46b59f1358f37925399ffd8ea750e487f22d2f655999d5fd04d053254457b3a8d97c245bf2ec126b8216ba2a3e4cf21064f
Type fulltextMimetype application/pdf

Other links

Publisher's full textPubMed

Search in DiVA

By author/editor
Lagali, Neil S.Peterson, Magnus
By organisation
Family Medicine and Preventive Medicine
In the same journal
Scientific Data
Endocrinology and Diabetes

Search outside of DiVA

GoogleGoogle Scholar
Total: 2 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 5 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf