Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Electrical Impedance Tomography for Real-Time PEEP Monitoring and Atelectasis During Mask Ventilation: A Randomized Controlled Physiological Trial.

Anesthesia and analgesia·2026
Same author

EndoArt: Indications, Mechanism of Action, Outcomes, and Complications.

Klinische Monatsblatter fur Augenheilkunde·2026
Same author

[Light-induced immunomodulation : Corneal cross-linking to reduce neovascularization and optimize outcomes prior to corneal transplantation].

Die Ophthalmologie·2026
Same author

The impact of vision impairment on living with congenital aniridia: a pan-European survey study.

Orphanet journal of rare diseases·2026
Same author

[Inflammatory Eye Diseases].

Klinische Monatsblatter fur Augenheilkunde·2026
Same author

Early postoperative corneal thickness and 12-month endothelial cell outcomes after descemet membrane endothelial keratoplasty: A multicentre analysis.

Acta ophthalmologica·2026

Related Experiment Video

Updated: Jun 30, 2025

An “All-laser” Endothelial Transplant
09:59

An “All-laser” Endothelial Transplant

Published on: July 6, 2015

9.5K

Artificial Intelligence for Lamellar Keratoplasty.

Sebastian Siebelmann1, Takahiko Hayashi2, Mario Matthaei3

  • 1Augenärzte Kölner Höfe, Gemeinschaftspraxis Solingen, Deutschland.

Klinische Monatsblatter Fur Augenheilkunde
|March 19, 2024
PubMed
Summary

Artificial intelligence (AI) shows great potential for optimizing lamellar keratoplasty, particularly with optical coherence tomography imaging. Current AI applications focus on predicting outcomes and automating routine parameter analysis in procedures like DMEK, DSAEK, and DALK.

More Related Videos

Full-Field Optical Coherence Microscopy for Histology-Like Analysis of Stromal Features in Corneal Grafts
07:51

Full-Field Optical Coherence Microscopy for Histology-Like Analysis of Stromal Features in Corneal Grafts

Published on: October 21, 2022

1.6K
Corneal Donor Tissue Preparation for Endothelial Keratoplasty
08:37

Corneal Donor Tissue Preparation for Endothelial Keratoplasty

Published on: June 12, 2012

27.6K

Related Experiment Videos

Last Updated: Jun 30, 2025

An “All-laser” Endothelial Transplant
09:59

An “All-laser” Endothelial Transplant

Published on: July 6, 2015

9.5K
Full-Field Optical Coherence Microscopy for Histology-Like Analysis of Stromal Features in Corneal Grafts
07:51

Full-Field Optical Coherence Microscopy for Histology-Like Analysis of Stromal Features in Corneal Grafts

Published on: October 21, 2022

1.6K
Corneal Donor Tissue Preparation for Endothelial Keratoplasty
08:37

Corneal Donor Tissue Preparation for Endothelial Keratoplasty

Published on: June 12, 2012

27.6K

Area of Science:

  • Ophthalmology
  • Artificial Intelligence
  • Medical Imaging

Background:

  • Lamellar keratoplasty is increasingly studied, with optical coherence tomography (OCT) offering high-resolution, non-invasive imaging.
  • AI's application in optimizing lamellar keratoplasty is emerging, though under-explored.
  • OCT's capabilities align well with AI for ophthalmic applications.

Purpose of the Study:

  • To review the current applications and potential of artificial intelligence (AI) in optimizing lamellar keratoplasty.
  • To highlight AI's role in enhancing diagnostic and prognostic capabilities in corneal transplantation.
  • To identify limitations and future directions for AI in lamellar keratoplasty.

Main Methods:

  • Review of existing literature on AI applications in lamellar keratoplasty.
  • Analysis of AI's use in conjunction with optical coherence tomography (OCT) for corneal imaging.
  • Examination of AI algorithms for predicting outcomes in Descemet Membrane Endothelial Keratoplasty (DMEK), Descemet Stripping Automated Endothelial Keratoplasty (DSAEK), and Deep Anterior Lamellar Keratoplasty (DALK).

Main Results:

  • AI is being used to predict rebubbling success in DMEK and DSAEK and to assess graft adherence.
  • AI aids in predicting the formation of a "big bubble" in DALK.
  • AI enables automated recording of corneal edema, endothelial cell density, and graft detachment size.

Conclusions:

  • AI holds significant potential for optimizing lamellar keratoplasty procedures and outcomes.
  • Current AI algorithms show promise in specific predictive and analytical tasks within lamellar keratoplasty.
  • Widespread transferability of AI algorithms across different centers, surgeons, and devices remains a limitation.