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Leopold Schmetterer

Researcher at Nanyang Technological University

Publications -  605
Citations -  21212

Leopold Schmetterer is an academic researcher from Nanyang Technological University. The author has contributed to research in topics: Retinal & Blood flow. The author has an hindex of 70, co-authored 545 publications receiving 18022 citations. Previous affiliations of Leopold Schmetterer include Vienna General Hospital & Medical University of Vienna.

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Artificial intelligence and deep learning in ophthalmology

Daniel Shu Wei Ting, +9 more
- 01 Feb 2019 - 
TL;DR: There are also potential challenges with DL application in ophthalmology, including clinical and technical challenges, explainability of the algorithm results, medicolegal issues, and physician and patient acceptance of the AI ‘black-box’ algorithms.
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Real-time assessment of retinal blood flow with ultrafast acquisition by color Doppler Fourier domain optical coherence tomography.

Rainer A. Leitgeb, +5 more
- 17 Nov 2003 - 
TL;DR: The interfaced color Doppler Fourier domain optical coherence tomography (CD-FDOCT) with a commercial OCT system to perform in vivo studies of human retinal blood flow in real time and achieves a system sensitivity of 86dB using a beam power of 500microW at the cornea.
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Doppler Optical Coherence Tomography

Rainer A. Leitgeb, +3 more
- 01 Jul 2014 - 
TL;DR: As compared to standard techniques such as fluorescein and indocyanine-green angiography the technique offers two major advantages: no dye is required and depth resolution is required is provided.
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Use of laser speckle flowgraphy in ocular blood flow research

Tetsuya Sugiyama, +4 more
- 01 Nov 2010 - 
TL;DR: Laser speckle flowgraphy (LSFG) as discussed by the authors allows quantitative estimation of blood flow in the optic nerve head, choroid, retina and iris in vivo.
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Deep learning in ophthalmology: The technical and clinical considerations.

Daniel Shu Wei Ting, +11 more
- 01 Sep 2019 - 
TL;DR: Global eye disease burden, unmet needs and common conditions of public health importance for which AI and DL systems may be applicable are described and the potential challenges for clinical adoption are discussed.