AIMC Topic: Indocyanine Green
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Automated deep learning in ophthalmology: AI that can build AI.
Current opinion in ophthalmology
Sep 1, 2021
PURPOSE OF REVIEW: The purpose of this review is to describe the current status of automated deep learning in healthcare and to explore and detail the development of these models using commercially available platforms. We highlight key studies demons...
Artificial intelligence indocyanine green (ICG) perfusion for colorectal cancer intra-operative tissue classification.
The British journal of surgery
Jan 27, 2021
Deep learning for in vivo near-infrared imaging.
Proceedings of the National Academy of Sciences of the United States of America
Jan 5, 2021
Detecting fluorescence in the second near-infrared window (NIR-II) up to ∼1,700 nm has emerged as a novel in vivo imaging modality with high spatial and temporal resolution through millimeter tissue depths. Imaging in the NIR-IIb window (1,500-1,700 ...
SWEPT SOURCE OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY, FLUORESCEIN ANGIOGRAPHY, AND INDOCYANINE GREEN ANGIOGRAPHY COMPARISONS REVISITED: Using a Novel Deep-Learning-Assisted Approach for Image Registration.
Retina (Philadelphia, Pa.)
Oct 1, 2020
PURPOSE: To compare area measurements between swept source optical coherence tomography angiography (SSOCTA), fluorescein angiography (FA), and indocyanine green angiography (ICGA) after applying a novel deep-learning-assisted algorithm for accurate ...
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