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

Intelligence01:27

Intelligence

8.5K
The term "intelligence" is complex because it refers to both behavior and individuals, and its interpretation varies across cultures. European Americans tend to link intelligence with reasoning and cognitive skills, while in Kenya, it is tied to responsible participation in family and social life. In Uganda, intelligence is seen as the ability to know the right actions and carry them out effectively, while the Iatmul people of Papua New Guinea associate it with the capacity to remember...
8.5K
Measures of Intelligence01:29

Measures of Intelligence

8.4K
Psychologists measure intelligence by using standardized tests that produce a score known as the intelligence quotient or IQ. To understand IQ tests, it's important to recognize the key principles behind their construction: validity, reliability, and standardization.
Validity refers to how well a test measures what it claims to measure. An intelligence test should accurately assess intelligence rather than another characteristic, like anxiety. Criterion validity is one way to evaluate this;...
8.4K
Multiple Intelligences Theory01:20

Multiple Intelligences Theory

8.9K
Howard Gardner's theory of Multiple Intelligence proposes that there are nine distinct types of intelligence, each reflecting different ways of interacting with the world. Introduced in 1983 and expanded in subsequent years, Gardner's framework challenges the traditional notion of a single, generalized intelligence.
8.9K
Cattell's Theory of Intelligence01:25

Cattell's Theory of Intelligence

8.0K
Raymond Cattell, along with John Horn, made significant contributions to our understanding of intelligence by distinguishing between two types: fluid intelligence and crystallized intelligence.
Fluid intelligence involves the capacity to solve new problems and adapt to unfamiliar situations. It's the type of intelligence individuals use when they encounter a novel problem or puzzle that requires innovative thinking. For instance, figuring out how to operate a new gadget relies heavily on...
8.0K
Triarchic Theory of Intelligence01:24

Triarchic Theory of Intelligence

9.9K
Robert Sternberg's triarchic theory of intelligence posits that intelligence is composed of three distinct but interrelated components: analytical, creative, and practical intelligence.
9.9K
Biological Influences on Intelligence01:30

Biological Influences on Intelligence

516
Intelligence is often thought to be linked to brain size, but the relationship is more complex than that. While brain size does correlate modestly with some abilities, like verbal skills, the connection is weaker for others, such as spatial reasoning. Other factors, like brain structure, also play crucial roles. For instance, despite Einstein's smaller-than-average brain, his parietal cortex, which is involved in spatial reasoning, was 15% wider, suggesting that neural density might matter...
516

You might also read

Related Articles

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

Sort by
Same author

Development of a target product profile for artificial intelligence in diabetic eye screening in England: a modified Delphi consensus study.

The Lancet. Digital health·2026
Same author

Automated Deep Learning Quantification of Avascular Area and Intravitreal Neovascularization in Retinal Flatmounts of Rodent Oxygen-Induced Retinopathy Models.

Translational vision science & technology·2026
Same author

Community Optometrist-Led Monitoring of Quiescent Neovascular Age-Related Macular Degeneration: The FENETRE Randomized Clinical Trial.

JAMA network open·2026
Same author

Quantitative Swept-Source Optical Coherence Tomography Angiography Indicators of Neurovascular Dysfunction in Alzheimer Disease.

JAMA ophthalmology·2026
Same author

Head-to-Head Comparative Evaluation of Four Commercially Available Artificial Intelligence Systems for Detecting Referable Diabetic Retinopathy in a Tanzanian Population.

Diabetes care·2026
Same author

Mobile-Based Artificial Intelligence and Ocular Surface Malignancies.

JAMA ophthalmology·2026

Related Experiment Video

Updated: Jan 26, 2026

Optical Coherence Tomography: Imaging Mouse Retinal Ganglion Cells In Vivo
08:17

Optical Coherence Tomography: Imaging Mouse Retinal Ganglion Cells In Vivo

Published on: September 22, 2017

20.0K

Generating retinal flow maps from structural optical coherence tomography with artificial intelligence.

Cecilia S Lee1, Ariel J Tyring1, Yue Wu1

  • 1Department of Ophthalmology, University of Washington, Seattle, WA, USA.

Scientific Reports
|April 7, 2019
PubMed
Summary

Artificial intelligence (AI) can now generate retinal blood flow maps from standard OCT images, bypassing the need for expert labels. This AI model achieves high fidelity, improving upon expert clinician performance in inferring flow from structural imaging.

More Related Videos

In vivo Structural Assessments of Ocular Disease in Rodent Models using Optical Coherence Tomography
07:44

In vivo Structural Assessments of Ocular Disease in Rodent Models using Optical Coherence Tomography

Published on: July 24, 2020

3.4K
Integrated Photoacoustic Ophthalmoscopy and Spectral-domain Optical Coherence Tomography
11:21

Integrated Photoacoustic Ophthalmoscopy and Spectral-domain Optical Coherence Tomography

Published on: January 15, 2013

11.9K

Related Experiment Videos

Last Updated: Jan 26, 2026

Optical Coherence Tomography: Imaging Mouse Retinal Ganglion Cells In Vivo
08:17

Optical Coherence Tomography: Imaging Mouse Retinal Ganglion Cells In Vivo

Published on: September 22, 2017

20.0K
In vivo Structural Assessments of Ocular Disease in Rodent Models using Optical Coherence Tomography
07:44

In vivo Structural Assessments of Ocular Disease in Rodent Models using Optical Coherence Tomography

Published on: July 24, 2020

3.4K
Integrated Photoacoustic Ophthalmoscopy and Spectral-domain Optical Coherence Tomography
11:21

Integrated Photoacoustic Ophthalmoscopy and Spectral-domain Optical Coherence Tomography

Published on: January 15, 2013

11.9K

Area of Science:

  • Ophthalmology
  • Artificial Intelligence
  • Medical Imaging

Background:

  • Expert-generated labels currently limit AI applications in medical imaging.
  • Optical coherence tomography angiography (OCTA) measures retinal blood flow but requires specialized acquisition.
  • Standard optical coherence tomography (OCT) provides structural information but not direct flow data.

Purpose of the Study:

  • To develop an AI algorithm capable of generating retinal blood flow maps from standard OCT images.
  • To overcome the limitations of expert labeling in AI-driven medical imaging.
  • To enable the analysis of blood flow in previously collected OCT datasets.

Main Methods:

  • Trained a deep learning algorithm using OCTA images.
  • Utilized the trained AI to infer flow maps from standard OCT images.
  • Compared the AI-generated flow maps' fidelity against OCTA and expert clinician assessments.

Main Results:

  • AI successfully generated flow maps from structural OCT images.
  • The AI model's flow inference fidelity was comparable to OCTA.
  • AI performance significantly surpassed expert clinicians (P < 0.00001).

Conclusions:

  • AI can infer functional information (blood flow) from structural medical imaging data.
  • This AI approach bypasses the need for expert labels, enabling analysis of large existing OCT datasets.
  • Demonstrates a novel application of AI in medical imaging for functional tissue inference.