Related Experiment Video
Updated: Aug 31, 2025
04:48
Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
Published on: November 30, 2022
2.9K
Deep learning: applications in retinal and optic nerve diseases.
Jason Charng1,2, Khyber Alam2, Gavin Swartz2
1Centre of Ophthalmology and Visual Science (incorporating Lions Eye Institute), University of Western Australia, Perth, Australia.
Clinical & Experimental Optometry
|August 23, 2022
Summary
Deep learning (DL) advances optometry by enabling algorithms to learn from data, improving patient management for posterior eye diseases and vision loss. This technology automates complex data analysis, overcoming limitations of traditional programming.
Area of Science:
- Ophthalmology and Optometry
- Artificial Intelligence
- Medical Informatics
Background:
- Deep learning (DL) is a transformative AI field with growing optometric applications.
- Traditional programming requires explicit rules, which can be biased and insufficient for complex clinical data.
- The increasing volume and complexity of clinical data necessitate automated analysis methods.
Conclusions:
- Deep learning offers a powerful, data-driven approach to enhance optometric patient care.
- DL facilitates automated analysis, aiding clinicians in managing complex eye conditions and vision loss.
- Continued research in DL is crucial for advancing optometric diagnostics and treatment strategies.
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