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The Next Frontier of Imaging in Ophthalmology: Machine Learning and Tissue Biomechanics

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Ocular Fluid Dynamics

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Abstract

Medical imaging has revolutionized the diagnosis and management of disease in healthcare. Early integration of computers into medical imaging brought control of devices and data acquisition to new heights of precision. As computing power and sophistication of software evolve, we have reached an era of computer-based image interpretation. Machine learning approaches have been developed to automate certain quantitative measures derived from these modalities. Prospects for machine learning in ophthalmology address its potential role in approaching some of the most common causes of blindness worldwide: diabetic retinopathy, glaucoma, and age-related macular degeneration. As these analysis techniques evolve, concurrent advancements are seen in ophthalmology imaging technologies themselves, and today, the aqueous outflow tract and the optic nerve head can be visualized in more detail than ever before. The optimization and assimilation of these tools may hold clinically significant answers to screening, diagnosing, and managing disease.

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Notes

  1. 1.

    In discussing this process with radiology residents, I’ve been told that at some point in the second year of training, something clicks; a veil is lifted from their eyes, and they become aware of the vast hidden features contained in an X-ray.

  2. 2.

    In the case of MRI, some cleaver finagling is performed with magnetic fields prior to the presentation of the EMP, which is beyond the scope of this discussion.

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Authors and Affiliations

  1. Department of Ophthalmology, NYU Langone Medical Center, NYU School of Medicine, New York, NY, USA

    Jenna Tauber & Larry Kagemann

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  1. Jenna Tauber
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  2. Larry Kagemann
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Correspondence to Larry Kagemann .

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Editors and Affiliations

  1. Department of Math Sciences, Indiana University – Purdue University I, Indianapolis, IN, USA

    Giovanna Guidoboni

  2. Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Alon Harris

  3. Department of Mathematics, Polytechnic University of Milan, Milan, Italy

    Riccardo Sacco

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Disclaimer: All views and opinions express herein are those of the authors, and do not express federal policy or the views of the US Food and Drug Administration.

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Tauber, J., Kagemann, L. (2019). The Next Frontier of Imaging in Ophthalmology: Machine Learning and Tissue Biomechanics. In: Guidoboni, G., Harris, A., Sacco, R. (eds) Ocular Fluid Dynamics. Modeling and Simulation in Science, Engineering and Technology. Birkhäuser, Cham. https://doi.org/10.1007/978-3-030-25886-3_23

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