Smartphone-based imaging for quantitative biomedical applications: techniques and open-source software

Alberto J. Ruiz; Brady Hunt; Ethan P. M. LaRochelle; Brian W. Pogue

doi:10.1117/12.2614011

7 March 2022 Smartphone-based imaging for quantitative biomedical applications: techniques and open-source software

Alberto J. Ruiz, Brady Hunt, Ethan P. M. LaRochelle, Brian W. Pogue

Proceedings Volume PC11950, Optics and Biophotonics in Low-Resource Settings VIII; PC1195008 (2022) https://doi.org/10.1117/12.2614011
Event: SPIE BiOS, 2022, San Francisco, California, United States

Abstract

The development of smartphones over the last decade has led to a growth in interest of their potential to tackle numerous point-of-care diagnostic and treatment assessment applications. Despite this interest, there has been a lackluster transition of smartphones within clinical care, where the reproducibility of measurements across devices and the inability to perform image analysis within the device has hampered development. Here, we present characterization methodologies and imaging techniques, enabled by an open-source framework, for performing quantitative imaging and analysis within the iOS smartphone environment. We explore the need for RAW pixel data within fluorescence imaging and characterize the iPhone 11 to lay the foundation for its use in scientific and point-of-care applications.

Conference Presentation

Citation Download Citation

Alberto J. Ruiz, Brady Hunt, Ethan P. M. LaRochelle, and Brian W. Pogue "Smartphone-based imaging for quantitative biomedical applications: techniques and open-source software", Proc. SPIE PC11950, Optics and Biophotonics in Low-Resource Settings VIII, PC1195008 (7 March 2022); https://doi.org/10.1117/12.2614011

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