2014
DOI: 10.1586/17469899.2014.981532
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How the smartphone is driving the eye-health imaging revolution

Abstract: The digitization of ophthalmic images has opened up a number of exciting possibilities within eye care such as automated pathology detection, as well as electronic storage and transmission. However, technology capable of capturing digital ophthalmic images remains expensive. We review the latest progress in creating ophthalmic imaging devices based around smartphones, which are readily available to most practicing ophthalmologists and other medical professionals. If successfully developed to be inexpensive and… Show more

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Cited by 25 publications
(21 citation statements)
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“…Drawbacks to mobile fundus photography are as with any mobile based technology used in healthcare, namely secure transfer of patient data and a source of power. The field of view provided by mobile based fundus cameras in the undilated pupil is already improved compared to the direct ophthalmoscope but could be increased further in the future through the use of software to intelligently stitch multiple images together, which have been captured from different regions of the peripheral retina [14].…”
Section: Discussionmentioning
confidence: 99%
“…Drawbacks to mobile fundus photography are as with any mobile based technology used in healthcare, namely secure transfer of patient data and a source of power. The field of view provided by mobile based fundus cameras in the undilated pupil is already improved compared to the direct ophthalmoscope but could be increased further in the future through the use of software to intelligently stitch multiple images together, which have been captured from different regions of the peripheral retina [14].…”
Section: Discussionmentioning
confidence: 99%
“…Smartphones are particularly useful for the task of acquiring and processing images. As technology improves, hardware components such as digital displays and cameras are constantly being upgraded (51). Some works have successfully embedded mobile devices with CADx systems for the purpose of identifying specific diseases.…”
Section: Cadx and Machine Learningmentioning
confidence: 99%
“…Furthermore, the fact that 90% of blind people live in low-income countries [6] is not considered. Their location should be examined together with the lack of smartphone penetration, e.g., only 37% of population in China, and only 19% in Kenya owns a smartphone [7]. Contrary, truly widespread ophthalmoscopic screening will make use of ubiquitous technology, as "dumb" mobile phones, which represent exceptional penetration (e.g., 82% in Kenya [7]).…”
Section: Introductionmentioning
confidence: 99%