Wireless, Web-Based Interactive Control of Optical Coherence Tomography with Mobile Devices

Mehta, Rajvi; Nankivil, Derek; Zielinski, David J.; Waterman, Gar; Keller, Brenton; Kopper, Regis; Izatt, Joseph A.; Kuo, Anthony N.

doi:10.1167/tvst.6.1.5

Cited by 8 publications

(3 citation statements)

References 18 publications

(21 reference statements)

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“…Furthermore, these imaging modalities can be used in underserved areas to address ophthalmic emergencies in areas where ophthalmologists are unavailable. In fact, technology to remotely control OCT is under development 21. We believe that the automated OCT used in this study, which has voice direction for patient fixation in multiple language options, would be operable by emergency department staff after minimal training.…”

Section: Discussionmentioning

confidence: 98%

Impact of automated OCT in a high-volume eye urgent care setting

et al. 2019

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Background/AimsOptical coherence tomography (OCT) has become standard of care in the diagnosis and management of a myriad of retinal and optic nerve pathology. Access to diagnostic equipment and skilled imaging personnel in the after-hours setting is often limited. We examined the utility and diagnostic indications for automated OCT in a high-volume after-hours clinic within an eye institute.MethodsOCT images obtained over a period of 15 months were reviewed in the context of electronic patient records. Residents and fellows were surveyed regarding their experience with the OCT and its value in emergency patient management.Results202 patients and 359 eyes were examined. Complaints prompting imaging included flashes/floaters, metamorphopsia, decreased vision and scotomas. Diagnoses included vascular occlusion, retinal detachment, macular hole, cystoid macular oedema and central serous retinopathy. Of the 25 residents and fellows surveyed, most agreed that the OCT that facilitated delivery of optimal urgent management. OCT also aided in the triage of patients to specialty clinics.ConclusionExpanded access to automated OCT in the urgent care setting shows promise for improving the accuracy and timeliness of diagnosis, which can be critical for optimising patient outcomes. OCT also provides clear, immediate documentation of pathology for substantiating medical decision-making.

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Section: Discussionmentioning

confidence: 98%

Impact of automated OCT in a high-volume eye urgent care setting

et al. 2019

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“…Recently, there have been studies highlighting the emerging applications of portable and handheld OCT systems in non-traditional settings. 23–25 Mehta et al have utilized a web-based user interface being accessed on a cellular phone mounted to a handheld OCT probe, 26 for the wireless control of the imaging device; 27 however, it does not meet the needs of social distancing between the photographer having the OCT probe and the patient. However, with this software, multiple users can review and control the same imaging session remotely in another remote via the same web-based user interface on various devices like cellular phone, tablets, or laptop.…”

Section: Discussionmentioning

confidence: 99%

Remote Imaging Capture with Widefield Swept-Source OCT Angiography During the COVID-19 Pandemic

Garg¹,

Katz²,

Lu³

et al. 2022

OPTH

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The COVID-19 pandemic has had a widespread impact on the health sector worldwide, both in the clinical and research subsector. This has necessitated for the invention of protocols compliant with social distancing policies to efficiently tackle the current needs. Our aim is to describe a novel remote imaging technique, which helped us continue our research with widefield swept-source optical coherence tomography angiography (WF SS-OCTA). Patients and Methods: As a part of this cross-sectional observational study from August 2020 to September 2020 at Massachusetts Eye and Ear (MEE), we used our institute approved remote desktop, outside of MEE, to gain full access to the on-site WF SS-OCTA device in the imaging room for the purpose of remote imaging. With only the patient being in the imaging room, effective communication was established via video conferencing on an encrypted tablet computer device for the entire procedure. Results: We imaged four patients with various retinal pathologies, aged 32-69 years. All images obtained were of high quality and signal strength (median score 9/10 for both) and all patients reported a highly satisfactory, comfortable, and safe experience amidst the COVID-19 pandemic. Conclusion: This novel method is better for remote imaging compared to the previously described techniques as it is time and cost effective, requires limited resources without compromising the image quality or patient satisfaction and adheres to the various guidelines for infection control, most importantly social distancing. As a paradigm shift, this can also be employed in future for setups with limited staff like busy emergency departments or a rural setup with limited access or difficult commute, in the "newnormal" era.

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“…One of the significant challenges that hinders the availability of large quantities of data required for training data hungry deep learning models is the cost of data collection, limiting the accessibility of deep learning based decision support systems to general public specially in developing regions of the world [14]. This has motivated the development of low-cost diagnostic devices such as wireless phone stethoscope [14], wireless OCT devices [25]. Data collection using these lowcost devices can be noisy and have out-of-distribution samples collectively termed as outliers.…”

Section: Introductionmentioning

confidence: 99%

Multiview Outlier Filtered Pediatric Heart Sound Classification

Dakshit

2024

ijacsa

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The advancements in deep learning has generated a large-scale interest in development of black-box models for various use cases in different domains such as healthcare, in both at-home and critical setting for diagnosis and monitoring of various health conditions. The use of audio signals as a view for diagnosis is nascent and the success of deep learning models in ingesting multimedia data provides an opportunity for use as a diagnostic medium. For the widespread use of these decision support systems, it is prudent to develop high performing systems which require large quantities of data for training and low-cost method of data collection making it more accessible for developing regions of the world and general population. Data collected from low-cost collection especially wireless devices are prone to outliers and anomalies. The presence of outliers skews the hypothesis space of the model and leads to model drift on deployment. In this paper, we propose a multiview pipeline through interpretable outlier filtering on the small Mendeley Children Heart Sound dataset collected using wireless low-cost digital stethoscope. Our proposed pipeline explores and provides dimensionally reduced interpertable visualizations for functional understanding of the effect of various outlier filtering methods on deep learning model hypothesis space and fusion strategies for multiple views of heart sound data namely raw time-series signal and Mel Frequency Cepstrum Coefficients achieving 98.19% state-of-the-art testing accuracy.

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Wireless, Web-Based Interactive Control of Optical Coherence Tomography with Mobile Devices

Cited by 8 publications

References 18 publications

Impact of automated OCT in a high-volume eye urgent care setting

Impact of automated OCT in a high-volume eye urgent care setting

Remote Imaging Capture with Widefield Swept-Source OCT Angiography During the COVID-19 Pandemic

Multiview Outlier Filtered Pediatric Heart Sound Classification

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