Highly phase-stable 200 kHz swept-source optical coherence tomography based on KTN electro-optic deflector

Ling, Yuye; Yao, Xinwen; Hendon, Christine P.

doi:10.1364/boe.8.003687

Cited by 15 publications

(9 citation statements)

References 48 publications

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“…Fig. 12 shows a B-scan of swine left atrial tissue optically cleared by a 2,2’-thiodiethanol-based aqueous solution (51) and imaged by a custom-built SS-OCT system (52), showing tissue contrast throughout the tissue thickness of ∼2 mm. Combined with increased optical depth penetration induced by optical clearing, imaging with an SS-OCT system could enable high-resolution imaging of deeper tissue structure without complications of image registration or potential artifacts from sectioning.…”

Section: Discussionmentioning

confidence: 99%

Tissue-Specific Optical Mapping Models of Swine Atria Informed by Optical Coherence Tomography

Lye

Vincent

McCulloch

et al. 2018

Biophysical Journal

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Computational models and experimental optical mapping of cardiac electrophysiology serve as powerful tools to investigate the underlying mechanisms of arrhythmias. Modeling can also aid the interpretation of optical mapping signals, which may have different characteristics with respect to the underlying electrophysiological signals they represent. However, despite the prevalence of atrial arrhythmias such as atrial fibrillation, models of optical electrical mapping incorporating realistic structure of the atria are lacking. Therefore, we developed image-based models of atrial tissue using structural information extracted from optical coherence tomography (OCT), which can provide volumetric tissue characteristics in high resolution. OCT volumetric data of four swine atrial tissue samples were used to develop models incorporating tissue geometry, tissue-specific myofiber orientation, and ablation lesion regions. We demonstrated the use of these models through electrophysiology and photon scattering simulations. Changes in transmural electrical conduction were observed with the inclusion of OCT-derived, depth-resolved fiber orientation. Additionally, the amplitude of optical mapping signals were not found to correspond with lesion transmurality because of lesion geometry and electrical propagation occurring beyond excitation light penetration. This work established a framework for the development of tissue-specific models of atrial tissue derived from OCT imaging data, which can be useful in future investigations of electrophysiology and optical mapping signals with respect to realistic atrial tissue structure.

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Section: Discussionmentioning

confidence: 99%

Tissue-Specific Optical Mapping Models of Swine Atria Informed by Optical Coherence Tomography

Lye

Vincent

McCulloch

et al. 2018

Biophysical Journal

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“…We may reduce the number of shifting steps and increase the distance of each shifting step, so the off-axis steps may even be reduced to two steps. This speed limitation may be also mitigated by the use of faster spectrometers (Cobra-S 800, e2V, Chelmsford, UK) or an ultra-high-speed swept source [18] as well. The proposed PRA apparatus is applicable to desktop OCT imaging systems and improves the overall performance of transverse superresolution, DOF, and intensity.…”

Section: Discussionmentioning

confidence: 99%

Pixel-Reassigned Spectral-Domain Optical Coherence Tomography

Wang

Xie

et al. 2018

IEEE Photonics J.

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A novel method of pixel reassignment (PRA) is proposed to achieve transverse superresolution in the confocal microscopy. Inspired by it, for the first time, we report a pixel-reassigned spectral-domain optical coherence tomography (OCT) with ∼1.5 times transverse resolution improvement both in numerical simulations and imaging experiments. PRA is implemented by transversely shifting the detection fiber from the on-axis position to five off-axis positions, capturing cross-sectional images at each shifting step of the detection fiber and digitally reassigning them together to give a sharper image with moderately extended depth of focus and enhanced intensity. So, we believe that the PRA technique will improve the imaging performance and be beneficial to the development of the OCT community.

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“…In phase-sensitive OCT application such as elastography, angiography, and vibrometry, a dual beam setup could be used with a highly phase-stable laser as the ground truth and ‘ordinary’ laser as the input to be enhanced. 126 …”

Section: Embedded Ophthalmic Devicesmentioning

confidence: 99%

Embedded deep learning in ophthalmology: making ophthalmic imaging smarter

et al. 2019

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Deep learning has recently gained high interest in ophthalmology due to its ability to detect clinically significant features for diagnosis and prognosis. Despite these significant advances, little is known about the ability of various deep learning systems to be embedded within ophthalmic imaging devices, allowing automated image acquisition. In this work, we will review the existing and future directions for ‘active acquisition’–embedded deep learning, leading to as high-quality images with little intervention by the human operator. In clinical practice, the improved image quality should translate into more robust deep learning–based clinical diagnostics. Embedded deep learning will be enabled by the constantly improving hardware performance with low cost. We will briefly review possible computation methods in larger clinical systems. Briefly, they can be included in a three-layer framework composed of edge, fog, and cloud layers, the former being performed at a device level. Improved egde-layer performance via ‘active acquisition’ serves as an automatic data curation operator translating to better quality data in electronic health records, as well as on the cloud layer, for improved deep learning–based clinical data mining.

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Highly phase-stable 200 kHz swept-source optical coherence tomography based on KTN electro-optic deflector

Cited by 15 publications

References 48 publications

Tissue-Specific Optical Mapping Models of Swine Atria Informed by Optical Coherence Tomography

Tissue-Specific Optical Mapping Models of Swine Atria Informed by Optical Coherence Tomography

Pixel-Reassigned Spectral-Domain Optical Coherence Tomography

Embedded deep learning in ophthalmology: making ophthalmic imaging smarter

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