Correcting Motion Artifacts in Retinal Spectral Domain Optical Coherence Tomography via Image Registration

Ricco, Susanna; Chen, Mei; Ishikawa, Hiroshi; Wollstein, Gadi; Schuman, Joel S.

doi:10.1007/978-3-642-04268-3_13

Cited by 68 publications

(61 citation statements)

References 12 publications

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“…There have been various publications about averaging of several OCT volumes [15,67,[69][70][71]. Most of them are either complex, or slow, or require a tracking system during data acquisition.…”

Section: The Simple "Acquire-align-average" (Aaa) Processing Approachmentioning

confidence: 99%

Multi-MHz retinal OCT

Klein

Wieser

Reznicek

et al. 2013

Biomed. Opt. Express

197

124

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Abstract:We analyze the benefits and problems of in vivo optical coherence tomography (OCT) imaging of the human retina at A-scan rates in excess of 1 MHz, using a 1050 nm Fourier-domain mode-locked (FDML) laser. Different scanning strategies enabled by MHz OCT line rates are investigated, and a simple multi-volume data processing approach is presented. In-vivo OCT of the human ocular fundus is performed at different axial scan rates of up to 6.7 MHz. High quality non-mydriatic retinal imaging over an ultra-wide field is achieved by a combination of several key improvements compared to previous setups. For the FDML laser, long coherence lengths and 72 nm wavelength tuning range are achieved using a chirped fiber Bragg grating in a laser cavity at 419.1 kHz fundamental tuning rate. Very large data sets can be acquired with sustained data transfer from the data acquisition card to host computer memory, enabling high-quality averaging of many frames and of multiple aligned data sets. Three imaging modes are investigated: Alignment and averaging of 24 data sets at 1.68 MHz axial line rate, ultra-dense transverse sampling at 3.35 MHz line rate, and dual-beam imaging with two laser spots on the retina at an effective line rate of 6.7 MHz. 58. R. Huber, D. C. Adler, V. J. Srinivasan, and J. G. Fujimoto, "Fourier domain mode locking at 1050 nm for ultrahigh-speed optical coherence tomography of the human retina at 236,000 axial scans per second," Opt. Lett. ©2013 Optical Society of America

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Section: The Simple "Acquire-align-average" (Aaa) Processing Approachmentioning

confidence: 99%

Multi-MHz retinal OCT

Klein

Wieser

Reznicek

et al. 2013

Biomed. Opt. Express

197

124

View full text Add to dashboard Cite

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“…However, register every frame to its precedent scan leads to excessive registration especially for B-scans without eye movement. Ricco et al [4] proposed to register the OCT en face image to an instantaneous artifact-free reference image. Xu et al [5] proposed a particle filtering approach which is updated frame by frame to detect A-scan movement.…”

Section: Introductionmentioning

confidence: 99%

Motion Correction in Optical Coherence Tomography for Multi-modality Retinal Image Registration

Cheng

Lee

et al. 2016

Proceedings of the Ophthalmic Medical Image Analysis Third International Workshop

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Abstract. Optical coherence tomography (OCT) is a recently developed non-invasive imaging modality, which is often used in ophthalmology. Because of the sequential scanning in form of A-scans, OCT suffers from the inevitable eye movement. This often leads to mis-alignment especially among consecutive B-scans, which affects the analysis and processing of the data such as the registration of the OCT en face image to color fundus image. In this paper, we propose a novel method to correct the mis-alignment among consecutive B-scans to improve the accuracy in multi-modality retinal image registration. In the method, we propose to compute decorrelation from overlapping B-scans and to detect the eye movement. Then, the B-scans with eye movement will be re-aligned to its precedent scans while the rest of B-scans without eye movement are untouched. Our experiments results show that the proposed method improves the accuracy and success rate in the registration to color fundus images.

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“…[4] These SDOCT setups have been used to obtain 2D images and 3D volumes; for high resolution 3D volumetric scans, the acquisition time is still on the order of seconds. [5,6,7] However, most of the SDOCT systems today were developed for diagnosis rather than clinical surgery, and only a few attempts have been made to integrate real-time OCT into eye surgery. OCT systems have been previously combined with surgical microscopes in order to obtain cross-sections of the sclera and cornea, but these systems were used in a "stop and check" scenario rather than for real-time guidance.…”

Section: Introductionmentioning

confidence: 99%

Graphics Processor Unit (GPU) Accelerated Shallow Transparent Layer Detection in Optical Coherence Tomographic (OCT) Images for Real-Time Corneal Surgical Guidance

Mathai

Galeotti

Horvath

et al. 2014

Augmented Environments for Computer-Assisted Interventions

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Abstract. An image analysis algorithm is described that utilizes a Graphics Processor Unit (GPU) to detect in real-time the most shallow subsurface tissue layer present in an OCT image obtained by a prototype SDOCT corneal imaging system. The system has a scanning depth range of 6mm and can acquire 15 volumes per second at the cost of lower resolution and signal-to-noise ratio (SNR) than diagnostic OCT scanners. To the best of our knowledge, we are the first to experiment with non-median percentile filtering for simultaneous noise reduction and feature enhancement in OCT images, and we believe we are the first to implement any form of non-median percentile filtering on a GPU. The algorithm was applied to five different test images. On an average, it took ~0.5 milliseconds to preprocess an image with a 20 th -percentile filter, and ~1.7 milliseconds for our second-stage algorithm to detect the faintly imaged transparent surface.

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Correcting Motion Artifacts in Retinal Spectral Domain Optical Coherence Tomography via Image Registration

Cited by 68 publications

References 12 publications

Multi-MHz retinal OCT

Multi-MHz retinal OCT

Motion Correction in Optical Coherence Tomography for Multi-modality Retinal Image Registration

Graphics Processor Unit (GPU) Accelerated Shallow Transparent Layer Detection in Optical Coherence Tomographic (OCT) Images for Real-Time Corneal Surgical Guidance

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