Article

Volumetric microvascular imaging of human retina using optical coherence tomography with a novel motion contrast technique

California Institute of Technology, Pasadena, California 91125, USA.
Optics Express (Impact Factor: 3.49). 11/2009; 17(24):22190-200. DOI: 10.1364/OE.17.022190
Source: PubMed

ABSTRACT

Phase variance-based motion contrast imaging is demonstrated using a spectral domain optical coherence tomography system for the in vivo human retina. This contrast technique spatially identifies locations of motion within the retina primarily associated with vasculature. Histogram-based noise analysis of the motion contrast images was used to reduce the motion noise created by transverse eye motion. En face summation images created from the 3D motion contrast data are presented with segmentation of selected retinal layers to provide non-invasive vascular visualization comparable to currently used invasive angiographic imaging. This motion contrast technique has demonstrated the ability to visualize resolution-limited vasculature independent of vessel orientation and flow velocity.

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Available from: Robert J Zawadzki
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    • "Generally, each spatial position is OCT sampled several times with a certain time interval using repeated [6] [15] [17] or dense [16] [19] scanning protocols. Then the temporal changes in OCT intensity (or amplitude) [1, 4–6], phase [3] [13] [20] or complex-valued signals [9] [15] [18] [21] over such a time interval are analyzed with different processing algorithms, such as speckle variance [1] [4] [12], Doppler variance [9] [14] [16], phase variance [7] [13], differential calculation [11] [19] and correlation mapping [5] [22]. In consideration of the fact that the temporal dynamics can be amplified by increasing the time interval, an inter-frame analysis has been widely accepted for higher motion sensitivity [16]. "
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    ABSTRACT: The complex-based OCT angiography (Angio-OCT) offers high motion contrast by combining both the intensity and phase information. However, due to involuntary bulk tissue motions, complex-valued OCT raw data are processed sequentially with different algorithms for correcting bulk image shifts (BISs), compensating global phase fluctuations (GPFs) and extracting flow signals. Such a complicated procedure results in massive computational load. To mitigate such a problem, in this work, we present an inter-frame complex-correlation (CC) algorithm. The CC algorithm is suitable for parallel processing of both flow signal extraction and BIS correction, and it does not need GPF compensation. This method provides high processing efficiency and shows superiority in motion contrast. The feasibility and performance of the proposed CC algorithm is demonstrated using both flow phantom and live animal experiments.
    Full-text · Article · Feb 2016 · Journal of optics
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    • "Both phase-based and amplitude-based OCT provide noninvasive visualization of both larger blood vessels and capillary networks in the retina and choroid [6] [8]. The results obtained with these modalities were comparable to currently used invasive angiographic imaging [6] [8] in addition to being able to separately characterize features of the superficial and deep vascular plexuses, which cannot be distinguished in FA [9]. The aim of this study was to evaluate the ability of OCT-A for imaging retina of subjects affected with vascular diseases to assess perfused and nonperfused areas and choroidal "
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    Full-text · Article · Oct 2015 · Journal of Ophthalmology
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    • "Once the scan was completed, one OCT data cube (256 (X) × 2048 (Y) × 4096 (Z) voxels) was produced over the region of interest within 20 s. After the analytical OCT data cube was converted to an amplitude form using a fast Fourier transformation (FFT), a cross-correlation based image registration method was applied for the adjacent B-frames in the 3D amplitude data set to compensate axial displacement induced by possible tissue bulk motion [50]. Then, subtraction between the adjacent B-frames was operated with the consecutive 8 B-frames obtained at the same location to suppress the stationary signals and extract the moving blood flow signals, and thus the resulting 7 images were averaged to enhance flow signal sensitivity, yielding one cross-sectional blood flow intensity image. "
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    Preview · Article · Aug 2014 · Biomedical Optics Express
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