BACKGROUND

Retinal microcirculation is important in maintaining normal visual functions, providing oxygen and nutrients to active retinal tissue, and removing metabolites and waste from the tissue. Retinal pathologies can cause alteration in the retinal vascular network and affect photoreceptor function, which may lead to a significant loss of vision. Visualizing such alterations in retinal vasculature is thus desirable.

Fluorescein angiography (FA) is a minimally invasive method used for the clinical investigation and diagnosis of the vascular change in a retina. However, due to its relatively low spatial resolution and lack of depth information, it is difficult to obtain detailed information of the pathology, such as the location of affected vessels and the specific morphological changes in the capillary network.

OCT has been used for both structural and functional imaging of the posterior eye, and retinal blood flow based on the principle of the Doppler phenomenon. However, Doppler based flow detection is dependent on the Doppler angle, which is insensitive to the particle movement perpendicular to the probing beam, and most of the retinal blood vessels run almost perpendicular to the incident OCT probe beam.

Optical microangiography (OMAG) is an optical coherence tomography (OCT) based imaging technique used for angiographic imaging of biological tissues in vivo. The OMAG method extracts blood flow information based on a direct differentiation of complex or intensity OCT signals between repeated B-scans acquired at the same cross-section. The OMAG method is sensitive to blood cell movement and thereby provides a high imaging resolution.

However, in OMAG, the acquired signals from static background within repeated B-scans are not exactly the same due to, for example, sample movement, system noise, and stability in scanning mechanisms. Thus, the angiographic results not only contain flow information but also bear a static background signal. Such “false flow” is difficult to differentiate from real blood flow based on flow images alone. Additionally, OMAG is prone to artifacts due to tissue hyper-reflection, which is commonly seen in retinal diseases.

SUMMARY

In accordance with the present invention, a system and a method are defined for enhancing quality of a flow image of a sample of a subject. In one embodiment, the computer-implemented method may comprise acquiring a first flow image from a plurality of first OMAG scans of the sample. The sample comprises a biological tissue having fluid flow therethrough. The method includes acquiring a structure image from a second OMAG scan of the sample, plotting, onto a graph, data based on pixel intensity values from the flow image and pixel intensity values from the structure image and differentiating the data, based on location on the graph, into a first data group representing static structure signals and a second data group representing flow signals. The method then includes suppressing pixels in the flow image corresponding to the first data group. The graph may be a two-dimensional (2D) graph or a three-dimensional (3D) graph. The fluid flow may be a blood flow, and the method may further comprise quantifying blood perfusion within the biological tissue in the image.

In one example embodiment, the method may further comprise setting pixels with a probability greater than a threshold to zero intensity on the flow image.

Plotting data based on pixel intensity values from the flow image and pixel intensity values from the structure image may comprise plotting a logarithm of structural pixel intensity over a ratio of flow pixel intensity to structural pixel intensity. In one example embodiment, only data having pixel intensity values above a noise level are plotted onto the graph.

Differentiating the data by location on the graph may comprise determining a boundary on the graph between the first data group and the second data group.

Acquiring the first flow image from the plurality of first OMAG scans of the sample may comprise generating the first flow image from a plurality of adjacent B-scans of the sample.

In another embodiment, a method for reducing artifacts in an image of a sample of a subject is provided. The method comprises extracting at least one flow signal from a plurality of optical microangiography (OMAG) scans of the sample, wherein the sample comprises a biological tissue having fluid flow therethrough, multiplying the at least one flow signal by a weighting factor comprising a motion index to produce at least one weighted flow signal to suppress artifacts, and displaying an image of the sample from the at least one weighted flow signal. The OMAG scans may comprise a plurality of adjacent B-scans of the sample.

In one example embodiment, the motion index is an inter-frame pixel decorrelation coefficient.

In another example embodiment, the method comprises compressing the at least one weighted flow signal with a threshold. The weighted flow signal may be generated from the structural image.

In some example embodiments, the sample comprises one of the following: a brain, an eye, a retina, a tumor, a heart, skin, a kidney, a gastroenterology tract, a productive system, and a cochlear. The method may be used in imaging cerebrovascular perfusion, retinal microcirculation, tumor progression, posterior eye vascular imaging, or angiography, among other applications.

In yet another embodiment, a system for in vivo imaging is provided. The system comprises an OMAG apparatus configured to generate images from living tissue, and a non-transitory computer-readable medium having stored therein instructions executable to cause a computing device to carry out a method comprising acquiring a first flow image from a plurality of first optical microangiography (OMAG) scans of the sample. The sample comprises a biological tissue having fluid flow therethrough. The method further comprises acquiring a structure image from a second OMAG scan of the sample, plotting, onto a graph, data based on pixel intensity values from the flow image and pixel intensity values from the structure image, and differentiating the data, based on location on the graph, into a first data group representing static structure signals and a second data group representing flow signals. The method then comprises suppressing pixels in the flow image corresponding to the first data group.

In yet another embodiment, a system for in vivo imaging is provided. The system comprises an OMAG apparatus configured to generate images from living tissue and a non-transitory computer-readable medium having stored therein instructions executable to cause a computing device to carry out a method comprising extracting at least one flow signal from a plurality of OMAG scans of the sample, wherein the sample comprises a biological tissue having fluid flow therethrough, multiplying the at least one flow signal by a weighting factor comprising a motion index to produce at least one weighted flow signal to suppress artifacts, and displaying an image of the sample from the at least one weighted flow signal.

These as well as other aspects and advantages of the synergy achieved by combining the various aspects of this technology, that while not previously disclosed, will become apparent to those of ordinary skill in the art by reading the following detailed description, with reference where appropriate to the accompanying drawings.

