System and method for fiber-based laser speckle imaging

Abstract

An illumination system for laser speckle imaging includes: a laser source; two or more sections of optical fibers; a fiber coupled acousto-optic modulator (FCAOM) coupled to the light source through a first segment of the two or more segments of optical fibers; and collimating optics that focus light output by the laser to illuminate an object within a field of view (FOV), where the collimating optics are coupled to the FCAOM through a second of the two or more segments of optical fibers. In some implementations, the illumination system is incorporated into a laser speckle imaging system that includes an image capture device for capturing an image of an object within the FOV. In some implementations, images are captured and processed using in-exposure modulated speckle imaging techniques.

Description

[0001] STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

[0002] This invention was made with government support under Grant Nos. R01 EB011556 and R01 NS108484 awarded by the National Institutes of Health. The government has certain rights in this invention.

[0003] CROSS-REFERENCE TO RELATED APPLICATIONS

[0004] This application claims priority to and the benefit of U.S. Provisional Patent Application No. 63 / 478,264, filed on January 3, 2023, which is incorporated herein by reference in its entirety. Background Art

[0005] Monitoring cerebral blood flow (CBF) plays an important role in numerous neurosurgical and neuroscience applications. In the operating room, applications for CBF monitoring range from tumor resection, cerebral artery bypass grafting, arteriovenous malformation (AVM) removal, and microvascular clipping of cerebral aneurysms. In neuroscience and preclinical research, CBF monitoring can play an important role in understanding the impact of stroke and stroke recovery. Many imaging techniques are available for monitoring CBF, ranging from optical techniques such as indocyanine green angiography (ICGA) to radiographic techniques such as digital subtraction angiography (DSA); however, these techniques have the disadvantage of requiring contrast agents, which, if used during surgery, can interfere with the surgical procedure and, in the case of DSA, require radiation exposure.

[0006] Laser speckle contrast imaging (LSCI) has become a powerful technique for continuous imaging of CBF without the use of contrast agents. LSCI has been applied both to studying stroke and to studying various surgical and neurosurgical applications. LSCI is a label-free optical technique that can provide continuous monitoring of CBF using simple instrumentation. However, LSCI has several disadvantages that limit its impact in quantifying blood flow. For example, although LSCI reliably detects qualitative changes in flow, LSCI is unable to accurately quantify flow differences or flow changes between different regions or tissue types. This is primarily because LSCI measurements are highly instrument-dependent, cannot account for the effects of static scatterers present in actual tissue, and do not take into account noise. Due to these limitations, LSCI is typically limited to measuring relative changes in blood flow within a single subject during a single experiment. Summary of the Invention

[0007] One implementation of the present disclosure is an illumination system for laser speckle imaging, the illumination system comprising: a light source configured to output light having a wavelength in a range of 600 nm to 2000 nm; two or more lengths of optical fiber; a fiber-coupled acousto-optic modulator (FCAOM), wherein the FCAOM is coupled to the light source through a first length of the two or more lengths of optical fiber; and collimating optics that focus light output by a wavelength-stabilized laser to illuminate an object within a field of view (FOV), wherein the collimating optics is coupled to the FCAOM through a second length of the two or more lengths of optical fiber.

[0008] Another implementation of the present disclosure is a laser speckle imaging system comprising: a light source having an operating wavelength in a range of 600 nm to 2000 nm; an optical fiber; a fiber-coupled acousto-optic modulator (FCAOM), wherein the FCAOM is coupled to the light source via a first segment of optical fiber; collimating optics that focus light output by the light source to illuminate a field of view (FOV), wherein the collimating optics is coupled to the FCAOM via a second segment of optical fiber; and an image capture device for capturing an image of the FOV when the FOV is illuminated by the light source.

[0009] Yet another implementation of the present disclosure is a method of speckle imaging, comprising performing the following operations within a single exposure time of a laser speckle imaging system: operating a light source and an acousto-optic modulator (AOM) of the laser speckle imaging system to illuminate a field of view (FOV) at a plurality of different modulation frequencies; capturing at least one image of the FOV at each of the plurality of different modulation frequencies; calculating speckle contrast for each captured image to create one or more speckle contrast image sets; and extracting an inverse correlation time value at each pixel using the one or more speckle contrast image sets.

[0010] Yet another implementation of the present disclosure is a method for speckle imaging, comprising: operating a light source and an acousto-optic modulator (AOM) of a laser speckle imaging system to generate a first set of pulses with a first time delay between the pulses within a first exposure time of the laser speckle imaging system, wherein light output by the light source illuminates a field of view (FOV); operating the light source and the AOM to generate a second set of pulses with a second time delay between the pulses within a second exposure time of the laser speckle imaging system, wherein the second time delay is different from the first time delay; capturing a series of images of the FOV within each of the first exposure time and the second exposure time; calculating speckle contrast for each image in the series of images to create a corresponding speckle contrast image set; and extracting an inverse correlation time value at each pixel using the speckle contrast image set.

[0011] Additional advantages will be set forth in part in the following description or may be learned through practice. Advantages will be realized and attained by means of the elements and combinations particularly pointed out in the appended claims. It should be understood that both the foregoing general description and the following detailed description are exemplary and illustrative only and are not intended to limit the scope of the invention as claimed. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The various objects, aspects, features and advantages of the present disclosure will become more apparent and better understood by referring to the detailed description taken in conjunction with the accompanying drawings, in which like reference numerals identify corresponding elements throughout. In the drawings, like reference numerals generally indicate identical, functionally similar and / or structurally similar elements.

[0013] Figure 1A is a diagram of an example free-space multi-exposure speckle imaging (MESI) system, according to some implementations.

[0014] Figure 1B is a diagram of another example MESI system according to some implementations.

[0015] Figure 2 is a diagram of a fiber-coupled laser speckle imaging system according to some implementations.

[0016] Figure 3 is a diagram of an example image processing pipeline according to some implementations.

[0017] Figure 4A and Figure 4B is a diagram illustrating example gating of a MESI pulse sequence according to some implementations.

[0018] Figure 5 is a graph illustrating relative microfluidic flow rates for an example microfluidic flow scheme, according to some implementations.

[0019] Figure 6A and Figure 6B is to illustrate the use of some implementations Figure 1A The traditional MESI system and Figure 2 Plot of the percent deviation of accuracy and repeatability measurements performed by the FCMESI system.

[0020] Figure 7 Is based on the use of some implementations Figure 1A The traditional MESI system and Figure 2 Example of in vivo imaging performed with the FCMESI system.

[0021] Figure 8A is used in stroke models according to some implementations Figure 2 Example in vivo images captured by the FCMESI system.

[0022] Figure 8B Based on some implementations Figure 8A Plot of the mean speckle variance for in vivo images.

[0023] Figure 9 is a flow chart of a process for intra-exposure modulated speckle imaging using frequency modulation, according to some implementations.

[0024] Figure 10 is a flow chart of a process for intra-exposure modulated speckle imaging using time delay modulation, according to some implementations.

[0025] Figure 11 is a diagram showing some implementations Figure 9 An example diagram of the intra-exposure modulation speckle imaging process in .

[0026] Figure 12 is a diagram showing some implementations Figure 10 An example diagram of the intra-exposure modulation speckle imaging process in .

[0027] Figure 13A is a graph of an example temporal relationship between intensity modulation and camera exposure according to some implementations.

[0028] Figure 13B is a graph illustrating an example autocorrelation function according to some implementations.

[0029] Figure 13C is a diagram of a workflow for extracting correlation times for dual-pulse modulation multi-exposure images, according to some implementations.

[0030] Figure 14A is an example of an original image and a speckle contrast image acquired using a dual-pulse modulation method according to some implementations.

[0031] Figure 14B It is based on some implementation methods Figure 14A The images in the graph compare the measured flow rates.

[0032] Figures 15A to 15C is a graph illustrating test results of the dual-pulse modulation method described herein, according to some implementations.

[0033] Figure 16A and Figure 16B is a graph comparing measured flow rates using double-pulse modulation and sinusoidal modulation, according to some implementations. DETAILED DESCRIPTION

[0034] To address some of the limitations of LSCI described above, multi-exposure speckle imaging (MESI) was developed as an extension of LSCI. MESI requires collecting LSCI images over a wide range of exposure times and can extract quantitatively accurate measurements of CBF from this series of images. This is possible because MESI allows the effects of instrumentation, static scatter, and noise to be separated from the actual CBF. MESI has been shown to quantify flow changes with substantially higher accuracy than LSCI, even in the presence of strong static scatter.

[0035] Because MESI requires variations in exposure time, the intensity of the light incident on the camera is modulated for several reasons: first, to ensure sufficient signal at short exposure times; second, to prevent saturation at longer exposure times; and finally, to produce similar average intensity across exposure times to minimize variations in the camera and shot noise. Traditionally, this intensity modulation is accomplished using an acousto-optic modulator (AOM), which acts as a variable amplitude gate for the illumination. This additional instrumentation significantly increases the complexity of MESI compared to traditional single-exposure LSCI. A pilot clinical study of intraoperative MESI during brain tumor resection surgery found improved quantitative measurements of CBF compared to single-exposure LSCI, but the study was limited to very low temporal resolution because the constraints of the clinical environment prevented the use of an AOM and required manual adjustment of light intensity.

[0036] To further address these and other limitations of conventional MESI systems, according to some implementations, a fiber-coupled MESI (FCMESI) illumination system using a fiber-coupled laser and a fiber-coupled AOM (FCAOM) is described herein. The system is compact and less complex than other MESI systems, and unlike other systems, the system utilizes an FCAOM. The FCMESI system described herein is generally based on the principles of existing free-space MESI systems, but reduces many of the instrumentation challenges of existing systems by using fiber-based components. As discussed in more detail below, the FCMESI system described herein performs comparable to or better than conventional MESI systems in both microfluidics and in vivo experiments. Furthermore, the illumination arm of the FCMESI system described herein can be used with many other types of speckle imaging systems and is not limited to MESI applications.

[0037] In addition to the FCMESI system mentioned above, this article also describes a LSCI method called "within-exposure modulated speckle imaging" or intensity modulated imaging. The traditional illumination method is to keep the laser at a constant intensity throughout the camera exposure time. The exposure time can be varied to increase sensitivity to certain flow ranges. However, using this traditional method, it can be difficult to obtain reproducible blood flow values. Currently, the only way to increase the sensitivity of LSCI to high flows is to reduce the camera exposure time to very short values (e.g., microseconds). These very short exposure times require high illumination powers to detect enough light to capture the speckle pattern. Such high powers are generally not possible due to limitations of the laser diode and / or safety restrictions. Notably, modulated intensity imaging is more sensitive to high flow values without reducing the camera exposure time to excessively short values, which enables imaging of high flows at lower average powers.

[0038] Intra-exposure modulated speckle imaging involves varying the intensity of laser illumination within the exposure time of an imaging device (e.g., a camera). The speckle contrast of the image resulting from the modulated illumination can then be correlated with the underlying flow dynamics in a more quantitative manner. The intensity modulation within the camera exposure can be pulsed, sinusoidal, or any other function. Because the laser illumination is coherent, the speckle contrast of the modulated illumination, integrated within the camera exposure time, will vary depending on the temporal characteristics of the laser illumination. Thus, by varying the nature of the intensity modulation, the sensitivity of the blood flow image can be tuned to different flow levels. Additional details are provided below.

[0039] Overview

[0040] In LSCI, decorrelation of the speckle pattern due to dynamic scattering events results in blurring within the exposure time of the camera device, which is quantified by the speckle contrast K, defined as:

[0041]

[0042] where σ is the standard deviation, and is the average intensity over a sliding window of pixels. Based on the square of the speckle contrast (which is called the speckle variance), the correlation time, a measure of how quickly the speckle pattern decorrelates, can be calculated as follows:

[0043]

[0044] where β is the constant instrument factor, T is the exposure time, and τ c is the correlation time. The inverse of the correlation time (ICT = 1 / τ) is called the inverse correlation time. c ) is directly related to flow and is often used as a measure of flow; when monitoring flow changes, relative ICT (rICT) is often reported—that is, ICT normalized to some reference value. However, Equation 2 is based on several simplifying assumptions, such as the absence of static scattering events. These simplifying assumptions limit the accuracy and repeatability of LSCI.

[0045] MESI is based on a more rigorous model that takes into account static scattering events and non-ideal conditions, resulting in the MESI formula:

[0046]

[0047] Where ρ is the ratio of collected photons that undergo dynamic scattering events to the total number of collected photons, v is the noise due to experimental noise and simplifying assumptions made in the model, and all other terms are defined as above. Accounting for these additional factors allows MESI to more accurately quantify changes in flux, especially in the presence of static scatterers. To derive ICT from the MESI equation, speckle contrast images are collected over a range of exposure times, ideally spanning several orders of magnitude, and the MESI equation is then fitted to the data at each pixel. This fitting process allows solving for β, ρ, v, and τ c , and finally calculate the ICT value representing the flow change.

[0048] Multi-Exposure Speckle Imaging (MESI)

[0049] First refer to Figure 1A , a diagram of an example free-space multi-exposure speckle imaging (MESI) system 100 is shown, according to some implementations. System 100 is generally an example of a "traditional" MESI system. As shown, system 100 includes a light source 102 that emits light for imaging. In some implementations, light source 102 is, for example, a laser or laser diode that emits light in the range of 600 nm to 2000 nm. System 100 also includes an isolator 104, followed by a length of optical fiber 106 and an acousto-optic modulator (AOM) 108. In some implementations, optical fiber 106 is configured to optically correct for the anomalous beam shape provided by light source 102. In particular, optical fiber 106 can be terminated with a collimating lens to produce a circular beam. The collimated output can then pass through AOM 108, and aperture 110 can be used to select the first diffraction order of AOM 108. Typically, the AOM 108 is configured to use acoustic waves to diffract and / or shift the frequency of light, or in other words, can be used to control the power / intensity of light emitted by the light source 102 .

[0050] As shown, in some implementations, a series of mirrors and / or lenses can be used to direct light emitted by light source 102; however, it should be understood that the number and / or arrangement of mirrors and / or lenses can vary based on the specific implementation of system 100. In this example, the mirrors direct light toward a flow phantom 112, through which a fluid sample passes for testing. However, in use, the light can be directed toward a blood vessel for measuring blood flow. More generally, light emitted from light source 102 is directed toward the field of view (FOV) of image capture system 114. In this case, the FOV of image capture system 114 includes at least a portion of flow phantom 112. In some implementations, image capture system 114 includes a camera 116 or other suitable device or sensor for capturing images. In some such implementations, camera 116 is a monochrome camera. In some implementations, image capture system 114 includes one or more lenses for magnifying the FOV.

[0051] In some implementations, the system 100 includes a radio frequency (RF) driver 120 for controlling the optical flux of the AOM 108. Specifically, in some such implementations, the RF driver 120 can output an electrical signal at a controlled frequency that excites a piezoelectric transducer or other similar component of the AOM 108 to modulate or adjust the light output by the AOM 108. To synchronize image acquisition via the image capture system 114 with the modulation of the AOM 108, a data acquisition device (DAQ) 122 can also be included. The DAQ 122 can generally be configured to provide command signals to the RF driver 120 to control the modulation of the AOM 108, and can also receive captured image data from the image capture system 114. In some implementations, the system 100 also includes a computing device 124 that can interface with the DAQ 122 to receive image data and further process the image data and / or otherwise control the RF driver 120 and the DAQ 122. In some such implementations, computing device 124 may be a desktop computer, a laptop computer, a server, or any other suitable computing device.

[0052] Figure 1B FIG2 is a diagram of another example MESI system 150, according to some implementations. Similar to system 100, as described above, system 150 includes a light source 102 and an isolator 104, followed by a length of optical fiber 106 and an AOM 108. In some implementations, MESI system 150 can include one or more mirrors and / or lenses positioned between isolator 104 and optical fiber 106 to direct light emitted by light source 102. For example, in the illustrated configuration, system 150 includes two mirrors (labeled "M"), followed by a first lens (L1), and then optical fiber 106. Similarly, a second lens (L2) and a corresponding mirror are positioned after optical fiber 106. However, it should be understood that this particular configuration is not intended to be limiting; rather, the number, arrangement, and / or inclusion of mirrors and / or lenses can vary based on the application, layout, etc.

[0053] In the illustrated implementation, for example, after passing through the AOM 108, two illumination light paths are established, including a widefield path shown by a solid line and a focused path shown by a dashed line. In some implementations, the MESI system 150 is shown as including a flip mirror (labeled "FM") to switch the light between the two paths via the flip mirror; however, it should be understood that the light is typically modulated by the same pulse sequence. After contacting the target 160 (e.g., a sample, a flow phantom 112, etc.), the diffusely reflected light is collected by, for example, an objective lens (L5) and can then be separated by a beam splitter 152. A first portion of the light passes toward the camera 156, while a second portion of the light is reflected toward an avalanche photodiode (APD) 154, for example, for pulse sequence control. In some implementations, the beam splitter 152 is a 50 / 50 beam splitter, for example, so that the first and second portions of the light are approximately equal; however, the present disclosure is not intended to be limited in this respect.

[0054] As shown, the camera 156 collects a first portion of the reflected light and transmits the image data to the computing device 124, for example, for further processing and / or display. The second portion of the reflected light is shown as passing through a lens (L6) and a fiber coupler (FC) to a second optical fiber 158. In some implementations, the second optical fiber 158 is a single-mode fiber (SMF). The light exiting the second optical fiber 158 can pass through one or more lenses (L7, L8) before reaching the APD 154. As will be understood, the APD 154 generates an electrical signal in response to the received light, which is provided to the DAQ 122 to facilitate pulse sequence control. In some implementations, the electrical signal output by the APD 154 passes through a low-pass filter (LFP) or other suitable filter.

[0055] Fiber-coupled laser speckle imaging system

[0056] Now refer to Figure 2 , a diagram of a fiber-coupled laser speckle imaging system 200, according to some implementations, is shown. Generally, the operating principles of system 200 are similar to those of system 100 described above. For example, system 200 includes an illumination arm 202 having a light source 204, which illuminates a field of view (FOV) (e.g., in this example, containing a flow phantom 112) for speckle imaging. However, the illumination arm 202 of system 200 is typically constructed from fiber-coupled components, which significantly reduces the complexity and size of the system. For example, system 200 typically does not require the numerous mirrors used to focus and manipulate light emitted from the light source, as in system 100. As shown, system 200 also does not include isolator 104 or aperture 110. In this regard, system 200 can generally be easier to set up, operate, and use than system 100 due to the reduced number of components, and has fewer points of failure. In some cases, system 200 can even be less expensive to construct than system 100.

[0057] Furthermore, the use of fiber-based components and docking sleeves eliminates the need for careful alignment and realignment of optical components and minimizes the number of components that can accumulate dust, which is particularly important in clinical settings and in laboratories outside the field of optics. Since LSCI applications are growing while MESI adoption is lagging, system 200 can eliminate barriers to MESI adoption for new applications, both in surgery and in new research settings. Given the benefits of MESI, adopting FCMESI in settings where LSCI is currently used will allow for accurate CBF monitoring in a wide range of applications, from neurosurgery to neuroscience.

[0058] It should also be understood that the system 200 is not limited to MESI applications. For example, while the system 200 can be used for multi-exposure speckle imaging, the illumination arm 202 and its components make the system 200 applicable to other forms of laser speckle imaging. In some implementations, the system 200 can be used to implement an intra-exposure modulation method for speckle imaging, as described below with reference to Figures 9 to 12 Intra-exposure modulation is a speckle imaging technique that involves modulating the intensity of light applied to an object within the FOV. Intra-exposure modulation may also be referred to as intensity-modulated speckle imaging. Thus, the present disclosure contemplates that system 200 is suitable for various speckle imaging techniques, including MESI and intra-exposure modulation.

[0059] As shown, the illumination arm 202 of the system 200 also includes a fiber-coupled AOM (FCAOM) 208 coupled to the light source 204 via a first portion of an optical fiber 206. In some implementations, the light source 204 is a volume holographic grating (VHG) stabilized laser diode that outputs light having a dominant wavelength of 785 nm. It should be understood that a VHG-stabilized laser is provided by way of example only. The present disclosure contemplates the use of other laser sources, including, for example, non-wavelength stabilized lasers. Additionally, it should be understood that 785 nm is provided by way of example only. The present disclosure contemplates the use of light sources having a dominant wavelength greater than or less than 785 nm. For example, the light source 204 can operate at a wavelength in the range of 600 nm to 2000 nm.

[0060] In some implementations, the FCAOM 208 has a rise time of 50 ns; however, the FCAOM 208 can be configured for other rise times as contemplated herein. In some implementations, the optical fiber 206—or at least a portion of the optical fiber 206—is part of the light source 204 or is fixedly coupled thereto. Similarly, in some implementations, a portion of the optical fiber 206 or the entire optical fiber 206 can be part of the FCAOM 208 or fixedly coupled thereto. For example, a first portion of the optical fiber 206 can extend relative to the output side of the light source 204, and a second portion of the optical fiber 206 can extend relative to the input side of the FCAOM 208. In some such implementations, the portions of the optical fiber 206 can be coupled via a docking sleeve. However, it should be understood that the specific configuration of the system 200 is not limited to this description. For example, in other implementations, the optical fiber 206 can be a separate component from the light source 204 and / or the FCAOM 208, and thus can be removably coupled to both components.

[0061] In some implementations, the illumination arm 202 further includes a second segment of optical fiber 210 that couples the FCAOM 208 to the collimating optics 212. Optionally, the collimating optics 212 are adjustable-focus collimating optics. In some such implementations, the adjustable-focus collimating optics 212 can be used to adjust the illumination of the FOV (e.g., in the example shown, generally including a portion of the flow phantom 112). As with the optical fiber 206, in some cases, the optical fiber 210 or a portion thereof can be part of the FCAOM 208 (e.g., fixedly coupled thereto). For example, the optical fiber 210 can extend relative to the output of the FCAOM 208. In other implementations, the optical fiber 210 is a separate component from the FCAOM 208 and can therefore be removably coupled to the FCAOM 208 and / or the adjustable-focus collimating optics 212. Typically, one or both of the optical fibers 206, 210 are single-mode optical fibers. It should be understood that the adjustable-focus collimating optics are provided by way of example only. The present disclosure contemplates the use of other collimating optics.

[0062] As with system 100, system 200 is shown to include an image capture system 214 that includes one or more lenses and an image capture device 216. In some implementations, image capture device 216 is any suitable camera or image sensor, such as a monochrome camera (e.g., a 155 μm camera). In the example shown, image capture system 214 includes two lenses. In some implementations, at least one of the lenses is configured to magnify the FOV relative to image capture device 216. In some implementations, image capture system 214 includes a long pass filter to filter out visible light. For example, the long pass filter can be Figure 2 2. The optical fiber optic cable 208 is coupled to the image capture device 216 and includes a plurality of optical fibers, one of which is shown in FIG. Coupled to the image capture device 216 is a DAQ 222 that can receive and optionally process image data captured by the image capture device 216. In some implementations, the DAQ 222 is also configured to trigger the image capture device 216 (e.g., to cause the image capture device 216 to capture one or more images). Optionally, the DAQ 222 can be communicatively coupled to an RF driver 220 that modulates the optical flux of the FCAOM 208 by applying an electrical signal to the FCAOM 208. Specifically, the DAQ 222 can communicate with the RF driver 220 to synchronize optical output or modulation with the triggering of the image capture device 216.

[0063] In some implementations, the system 200 includes a controller 230 that also communicates with one or both of the RF driver 220 and the DAQ 222. Generally, the controller 230 is configured to receive, process, and / or store image data from the DAQ 222. In some implementations, the controller 230 performs all of the functions of the DAQ 222; thus, the DAQ 222 may not be included. In some implementations, the controller 230 provides control signals to the RF driver 220 (e.g., as opposed to the DAQ 222 providing control signals), thereby coordinating the operation of the components of the illumination arm 202 and the image capture system 214. It should be understood that any such arrangement and implementation of the components of the system 200 is contemplated herein.

[0064] As shown, the controller 230 generally includes a processor 232 and a memory 234. Thus, the controller 230 can be any suitable computing device (e.g., a laptop computer, a server, etc.). The processor 232 can be a general-purpose processor, an application-specific integrated circuit (ASIC), one or more field-programmable gate arrays (FPGAs), a set of processing components, or other suitable electronic processing structures. In some embodiments, the processor 232 is configured to execute program code stored on the memory 234 to cause the controller 230 to perform one or more operations as described in more detail below. In some implementations, the controller 230 can be part of another computing device (e.g., the DAQ 222 or another computer); thus, components of the controller 230 can be shared with or identical to a host device.

[0065] Memory 234 may include one or more devices (e.g., memory units, storage devices, storage devices, etc.) for storing data and / or computer code used to perform and / or facilitate the various processes described in this disclosure. In some embodiments, memory 234 includes tangible (e.g., non-transitory) computer-readable media that stores code or instructions executable by processor 232. Tangible computer-readable media refers to any physical medium that can provide data that causes controller 230 to operate in a specific manner. Example tangible computer-readable media may include, but are not limited to, volatile media, non-volatile media, removable media, and non-removable media implemented in any method or technology for storing information such as computer-readable instructions, data structures, program modules, or other data. Thus, memory 234 may include RAM, ROM, hard drive storage, temporary storage, non-volatile memory, flash memory, optical storage, or any other suitable memory for storing software objects and / or computer instructions. Memory 234 may include database components, object code components, script components, or any other type of information structure used to support the various activities and information structures described in this disclosure. Memory 234 may be communicatively connected to processor 232 and may include computer code for executing (eg, via processor 232 ) one or more of the processes described herein.

[0066] Although shown as separate components, it should be understood that the processor 232 and / or memory 234 can be implemented using a variety of different types and quantities of processors and memories. For example, the processor 232 can represent a single processing device or multiple processing devices. Similarly, the memory 234 can represent a single memory device or multiple memory devices. Additionally, in some embodiments, the controller 230 can be implemented within a single computing device (e.g., a server, a housing, etc.). In other embodiments, the controller 230 can be distributed across multiple devices (e.g., it can be present in distributed locations). For example, the controller 230 can include multiple distributed computing devices (e.g., multiple processors and / or memory devices) that communicate with each other and collaborate to perform operations.

[0067] Experimental setup and results

[0068] The ability of both the AOM 108 and the FCAOM 208 to gate the laser illumination was tested using appropriate photodiodes. A pulse sequence covering the first ten exposure times in the MESI pulse sequence was supplied to each of the AOM 108 and the FCAOM 208 (e.g., via the respective light sources 102, 204), and the optical power was measured. A microfluidic flow phantom (e.g., the flow phantom 112) was used to test the system's ability to quantify flow changes. For these tests, the flow phantom 112 comprised polydimethylsiloxane (PDMS) with titanium dioxide added to simulate the scattering properties of tissue. A 300×300 μm square channel was embedded in the phantom, which had a glass coverslip glued on top, and plastic tubing was connected to create the inlet and outlet of the channel.

[0069] A solution of polystyrene microspheres with a diameter of 1.1 μm in deionized water was used to create a solution that simulates the optical properties of blood at 785 nm (e.g., the wavelength of light source 204). Specifically, the scattering coefficient of the microspheres was calculated using Mie theory, and the concentration was then adjusted to match the reduced scattering coefficient of blood (1.3 μm). -1 The solution consisted of the following by volume: 4.8% microsphere solution; 0.1% Tween (P1379-100ML, Sigma-Aldrich), which was used to prevent the microspheres from clumping; and the rest was deionized water.

[0070] The flow in the external flow control system (not shown) regulation system is used.In a word, polystyrene solution is stored in the reservoir that is connected to pressure regulator, and the outlet of reservoir is connected to the plastic tube that reservoir is connected to microfluidic channel entrance.The outlet of microfluidic channel is placed in an independent collection reservoir.Use two independent flow sensors to monitor flow at two different points, a flow sensor before channel, and a flow sensor after channel.Two flow sensors are connected to the control center with control computer (for example, controller 230) interface.

[0071] The flow rate is set to a step function, ranging from 1 mm / s to 10 mm / s, with an interval of 1 mm / s. Each step is maintained for 90 seconds, and the entire protocol is followed by a 30-second period in which the flow rate is set to 0 mm / s. The total experimental time is 15.5 minutes. The protocol is carried out when imaging two conditions using a free space MESI system, i.e., system 100, and a FCMESI system, i.e., system 200. MESI images are continuously acquired throughout the protocol for a total of 1950 image sequences, each of which includes 15 images collected at 15 different exposure times. For system 200, the protocol was carried out three separate times, with the start of each experiment spaced approximately 20 minutes apart. Since free space MESI systems, such as system 100, have been fully tested by others in the art in the past, the microfluidic protocol was only carried out once with this system.

[0072] For testing, mice were anesthetized with isoflurane and maintained at body temperature with a heating pad during all procedures. Two mice underwent craniectomy to remove a portion of the skull and replace the portion with a glass cover slip fixed with dental cement. Photothrombotic stroke was induced in one of the mice by injecting rose bengal dye and then illuminating the area of the cortical surface with 532nm light, thereby causing a stroke. Photothrombotic stroke was induced in one of the mice by retroorbital injection of rose bengal dye (15mg / kg) and then focusing 532nm light on the penetrating arterioles in the motor cortex. MESI was performed three weeks after stroke induction, and each mouse was imaged through a cranial window using both free space and FCMESI systems, systems 100 and 200. For each imaging session, 56 sequences were acquired, each consisting of 15 frames with 15 different exposure times.

[0073] Then, based on Figure 3 The example image processing pipeline 300 shown performs processing on the collected images. For each raw image collected, such as raw image 302, speckle contrast is calculated over a 7×7 pixel sliding window to produce a speckle contrast image 304. For the microfluidics experiment, a 40×40 pixel region of interest (ROI) was selected to correspond to the width of the microfluidic channel in the FCMESI (e.g., system 200) image. Within this ROI in the speckle contrast image, an arithmetic mean is calculated to produce a single speckle contrast value at each exposure time, as shown in graph 306. Using this mean, the measured K 2 (T) was fitted to Equation 3 above to obtain ICT. Considering the numerical stability of the fitting results in Equation 3, β was selected as a constant value during the fitting process to remove one of the four variables from the fitting process. The β value was selected by finding the median value of K for each exposure time for each frame in the 1 mm / s step of the microfluidic step function, fitting this data to Equation 3, and selecting the resulting β value as its true constant value.

[0074] In order to eliminate the influence of the conversion time between flow rates in the flow scheme, 25 frames of data on each side of the midpoint of the conversion between speeds are removed. The cutting of this data and the subsequent ICT fitting produce a sequence of ICT values corresponding to the ten steps in the step function. All ICT values are normalized to the average ICT value for the slowest flow rate to produce the time course of rICT values, as shown in graph 308. Relative microfluid flow (rM) is obtained by taking the average flow value of two flow sensors and then taking the average value under each flow rate, normalized to the first step. Then, rICT is drawn for the relative microfluid flow of each flow rate, as shown in graph 310.

[0075] For each step in the step function, the arithmetic mean of ICT was obtained for each trial. In addition, using rICT and the mean of the relative microfluidic (rM) value at each step, the accuracy (Δ ACC ) and repeatability (Δ REP ) average percentage deviation:

[0076]

[0077] These metrics allow for accurate determination of flow rate changes (Δ ACC ) and the stability of these measurements (Δ REP Since three separate experiments were performed on the system 200, the Δ ACC and Δ REP The mean and standard deviation of .

[0078] For in vivo imaging, speckle contrast was calculated for each image in the image. All images captured at the same exposure were averaged together to produce a dataset consisting of 15 averaged images for each of 15 different exposure times. ICT was then obtained across the entire relevant FOV by fitting the data at each pixel to the MESI equation. To image the stroke model using the FCMESI system, three ROIs corresponding to vessels, parenchyma, and infarct were selected, and the goodness of fit to the MESI equation was determined.

[0079] Now refer to Figure 4A and Figure 4B , according to some implementations, a graph illustrating example gating of a MESI pulse sequence is shown. As shown, both a free-space AOM (e.g., AOM 108) and a FCAOM 208 demonstrate similar capabilities for gating optical signals of a MESI sequence of different exposure times. For example, Figure 4A The signal intensity for both AOM 108 and FCAOM 208 over ten exposure times is shown. For each of the ten different exposure times, each AOM modulates the optical flux to reduce the instantaneous optical power as exposure time increases. Because AOM 108 and FCAOM 208 have unique calibration curves, the absolute value of the optical power differs between each pulse train, but each pulse train produces a pulse train of comparable shape. Furthermore, each individual pulse within a train has a similar shape, form, and rise time, despite differing absolute measurements. Figure 4B pass Figure 4A A close-up view of the second pulse is shown illustrating these characteristics.These results indicate that there is no substantial difference in the ability of the two systems to generate MESI pulse sequences.

[0080] Figure 5 Example graphs of rICT plotted against rM for each of the 10 speeds in a step function for four test runs (e.g., three for system 200 and one for system 100, as described above) of a microfluidic flow regime are shown. Although rICT and rM are not equal in all steps, they are similar throughout the step function. Notably, the rICT from system 100 is almost always within the range of values from the trials with system 200, indicating that the performance of system 200 in measuring flow changes in microfluidic channels is comparable to that of the more traditional free-space MESI (e.g., system 100). Although Δ ACC The standard deviation of is large enough at lower speeds (eg, less than or equal to 4 mm / s), but the average Δ ACC Less than the average delta of the system 100 at all speeds ACC , so that the performance of system 100 falls within the expected performance of system 200, as Figure 6A shown.

[0081] In particular, Figure 6A and Figure 6B The percentage deviation of the accuracy and repeatability measurements is shown, with the error bars representing the range of standard deviation from the mean. The performance of system 200 is represented by the blue bars, while the performance of system 100 is shown in orange. Figure 6A The percentage deviation of accuracy (Δ ACC ) versus flow rate. At all flow rates, the average error in accuracy for system 200 is lower than the average error in accuracy for older systems (e.g., system 100), although there are large error bars for the 2 mm / s to 4 mm / s step. Figure 6B The repeatability percentage deviation (Δ REP Although there is no consistent trend in repeatability across all flow rates, the upper bound of the error at each rate is less than 6%, with no substantial difference between the two systems. In summary, despite the hardware changes, this data demonstrates that System 200 offers comparable accuracy and repeatability to System 100.

[0082] Since the flow rates in the previously mentioned microfluidic systems have been shown to be very stable, accuracy and repeatability issues with rICT are generally caused by errors in MESI imaging and fitting to the MESI equation. In terms of accuracy, MESI appears to systematically underestimate the flow rate in almost all cases, especially for velocities of 3 mm / s to 5 mm / s. This problem may be caused by the stability of the numerical calculations, especially the fact that β is treated as a constant, thereby potentially introducing systematic biases. This can be addressed by fitting different βs, different fitting algorithms, or even utilizing different models or using several models depending on the flow conditions. Despite these potential numerical deficiencies, FCMESI (e.g., system 200) is able to quantify flow changes with accuracy and repeatability at the level of previous MESI systems (e.g., system 100), and FCMESI has been shown to have significant advantages in quantifying flow changes compared to single-exposure LSCI.

[0083] Now refer to Figure 7 , according to some implementations, shows example in vivo images from the previously mentioned mouse experiments. Figure 7 Specifically, shown are: in the upper left corner, an image of a control mouse collected on system 100; in the upper right corner, an image of a stroke model collected on system 100, with the infarct marked within the box; in the lower left corner, an image of a control mouse collected on system 200; and in the lower right corner, an image of a stroke model collected on system 200, with the infarct marked within the box. In mouse imaging, both system 100 and system 200 were able to detect infarcts in stroke mice and map the vasculature of healthy mice. Due to the different magnifications on the two systems, the vascular networks are not completely comparable, and system 100 has higher resolution due to the higher magnification. However, all major features on the cortical surface are clearly visible in both sets of images, demonstrating that FCMESI (e.g., system 200) can image neurovascular networks.

[0084] To further demonstrate the capability of FCMESI in wide-field mouse imaging, different ROIs were selected in FCMESI images of a stroke model. Each of these three ROIs corresponds to a different salient feature: vessel, parenchyma, and infarct, as shown in Figure 2. Figure 8A The speckle contrast was averaged across each ROI and fitted to Equation 3, and the fit was plotted against the measured data as Figure 8B As shown. Calculated τ c The trend is as expected, as it is highest in infarcts (τ c =938μs), slightly lower in the parenchyma (τ c = 349 μs) and is much lower in blood vessels (τ c =75.4μs), the result and τ c The inverse relationship between FCMESI and CBF was consistent. The goodness of fit, as determined by mean squared error (MSE), was best in vessels (MSE = 0.0054) and worst in infarcts (MSE = 0.0171), with the parenchymal fit quality falling between the two (MSE = 0.0109), indicating a correlation between increasing flow and increasing goodness of fit to the MESI formula. Taken together, these fits demonstrate that FCMESI can discriminate between different flow velocities in different tissue structures within the mouse brain, providing further evidence that system 200 can be used in clinical settings with complex anatomy.

[0085] Intra-exposure modulated speckle imaging

[0086] As described above, intra-exposure modulated speckle imaging generally involves varying the intensity of laser illumination during the exposure time of an imaging device (e.g., a camera). In some implementations, the intensity of the laser (e.g., a light source) is varied by modulating the optical flux of an AOM (e.g., AOM 108, FCAOM 208). The AOM modulation function can be defined as m(t), the complete speckle signal can be defined as I(t), and the modulated speckle signal can be defined as I m (t), such that:

[0087] I m (t)=I(t)m(t)

[0088] Then, during the intensity modulation exposure time T, the intensity of pixel i on the image capture device (e.g., camera sensor) will be

[0089]

[0090] Among them, I i (t) is the complete speckle signal for pixel i, and m(t) is the modulation function with respect to the illumination intensity.

[0091] Then, the intensity modulation can be defined as:

[0092]

[0093] And the expression of the speckle contrast of the intra-exposure intensity modulated speckle signal is:

[0094]

[0095] where K is the speckle contrast, g2 is the blood flow, and M(τ) is the intensity modulation. Note that when the modulation function m(t) is a constant 1, M = T - τ, and this equation reduces to the conventional speckle contrast expression (e.g., as described above). In other words, the classical expression for speckle contrast is a special case when the illumination intensity remains constant.

[0096] Regarding square wave modulation, the speckle contrast expression can be defined as:

[0097]

[0098] Assume that g2(τ)-C decreases to 0 before M2(τ) starts, that is, τ c <<T min / d, where C is the constant part of g2(τ), i.e., lim τ→∞ g2(τ)=C.

[0099] Substituting the assumed g2(τ) into this formula, the relationship between speckle contrast and correlation time in different g2(τ) models can be established as follows:

[0100]

[0101]

[0102] in, and Here, The above equations correspond to Gaussian, Lorentz and square root g2(τ) models respectively.

[0103] Now refer to Figure 9 , according to some implementations, a flow chart of a process 900 for intra-exposure modulated speckle imaging using frequency modulation is shown. In some implementations, the process 900 is implemented using / by the system 200, as described above. For example, the process 900 may be implemented at least in part by the controller 230. Additionally or alternatively, the process 900 may be implemented at least in part by the RF driver 220 and / or the DAQ 222. However, it should be understood that the process 900 may also be implemented by the system 100 or the system 150 (e.g., by the computing device 124) or other suitable laser speckle imaging systems. In some cases, certain steps of the process 900 may be optional, and the process 900 may be implemented using less than all steps. It should also be understood that Figure 9 The order of the steps shown in is not intended to be limiting.

[0104] It should also be noted that, as described below, one or more steps of process 900 can be implemented within a single exposure of an image capture device (e.g., camera 156, image capture device 216) defined by time T; hence the term "intra-exposure modulation" speckle imaging. In some implementations, at least steps 902 and 904 are performed with exposure time (T); however, steps 906 and / or 908 can also be performed within the exposure time. Figure 9 For the following description, reference can be made to the above-mentioned various formulas.

[0105] At step 902, the intensity of light applied to the field of view (FOV) of the MESI system is varied over an exposure time (T). In some implementations, the intensity of the light varies sinusoidally; however, other waveforms are contemplated herein. In this regard, the FOV is illuminated at multiple different modulation frequencies. In some implementations, the intensity of the light is modulated by controlling a light source, such as the isolator 104 or the light source 204. For example, the controller 230 may control the light source 204 by sending a control signal and / or modulating the power to the light source 204. In some implementations, the intensity of the light is modulated by controlling an AOM, such as the AOM 108 or the FCAOM 208. In some such implementations, the controller 230 may cause the RF driver 220 to modulate the light flux of the FCAOM 208 to illuminate the FOV at various modulation frequencies. Alternatively, the RF driver 220 may control the FCAOM 208 based on data provided by the DAQ 222. Likewise, in some implementations, the DAQ 122 and / or the computing device 124 can control the AOM 108 to modulate the light flux of the AOM 108 .

[0106] However, it should be understood that controlling the light source and / or AOM of a laser speckle imaging system (e.g., system 150) is not the only way to modulate / change the intensity of light over time. Therefore, the present disclosure contemplates various other methods of achieving modulation of light intensity. For example, in any of the systems 100, 150, or 200, the intensity of light can be modulated using (e.g., by controlling) one or more of an electro-optical modulator (EOM), direct modulation of the laser diode current (e.g., electrical modulation), or mechanical modulation (e.g., a chopper wheel). These and other techniques for modulating light intensity are contemplated herein, such as the technique in step 902.

[0107] Figure 11 An example of modulation of light illuminating a FOV is shown in FIG, where five different modulation frequencies (ω) are shown within an exposure time T of an image capture device (e.g., camera 156, image capture device 216). In some implementations, the light illuminating the FOV can be modulated at each modulation frequency within a single exposure time T. For example, the light flux of the FCAOM 208 can be emitted (e.g., onto the FOV) at each modulation frequency within a single exposure time, such that the modulation frequency of the light varies throughout the exposure.

[0108] At step 904, at least one image of the FOV is captured at each modulation frequency. In some implementations, the DAQ 222 and / or the controller 230 can store images for the entire exposure time T of the image capture device 216 to generate a sequence of images at different modulation frequencies. Similarly, the computing device 124 can store images for the exposure time T of the camera 156. Subsequently, at step 906, the speckle contrast (K) is calculated for each captured image. In general, the speckle contrast will vary depending on the modulation frequency. For example, at Figure 11 In , five different modulation frequencies are used to create speckle contrast image sets K(ω1), K(ω2), K(ω3), K(ω4), and K(ω5).

[0109] At step 908, the inverse correlation time (τ c ) value. In some implementations, each speckle contrast image set (e.g., K(ω1), K(ω2), K(ω3), K(ω4), and K(ω5)) is used to extract the inverse correlation time (τ c ) value. The above describes the calculation of the inverse correlation time (τ c Alternatively, at step 910, the above formula may be used again to determine the blood flow (g2) based on the inverse correlation time value at each pixel.

[0110] Now refer to Figure 10 , according to some implementations, a flow chart of a process 1000 for intra-exposure modulated speckle imaging using time delay modulation is shown. In some implementations, the process 1000 is implemented using / by the system 200, as described above. For example, the process 1000 may be implemented at least in part by the controller 230. Additionally or alternatively, the process 1000 may be implemented at least in part by the RF driver 220 and / or the DAQ 222. However, it should be understood that the process 1000 may also be implemented by the system 100 or the system 150 (e.g., by the computing device 124) or other suitable laser speckle imaging system. In some cases, certain steps of the process 1000 may be optional, and the process 1000 may be implemented using less than all steps. It should also be understood that Figure 10 The order of the steps shown in is not intended to be limiting. Figure 10 For the following description, reference can be made to the above-mentioned various formulas.

[0111] At step 1002, the intensity of light applied to the field of view (FOV) of the MESI system is varied over an exposure time (T) to produce at least two through-time delays (t d ) separated pulses. In some implementations, the intensity of the light is modulated by controlling a light source, such as the isolator 104 or the light source 204. For example, the controller 230 may control the light source 204 by sending a control signal and / or modulating the power to the light source 204. In some implementations, the intensity of the light is modulated by controlling an AOM, such as the AOM 108 or the FCAOM 208. In some such implementations, the controller 230 may cause the RF driver 220 to modulate the light flux of the FCAOM 208 to illuminate the FOV at various modulation frequencies. Alternatively, the RF driver 220 may control the FCAOM 208 based on data provided by the DAQ 222. Similarly, in some implementations, the DAQ 122 and / or the computing device 124 may control the AOM 108 to modulate the light flux of the AOM 108.

[0112] However, it should be understood that controlling the light source and / or AOM of a laser speckle imaging system (e.g., system 150) is not the only way to modulate / change the intensity of light over time. Therefore, the present disclosure contemplates various other methods of achieving modulation of light intensity. For example, in any of the systems 100, 150, or 200, the intensity of light can be modulated using (e.g., by controlling) an EOM, direct modulation of the laser diode current (e.g., electrical modulation), or mechanical modulation (e.g., a chopper wheel). These and other techniques for modulating light intensity are contemplated herein, such as the technique in step 1002.

[0113] Figure 12 An example of modulation of the light illuminating the FOV is shown in FIG. In this example, three different sets of pulses are shown, each with a different time delay (t d ). In some implementations, each set of pulses is emitted in a separate exposure. For example, Figure 12 In the example above, three different exposure times may be required to capture each set of pulses. However, each set of pulses is typically performed within a single exposure time.

[0114] At step 1004, at least one image of the FOV is captured for each set of pulses, or in other words, for each time delay. For example, in some implementations, the DAQ 222 and / or the controller 230 capture multiple sets of images to generate a sequence of images at each different delay time. Subsequently, at step 1006, the speckle contrast (K) is calculated for each captured image. Typically, the speckle contrast will be calculated based on the delay time (t d ). For example, in Figure 12 In the above example, three different delay times are used to create the speckle contrast image set K(t d1 ), K(t d2 ) and K(t d3 ).

[0115] At step 1008, the inverse correlation time (τ c ) value. In some implementations, each speckle contrast image set (e.g., K(t d1 ), K(t d2 ) and K(t d3 )) is used to extract the inverse correlation time (τ) at each pixel c ) value. The above describes the calculation of the inverse correlation time (τ c Alternatively, at step 1010, the above formula may be used again to determine the blood flow (g2) based on the inverse correlation time value at each pixel.

[0116] Additional experimental results

[0117] Now refer to Figures 13A to 16B , in general, presents additional details and related experimental results regarding the disclosed intra-exposure modulation technique. The results presented herein are based on the use of a technique similar to Figure 1B The results are obtained with an experimental setup for the configuration shown (e.g., system 150); however, it should be understood that, in some cases, these results more generally represent the feasibility of the disclosed intra-exposure modulation technique on various MESI systems, including system 100 and / or system 200.

[0118] Figure 13A The temporal relationship between intensity modulation and camera exposure is shown. In this figure, the x-axis is time. The AOM line represents the voltage signal of the AOM (e.g., AOM 108) or other method used to modulate the laser intensity. As shown, the target is illuminated only when the AOM modulation voltage is high. Therefore, for I t Only the signal when AOM is high will be recorded and integrated into the original image of the camera device. Figure 13B The autocorrelation function of a 2-pulse modulation waveform is shown. The intensity modulation waveform m(t) can be defined as m(t)∈[0,1]. The autocorrelation of m(t), defined as M(τ), includes two pulses represented as M0 and M1 in this figure. When T m As it approaches zero, M(τ) becomes the sum of two delta functions. Figure 13C The workflow for extracting correlation time from 2-pulse modulated multi-exposure raw images is shown. First, the 2-pulse modulation speckle contrast K is calculated based on the modulated raw speckle image. 2 2P , and then fitting its trajectory along the third dimension T with different electric field autocorrelation g1(τ) models (n=2, 1 or 0.5). By making the coefficient of determination R 2 Maximization is used to identify the best g1(τ) model.

[0119] Figure 14A and Figure 14B The normalized K in the flow phantom is shown in general. 2 2P Experimental verification of the consistency between τ and g2(τ). Figure 14A Includes an image acquired using the 2-pulse modulation method (left) and a speckle contrast image calculated from the 2-pulse modulation original image (right). Figure 14B is the normalized K measured in 10 μL / min steps at flow rates ranging from 0 μL / min to 100 μL / min. 2 2P Plot comparing (T) (shown as dots) with measured g2(τ) (shown as a solid line).

[0120] Figures 15A to 15C The normalized K in vivo in mouse brain is shown overall. 2 2P Experimental verification of the consistency between τ and g2(τ). Figure 15A It is a speckle contrast image calculated based on the 2-pulse modulated original image. Figure 15B It will be like Figure 15A The normalized K of the measurements at three different spatial positions indicated by P1, P2 and P3 in 2 2P A graph comparing (T) (shown as dots) with g2(τ) (shown as a solid line). The tilde above the symbol in the legend indicates the normalized quantity. Figure 15C It will be K from the body 2 2P A plot comparing the inverse correlation time (ICT) values extracted from g2(τ) shows excellent agreement between the two measurement types. In these example images, 28 points from four mice are shown.

[0121] Figure 16A and Figure 16B Generally shown is the experimental validation of sinusoidal modulation within the exposure in a flow phantom. Figure 16A is the normalized K measured with 2-pulse modulation 2 2P Plots of g(T) and g2(τ) for flow rates ranging from 0 μL / min to 80 μL / min. Figure 16B is the measured K extracted from the single-point intensity measurement 2 c Graph of the power spectrum density (PSD) (shown as dots) and the normalized power spectrum density (PSD) (shown as a solid line) for a flow rate range of 0 μL / min to 80 μL / min. In this example, ω represents the angular modulation frequency ( Figure 11 ). As the modulation frequency ω changes, K 2 c The (ω) values match the PSD values.

[0122] Configuration of some implementations

[0123] The construction and arrangement of the systems and methods as shown in various implementations are illustrative only. Although only some implementations are described in detail in this disclosure, many modifications are possible (e.g., changes in the size, dimensions, structure, shape and proportion of various elements, parameter values, installation arrangements, use of materials, colors, orientations, etc.). For example, the positioning of elements can be interchanged or otherwise changed, and the properties or number of discrete elements or positioning can be changed or altered. Therefore, all such modifications are intended to be included within the scope of this disclosure. According to alternative implementations, the order or sequence of any process or method steps can be changed or reordered. Without departing from the scope of this disclosure, other replacements, modifications, changes and omissions can be made in the design, operating conditions and arrangement of the implementation.

[0124] The present disclosure contemplates a program product on a method, system, and any machine-readable medium for completing various operations. The implementation of the present disclosure can be implemented using an existing computer processor, or implemented by a dedicated computer processor for an appropriate system incorporated for this purpose or another purpose, or implemented by a hard-wired system. The implementation within the scope of the present disclosure includes a program product, which includes a machine-readable medium for carrying or storing machine-executable instructions or data structures thereon. Such a machine-readable medium can be any available medium that can be accessed by a general-purpose or special-purpose computer or other machine with a processor. For example, such a machine-readable medium can include RAM, ROM, EPROM, EEPROM, CD-ROM or other optical disk storage devices, magnetic disk storage devices or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of machine-executable instructions or data structures and can be accessed by a general-purpose or special-purpose computer or other machine with a processor.

[0125] When information is transferred or provided to a machine over a network or another communications connection (hardwired, wireless, or a combination of hardwired and wireless), the machine effectively views the connection as a machine-readable medium. Therefore, any such connection is effectively referred to as a machine-readable medium. The above combinations are also included within the scope of machine-readable media. Machine-executable instructions include, for example, instructions and data that cause a general-purpose computer, a special-purpose computer, or a dedicated processing machine to perform a specific function or group of functions.

[0126] Although the accompanying drawings show a specific order of method steps, the order of the steps may be different from that depicted. In addition, two or more steps may be performed simultaneously or partially simultaneously. Such variations will depend on the selected software and hardware systems and on the designer's choice. All such variations are within the scope of this disclosure. Similarly, software implementations can be accomplished using standard programming techniques and rule-based logic and other logic to complete various connection steps, processing steps, comparison steps, and decision steps.

[0127] It should be understood that the methods and systems are not limited to specific synthetic methods, specific components or specific compositions. In addition, it should be understood that the terminology used herein is for the purpose of describing particular implementations only and is not intended to be limiting.

[0128] As used in the specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the context clearly indicates otherwise. Ranges may be expressed herein as from "about" one particular value and / or to "about" another particular value. When such a range is expressed, another implementation includes from one particular value and / or to the other particular value. Similarly, when a value is expressed as an approximation by using the antecedent "about," it will be understood that the particular value forms another implementation. It will also be understood that the endpoints of each range in a range are significant both in relation to the other endpoint and independently of the other endpoint.

[0129] "Optional" or "optionally" means that the subsequently described event or circumstance may or may not occur, and that the description includes instances where said event or circumstance occurs and instances where it does not.

[0130] Throughout the description and claims of this specification, the word "comprise" and variations thereof, such as "comprising" and "comprises," mean "including, but not limited to," and are not intended to exclude, for example, other additives, components, integers, or steps. "Exemplary" means "an example of..." and is not intended to indicate a preferred or ideal implementation. "Such as" is not used in a limiting sense, but rather for illustrative purposes.

[0131] Components that can be used to perform the disclosed methods and systems are disclosed herein. These and other components are disclosed herein, and it should be understood that when combinations, subsets, interactions, groups, etc. of these components are disclosed, while specific reference to each different individual and collective combination and arrangement of these components may not be explicitly disclosed, each is specifically contemplated and described herein for use in all methods and systems. This applies to all aspects of this application, including, but not limited to, steps in the disclosed methods. Therefore, if there are various additional steps that can be performed, it should be understood that each of these additional steps can be performed with any specific implementation or combination of implementations of the disclosed methods.

[0132] Example Implementation

[0133] Item 1. An illumination system for laser speckle imaging, the illumination system comprising: a light source configured to output light having a wavelength in a range of 600 nm to 2000 nm; two or more lengths of optical fiber; a fiber-coupled acousto-optic modulator (FCAOM), wherein the FCAOM is coupled to the light source through a first length of the two or more lengths of optical fiber; and collimating optics that focus light output by a wavelength-stabilized laser to illuminate an object within a field of view (FOV), wherein the collimating optics is coupled to the FCAOM through a second length of the two or more lengths of optical fiber.

[0134] Clause 2. The lighting system of clause 1, wherein the light source is a laser or a laser diode.

[0135] Clause 3. The illumination system of clause 2, wherein the wavelength-stabilized laser is a volume holographic grating (VHG)-stabilized laser diode.

[0136] Clause 4. The illumination system of any one of clauses 1 to 3, wherein the collimating optics has an adjustable focal length.

[0137] Clause 5. The illumination system of any one of clauses 1 to 4, wherein the first length of optical fiber comprises a first portion coupled to the light source and a second portion coupled to the FCAOM.

[0138] Clause 6. The lighting system of clause 5, wherein the first portion and the second portion are coupled by a docking sleeve.

[0139] Clause 7. The lighting system of any one of clauses 1 to 6, wherein the image capture device is configured to capture an image of the object within the FOV when the FOV is illuminated by the light source.

[0140] Clause 8. The lighting system of clause 7, wherein the image capture device comprises at least one magnifying lens that magnifies the FOV.

[0141] Clause 9. The lighting system of clause 7, wherein the image capture device comprises a monochrome camera.

[0142] Clause 10. The illumination system of clause 9, wherein the image capture device comprises a long pass filter located between the FOV and the monochrome camera.

[0143] Clause 11. The lighting system of any one of clauses 1 to 10, wherein the optical fiber is a single-mode optical fiber.

[0144] Clause 12. The illumination system of any one of clauses 1 to 11, wherein the collimating optics has an adjustable focal length.

[0145] Clause 13. The lighting system of any of clauses 1 to 12, further comprising a radio frequency (RF) driver configured to modulate an output of the FCAOM.

[0146] Clause 14. The illumination system of clause 13, further comprising a controller configured to control the RF driver, wherein the controller synchronizes an output of the FCAOM with operation of an image capture system to capture an image of the object within the FOV.

[0147] Item 15. A laser speckle imaging system comprising: a light source having an operating wavelength in the range of 600 nm to 2000 nm; an optical fiber; a fiber-coupled acousto-optic modulator (FCAOM), wherein the FCAOM is coupled to the light source via a first length of optical fiber; collimating optics that focus light output by the light source to illuminate a field of view (FOV), wherein the collimating optics is coupled to the FCAOM via a second length of optical fiber; and an image capture device for capturing an image of the FOV when the FOV is illuminated by the light source.

[0148] Clause 16. The laser speckle imaging system according to Clause 15, wherein the light source is a laser or a laser diode.

[0149] Clause 17. The laser speckle imaging system of clause 16, wherein the wavelength-stabilized laser is a volume holographic grating (VHG)-stabilized laser diode.

[0150] Clause 18. The laser speckle imaging system according to any one of clauses 15 to 17, wherein the collimating optics has an adjustable focal length.

[0151] Clause 19. The laser speckle imaging system according to any one of clauses 15 to 18, wherein the first section of optical fiber comprises a first portion coupled to the light source and a second portion coupled to the FCAOM.

[0152] Clause 20. The laser speckle imaging system of Clause 19, wherein the first portion and the second portion are coupled via a docking sleeve.

[0153] Clause 21. The laser speckle imaging system according to any one of clauses 15 to 20, wherein the image capture device comprises at least one magnifying lens for magnifying the FOV.

[0154] Clause 22. The laser speckle imaging system according to any one of clauses 15 to 21, wherein the image capture device comprises a monochrome camera.

[0155] Clause 23. The laser speckle imaging system of clause 22, wherein the image capture device comprises a long pass filter located between the FOV and the monochrome camera.

[0156] Clause 24. The laser speckle imaging system according to any one of clauses 15 to 23, wherein the optical fiber is a single-mode optical fiber.

[0157] Clause 25. The laser speckle imaging system of any one of clauses 15 to 24, further comprising a radio frequency (RF) driver configured to modulate an output of the FCAOM.

[0158] Clause 26. The laser speckle imaging system of Clause 25, further comprising a controller configured to control the RF driver and the image capture device, wherein the controller synchronizes capture of an image by the image capture device with an output of the FCAOM.

[0159] Item 27. A laser speckle imaging system according to Item 26, wherein the controller is further configured to: control the FCAOM to illuminate the FOV at multiple different modulation frequencies within a single exposure time of the image capture device; capture at least one image of the FOV at each of the multiple different modulation frequencies; calculate speckle contrast for each captured image to create one or more speckle contrast image sets; and extract an inverse correlation time value at each pixel using the one or more speckle contrast image sets.

[0160] Item 28. A laser speckle imaging system according to Item 26, wherein the controller is further configured to: control the FCAOM to generate a first group of light pulses within a first exposure time of the image capture device, with a first time delay between the first group of light pulses; control the FCAOM to generate a second group of light pulses within a second exposure time of the image capture device, with a second time delay between the second group of light pulses, wherein the second time delay is different from the first time delay; capture a series of images of the FOV within each of the first exposure time and the second exposure time; calculate the speckle contrast for each image in the series of images to create a corresponding speckle contrast image set; and use the speckle contrast image set to extract the inverse correlation time value at each pixel.

[0161] Clause 29. A method of speckle imaging, comprising performing the following operations within a single exposure time of a laser speckle imaging system: operating a light source and an acousto-optic modulator (AOM) of the laser speckle imaging system to illuminate a field of view (FOV) at a plurality of different modulation frequencies; capturing at least one image of the FOV at each of the plurality of different modulation frequencies; calculating speckle contrast for each captured image to create one or more speckle contrast image sets; and extracting an inverse correlation time value at each pixel using the one or more speckle contrast image sets.

[0162] Clause 30. The method of clause 29, wherein operating the light and the AOM to illuminate the FOV at the plurality of different modulation frequencies comprises controlling the AOM to adjust the modulation frequency of the light directed toward the FOV according to the plurality of different modulation frequencies.

[0163] Clause 31. The method of clause 29, wherein operating the light source and the AOM to illuminate the FOV at the plurality of different modulation frequencies comprises controlling the light source to adjust the modulation frequency of light directed toward the FOV according to the plurality of different modulation frequencies.

[0164] Clause 32. The method of any one of clauses 29 to 31, wherein the AOM is a fiber-coupled AOM.

[0165] Clause 33. The method of any one of clauses 29 to 32, further comprising determining blood flow based on the inverse correlation time value at each pixel.

[0166] Clause 34. The method of any one of clauses 29 to 33, wherein the light source of the laser speckle imaging system is a laser or a laser diode.

[0167] Clause 35. The method of clause 34, wherein the light source has an operating wavelength in the range of 600 nm to 2000 nm.

[0168] Clause 36. The method of clause 34, wherein the wavelength-stabilized laser is a fiber-coupled volume holographic grating (VHG) stabilized laser diode.

[0169] Clause 37. The method of any one of clauses 29 to 36, wherein the light source is coupled to the AOM via a length of optical fiber.

[0170] Clause 38. A method according to any one of clauses 29 to 37, wherein the AOM is coupled to an adjustable focus collimating optical device via a length of optical fiber, wherein the adjustable focus collimating optical device focuses light output by the light source to illuminate the FOV.

[0171] Clause 39. The method of any one of clauses 29 to 38, wherein the laser speckle imaging system comprises an image capture device for capturing the at least one image of the FOV, wherein the image capture device comprises a monochrome camera and at least one magnifying lens.

[0172] Clause 40. The method of clause 39, wherein the image capture device further comprises a long pass filter positioned between the FOV and the monochrome camera.

[0173] Clause 41. The method of any one of clauses 29 to 40, wherein operating the AOM comprises sending commands to a radio frequency (RF) driver of the laser speckle imaging system, wherein the RF driver is coupled to the AOM.

[0174] Item 42. A method of speckle imaging, comprising: operating a light source and an acousto-optic modulator (AOM) of a laser speckle imaging system to generate a first set of pulses within a first exposure time of the laser speckle imaging system, the first set of pulses having a first time delay therebetween, wherein light output by the light source illuminates a field of view (FOV); operating the light source and the AOM to generate a second set of pulses within a second exposure time of the laser speckle imaging system, the second set of pulses having a second time delay therebetween, wherein the second time delay is different from the first time delay; capturing a series of images of the FOV within each of the first exposure time and the second exposure time; calculating speckle contrast for each image in the series of images to create a corresponding speckle contrast image set; and extracting an inverse correlation time value at each pixel using the speckle contrast image set.

[0175] Clause 43. The method of clause 42, further comprising determining blood flow based on the inverse correlation time value at each pixel.

[0176] Clause 44. The method of clause 42 or 43, wherein the light source of the laser speckle imaging system is a laser or a laser diode.

[0177] Clause 45. The method of clause 44, wherein the light source has an operating wavelength in the range of 600 nm to 2000 nm.

[0178] Clause 46. The method of clause 44, wherein the wavelength-stabilized laser is a fiber-coupled volume holographic grating (VHG) stabilized laser diode.

[0179] Clause 47. The method of any one of clauses 42 to 46, wherein the light source is coupled to the AOM via a length of optical fiber.

[0180] Clause 48. A method according to any one of clauses 42 to 47, wherein the AOM is coupled to an adjustable focus collimating optic via a length of optical fiber, wherein the adjustable focus collimating optic focuses light output by the light source to illuminate the FOV.

[0181] Clause 49. A method according to any one of clauses 42 to 48, wherein the laser speckle imaging system includes an image capture device for capturing the series of images of the FOV, wherein the image capture device includes a monochrome camera and at least one magnifying lens.

[0182] Clause 50. The method of clause 49, wherein the image capture device further comprises a long pass filter positioned between the FOV and the monochrome camera.

[0183] Clause 51. The method of any one of clauses 42 to 50, wherein controlling the AOM comprises sending commands to a radio frequency (RF) driver of the laser speckle imaging system, wherein the RF driver is coupled to the AOM.

[0184] Clause 52. The method of any one of clauses 42 to 51, wherein the AOM is a fiber-coupled AOM.

Claims

1. An illumination system for laser speckle imaging, the illumination system comprising: a light source configured to output light having a wavelength in a range of 600 nm to 2000 nm; two or more lengths of optical fiber; a fiber-coupled acousto-optic modulator (FCAOM), wherein the FCAOM is coupled to the light source via a first optical fiber of the two or more optical fibers; and A collimating optic focuses light output by the wavelength-stabilized laser to illuminate an object within a field of view (FOV), wherein the collimating optic is coupled to the FCAOM via a second length of the two or more lengths of optical fiber.

2. The lighting system according to claim 1, wherein The light source is a laser or a laser diode.

3. The lighting system according to claim 2, wherein: The wavelength-stabilized laser is a volume holographic grating (VHG) stabilized laser diode.

4. The lighting system according to any one of claims 1 to 3, wherein: The collimating optics have an adjustable focal length.

5. The lighting system according to any one of claims 1 to 4, wherein: The first section of optical fiber includes a first portion coupled to the light source and a second portion coupled to the FCAOM.

6. The lighting system according to claim 5, wherein The first part and the second part are coupled by a docking sleeve.

7. The lighting system according to any one of claims 1 to 6, wherein: An image capture device is configured to capture an image of the object within the FOV when the FOV is illuminated by the light source.

8. The lighting system according to claim 7, wherein: The image capture device includes at least one magnifying lens that magnifies the FOV.

9. The lighting system according to claim 7, wherein: The image capture device includes a monochrome camera.

10. The lighting system according to claim 9, wherein: The image capture device includes a long pass filter located between the FOV and the monochrome camera.

11. The lighting system according to any one of claims 1 to 10, wherein: The optical fiber is a single-mode optical fiber.

12. The lighting system according to any one of claims 1 to 11, wherein: The collimating optics have an adjustable focal length.

13. The lighting system of any one of claims 1 to 12, further comprising a radio frequency (RF) driver configured to modulate the output of the FCAOM.

14. The lighting system of claim 13, further comprising a controller configured to control the RF driver, wherein: The controller synchronizes the output of the FCAOM with the operation of an image capture system to capture images of the object within the FOV.

15. A laser speckle imaging system, comprising: a light source having an operating wavelength in the range of 600 nm to 2000 nm; optical fiber; a fiber-coupled acousto-optic modulator (FCAOM), wherein the FCAOM is coupled to the light source via a first section of optical fiber; collimating optics that focus light output by the light source to illuminate a field of view (FOV), wherein the collimating optics are coupled to the FCAOM via a second length of optical fiber; and An image capture device is configured to capture an image of the FOV when the FOV is illuminated by the light source.

16. The laser speckle imaging system according to claim 15, wherein: The light source is a laser or a laser diode.

17. The laser speckle imaging system according to claim 16, wherein: The wavelength-stabilized laser is a volume holographic grating (VHG) stabilized laser diode.

18. The laser speckle imaging system according to any one of claims 15 to 17, wherein: The collimating optics have an adjustable focal length.

19. The laser speckle imaging system according to any one of claims 15 to 18, wherein: The first section of optical fiber includes a first portion coupled to the light source and a second portion coupled to the FCAOM.

20. The laser speckle imaging system according to claim 19, wherein: The first part and the second part are coupled by a docking sleeve.

21. The laser speckle imaging system according to any one of claims 15 to 20, wherein: The image capture device includes at least one magnifying lens that magnifies the FOV.

22. The laser speckle imaging system according to any one of claims 15 to 21, wherein: The image capture device includes a monochrome camera.

23. The laser speckle imaging system according to claim 22, wherein: The image capture device includes a long pass filter located between the FOV and the monochrome camera.

24. The laser speckle imaging system according to any one of claims 15 to 23, wherein: The optical fiber is a single-mode optical fiber.

25. The laser speckle imaging system according to any one of claims 15 to 24, further comprising a radio frequency (RF) driver configured to modulate the output of the FCAOM.

26. The laser speckle imaging system according to claim 25, further comprising a controller configured to control the RF driver and the image capture device, wherein: The controller synchronizes the capture of images by the image capture device with the output of the FCAOM.

27. The laser speckle imaging system according to claim 26, wherein: The controller is further configured to: During a single exposure time of the image capture device: controlling the FCAOM to illuminate the FOV at a plurality of different modulation frequencies; capturing at least one image of the FOV at each of the plurality of different modulation frequencies; calculating speckle contrast for each captured image to create one or more speckle contrast image sets; as well as An inverse correlation time value at each pixel is extracted using the one or more sets of speckle contrast images.

28. The laser speckle imaging system according to claim 26, wherein: The controller is further configured to: controlling the FCAOM to generate a first set of light pulses within a first exposure time of the image capture device, wherein the first set of light pulses have a first time delay between them; controlling the FCAOM to generate a second set of light pulses within a second exposure time of the image capture device, wherein the second set of light pulses have a second time delay therebetween, wherein the second time delay is different from the first time delay; capturing a series of images of the FOV during each of the first exposure time and the second exposure time; calculating speckle contrast for each image in the series of images to create a corresponding set of speckle contrast images; and The inverse correlation time value at each pixel is extracted using the speckle contrast image set.

29. A method for speckle imaging, comprising performing the following operations within a single exposure time of a laser speckle imaging system: operating the laser speckle imaging system to illuminate a field of view (FOV) at a plurality of different modulation frequencies; capturing at least one image of the FOV at each of the plurality of different modulation frequencies; calculating speckle contrast for each captured image to create one or more speckle contrast image sets; as well as An inverse correlation time value at each pixel is extracted using the one or more sets of speckle contrast images.

30. The method according to claim 29, wherein The laser speckle imaging system includes a light source and an acousto-optic modulator (AOM), wherein operating the laser speckle imaging system to illuminate the FOV at the plurality of different modulation frequencies includes controlling at least one of the light source or the AOM.

31. The method according to claim 30, wherein Operating the light and the AOM to illuminate the FOV at the plurality of different modulation frequencies includes controlling the AOM to adjust the modulation frequency of the light directed toward the FOV according to the plurality of different modulation frequencies.

32. The method according to claim 30, wherein Operating the light source and the AOM to illuminate the FOV at the plurality of different modulation frequencies includes controlling the light source to adjust the modulation frequency of light directed toward the FOV according to the plurality of different modulation frequencies.

33. The method according to any one of claims 30 to 32, wherein The AOM is a fiber-coupled AOM.

34. The method of any one of claims 30 to 33, further comprising determining blood flow from the inverse correlation time value at each pixel.

35. The method according to any one of claims 30 to 34, wherein The light source of the laser speckle imaging system is a laser or a laser diode.

36. The method according to claim 35, wherein The light source has an operating wavelength in the range of 600 nm to 2000 nm.

37. The method according to claim 35, wherein The wavelength-stabilized laser is a fiber-coupled volume holographic grating (VHG) stabilized laser diode.

38. The method according to any one of claims 30 to 37, wherein The light source is coupled to the AOM via a length of optical fiber.

39. The method according to any one of claims 30 to 38, wherein The AOM is coupled to an adjustable focus collimating optic via a length of optical fiber, wherein the adjustable focus collimating optic focuses light output by the light source to illuminate the FOV.

40. The method according to any one of claims 29 to 38, wherein The laser speckle imaging system comprises an image capture device for capturing the at least one image of the FOV, wherein the image capture device comprises a monochrome camera and at least one magnifying lens.

41. The method of claim 39, wherein The image capture device also includes a long pass filter located between the FOV and the monochrome camera.

42. The method according to any one of claims 30 to 41, wherein Operating the AOM includes sending commands to a radio frequency (RF) driver of the laser speckle imaging system, wherein the RF driver is coupled to the AOM.

43. A method for speckle imaging, comprising: operating the laser speckle imaging system to generate a first set of pulses within a first exposure time of the laser speckle imaging system, the first set of pulses having a first time delay therebetween, wherein light output by the light source illuminates a field of view (FOV); operating the laser speckle imaging system within a second exposure time of the laser speckle imaging system to generate a second set of pulses, wherein the second set of pulses have a second time delay therebetween, wherein the second time delay is different from the first time delay; capturing a series of images of the FOV during each of the first exposure time and the second exposure time; calculating speckle contrast for each image in the series of images to create a corresponding set of speckle contrast images; and The inverse correlation time value at each pixel is extracted using the speckle contrast image set.

44. The method of claim 42, further comprising determining blood flow based on the inverse-correlated time value at each pixel.

45. The method according to claim 43 or 44, wherein The laser speckle imaging system includes a light source and an acousto-optic modulator (AOM).

46. The method of claim 45, wherein The light source of the laser speckle imaging system is a laser or a laser diode.

47. The method of claim 46, wherein The light source has an operating wavelength in the range of 600 nm to 2000 nm.

48. The method of claim 46, wherein The wavelength-stabilized laser is a fiber-coupled volume holographic grating (VHG) stabilized laser diode.

49. The method according to any one of claims 45 to 48, wherein The light source is coupled to the AOM via a length of optical fiber.

50. The method according to any one of claims 45 to 49, wherein The AOM is coupled to an adjustable focus collimating optic via a length of optical fiber, wherein the adjustable focus collimating optic focuses light output by the light source to illuminate the FOV.

51. The method according to any one of claims 45 to 50, wherein The laser speckle imaging system comprises an image capture device for capturing the series of images of the FOV, wherein the image capture device comprises a monochrome camera and at least one magnifying lens.

52. The method of claim 51, wherein The image capture device also includes a long pass filter located between the FOV and the monochrome camera.

53. The method according to any one of claims 45 to 52, wherein Controlling the AOM includes sending commands to a radio frequency (RF) driver of the laser speckle imaging system, wherein the RF driver is coupled to the AOM.

54. The method according to any one of claims 45 to 53, wherein The AOM is a fiber-coupled AOM.

Images