Continuous blood flow visualization using laser speckle contrast imaging

Abstract

A system and method for visualizing blood flow is disclosed. The method generally includes obtaining a laser speckle contrast imaging (LSCI) image of blood flow; obtaining a white light image of tissue, the white light image capturing an anatomical structure of the subject in a region associated with the LSCI image of the blood flow; registering the LSCI image and the white light image to each other in space; overlapping the LSCI image and the white light image which are registered in the space; and generating display data that includes the spatially registered LSCI image and white light image and that continuously depicts the blood flow that overlaps the tissue.

Description

[0001] Statement Regarding Federally Sponsored Research

[0002] This invention was made with government support under Grant No. R01 EB011556 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 the benefit of and priority to U.S. Provisional Patent Application No. 63 / 335,854, filed on April 28, 2022, which is incorporated herein by reference in its entirety. Background Art

[0005] Cerebral blood flow (CBF) monitoring is a routine procedure used to inform decision-making during cerebrovascular surgery. In cases of cerebral aneurysm clipping, various techniques are commonly used to confirm vascular patency and determine whether aneurysm occlusion was successful. Current intraoperative tools for CBF monitoring and visualization include indocyanine green angiography (ICGA), Doppler and time-lapse ultrasound, and percutaneous transfemoral digital subtraction angiography (DSA). ICGA documents the fluorescent washout of an indocyanine green bolus following intravenous injection. DSA images are acquired by obtaining multiple timed X-rays during intra-arterial injection of contrast agent. Summary of the Invention

[0006] One embodiment of the present disclosure is a method for visualizing blood flow, the method comprising: obtaining a laser speckle contrast imaging (LSCI) image of blood flow; obtaining a white light image of tissue, the white light image capturing anatomical structure of a subject in a region associated with the LSCI image of blood flow; spatially registering the LSCI image and the white light image with each other; superimposing the spatially registered LSCI image and white light image; and generating display data continuously depicting the blood flow of the superimposed tissue, wherein the display data includes the spatially registered LSCI image and white light image.

[0007] In some embodiments, the display data continuously depicts the blood flow superimposed on the tissue in real time during surgery.

[0008] In some embodiments, the method further includes displaying the display data on a user interface.

[0009] In some embodiments, the tissue comprises vasculature.

[0010] In some embodiments, the tissue is brain tissue.

[0011] In some embodiments, spatially registering the LSCI image and the white-light image with each other includes creating a lookup table based on a spatial transformation for registering the LSCI image and the white-light image.

[0012] In some embodiments, superimposing the spatially registered LSCI image and white-light image includes using the lookup table to map corresponding pixels from the LSCI image to corresponding pixels from the white-light image.

[0013] In some embodiments, superimposing the spatially registered LSCI image and white light image further comprises contrast stretching the LSCI image, mapping the LSCI image to an n-bit color map, and performing a weighted sum with the white light image.

[0014] Another embodiment of the present disclosure is a system for visualizing blood flow, the system comprising: a first light source configured to illuminate blood flow at a target area of ​​a subject; a first camera configured to record a raw laser speckle image of the blood flow; and a computing device comprising a processor and a memory having instructions stored thereon, the instructions, when executed by the processor, causing the computing device to: obtain the raw laser speckle image of the blood flow via the first camera; derive a laser speckle contrast imaging (LSCI) image from the raw laser speckle image; obtain a white light image of tissue at the target area of ​​the subject, the white light image capturing anatomical structure; spatially register the LSCI image and the white light image with each other; superimpose the spatially registered LSCI image and white light image; and generate display data continuously depicting the blood flow of the superimposed tissue, wherein the display data comprises the spatially registered LSCI image and white light image.

[0015] In some embodiments, the system is a surgical microscope, an endoscope, an exoscope, a robotic surgical platform, a stand-alone imaging system, or a system dedicated to blood flow imaging.

[0016] In some embodiments, the display data continuously depicts the blood flow superimposed on the tissue in real time during surgery.

[0017] In some implementations, the instructions further cause the computing device to present the display data on a user interface.

[0018] In some embodiments, the tissue comprises vasculature.

[0019] In some embodiments, the tissue is brain tissue.

[0020] In some embodiments, spatially registering the LSCI image and the white-light image with each other includes creating a lookup table based on a spatial transformation for registering the LSCI image and the white-light image.

[0021] In some embodiments, superimposing the spatially registered LSCI image and white-light image includes using the lookup table to map corresponding pixels from the LSCI image to corresponding pixels from the white-light image.

[0022] In some embodiments, superimposing the spatially registered LSCI image and white light image further comprises contrast stretching the LSCI image, mapping the LSCI image to an n-bit color map, and performing a weighted sum with the white light image.

[0023] Yet another embodiment of the present disclosure is a method for visualizing blood flow, the method continuously comprising: capturing a laser speckle contrast imaging (LSCI) image of blood flow in a subject using a first image capture device; capturing a white light image of tissue using a second image capture device, the white light image capturing anatomical structure; co-registering the LSCI image and the white light image; superimposing the co-registered LSCI image and white light image; and displaying the superimposed and co-registered LSCI image and white light image via a user interface.

[0024] In some embodiments, the tissue comprises vasculature or brain tissue.

[0025] In some embodiments, co-registering the LSCI image and the white-light image with each other includes creating a lookup table based on a spatial transformation used to register the LSCI image and the white-light image. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is a block diagram of a blood flow visualization system according to some embodiments.

[0027] Figure 2A and Figure 2B According to some embodiments Figure 1 Diagram of various configurations of the visualization system.

[0028] Figure 3 According to some embodiments Figure 1 An image of an example configuration of the visualization system.

[0029] Figure 4 is a block diagram of a computer system for implementing the processes described herein, according to some embodiments.

[0030] Figure 5 is a flow chart of a method for visualizing blood flow according to some embodiments.

[0031] Figure 6 is a flow chart of a method for visualizing blood flow according to some embodiments.

[0032] 7A to 7D is an example image processing pipeline for generating an overlay for laser speckle contrast imaging (LSCI) according to some embodiments. 7A to 7D LCSI, threshold processing, white light and LCSI overlay images are shown in , respectively.

[0033] Figure 8 Included are a number of example images captured from a patient before aneurysm clipping (eg, pre-clip), immediately after aneurysm clipping (eg, post-clip), and during indocyanine green angiography (ICGA), in accordance with some embodiments.

[0034] Figure 9A and Figure 9B is an example graph of relative cerebral blood flow (CBF) during a clipping procedure, according to some embodiments.

[0035] Figure 10 Included are a number of example images captured from a patient during ICGA according to some embodiments.

[0036] Figure 11A and Figure 11B Comparative LSCI stacking according to some embodiments ( Figure 11A ) and ICGA superposition ( Figure 11B )

[0037] Figure 12A Included are several example images of arteriovenous malformation (AVM) resection in accordance with some embodiments.

[0038] Figure 12B is an example graph of average speckle contrast values ​​before and after AVM resection, according to some embodiments.

[0039] Figure 13A Included are several example images demonstrating changes in fluorescence intensity during a bolus administration of indocyanine green (ICG) and LSCI measurements of relative blood flow to the same target area, according to some embodiments.

[0040] Figure 13B is an example graph of fluorescence intensity changes during bolus administration of ICG and LSCI measures of relative blood flow for the same target area, according to some embodiments.

[0041] Various objects, aspects, and features of the present disclosure will become more apparent and better understood by reference 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. DETAILED DESCRIPTION

[0042] Cerebral blood flow (CBF) monitoring plays an important role in numerous neurosurgical and neuroscience applications, such as during cerebrovascular surgery. As mentioned above, current technologies are often insufficient to monitor CBF activity in real time or near real time, as many techniques only produce periodic measurements or may require significant additional effort by the physician to implement. Therefore, continuous monitoring of CBF may often be more desirable than periodic measurements. As mentioned above, ICGA is an effective decision aid; however, it does not provide continuous imaging because it requires injection of contrast agent. Doppler ultrasound provides absolute flow velocity but is limited to measurements at a single location and requires contact with the target vessel. DSA has been used to confirm aneurysm occlusion and patency of the underlying parent vasculature; however, it is invasive and time-consuming relative to ICGA or Doppler ultrasound, for example, typically requiring removal of the surgical microscope, fluoroscopy, and transfemoral selective arterial catheterization.

[0043] Laser speckle contrast imaging (LSCI) has emerged as a promising tool for non-invasively monitoring CBF because it produces real-time, full-field blood flow maps without the need for any contrast agents. Therefore, LSCI may provide a potential solution for continuous CBF monitoring. Several studies have demonstrated LSCI during human neurosurgery and shown its promise as a CBF monitoring tool, including surgical revascularization, awake functional mapping, brain tumor resection, cortical spreading depression, and infarction during ischemic stroke. However, many previous clinical implementations required the introduction of external devices into the surgical field, thereby interrupting the surgical procedure. Other implementations incorporate the instrument into the neurosurgical operating microscope, eliminating the need for external devices and surgical interruptions; however, the surgical procedure would still need to be paused while the LSCI images are acquired, and it would not be possible to record CBF images for extended periods of time or simultaneously with ICGA.

[0044] Described herein are LSCI systems and related methods that address these and other limitations of existing blood flow monitoring devices. In some embodiments, the LSCI systems described herein can be integrated into surgical microscopes or other medical devices to facilitate real-time continuous visualization of CBF (e.g., including simultaneous ICGA and LSCI imaging) superimposed on the surgical field of view during surgery. To demonstrate effectiveness, the disclosed LSCI systems and methods were evaluated during cerebral aneurysm clipping and arteriovenous malformation (AVM) resection surgeries. The present disclosure demonstrates the potential of LSCI for human CBF monitoring in at least two ways: performing LSCI continuously during cerebral aneurysm clipping and AVM resection surgeries without impacting the surgical flow, including real-time visualization of CBF during aneurysm clip placement; and performing LSCI and ICGA simultaneously to visualize CBF in five example neurovascular cases. In summary, these results demonstrate that when the LSCI device is integrated into a surgical microscope, LSCI can continuously monitor CBF during neurovascular surgery, and that LSCI and ICGA provide different but complementary information about vascular perfusion.

[0045] LSCI system

[0046] Now refer to Figure 1 , a block diagram of a blood flow visualization system 100 according to some embodiments is shown. The system 100 is shown as including a first light source 102 and a corresponding first optical device 104, and a second light source 106 and a corresponding second optical device 108. In some embodiments, the first light source 102 and the second light source 106 are configured to illuminate a target 120 (e.g., a target area of ​​a patient). At least a portion of the light emitted by the first light source 102 and the second light source 106 is then reflected off the target 120 and reflected toward a first camera 110 and a second camera 112. Each of the first camera 110 and the second camera 112 can then capture a respective image of the target 120 based on the reflected light and can transmit the image to a remote computing device 114.

[0047] As described herein, the first light source 102 is generally any suitable light source that can produce and emit coherent light. As described herein, coherent light is generally light in which electromagnetic waves maintain a fixed and predictable phase relationship with each other over a sufficiently long period of time so that interference effects can be recorded with a sensor. Such light can include a single wavelength or a narrow bandwidth. As will be understood by those of ordinary skill in the art, coherent light does not actually require a single wavelength and industrial standards allow relative deviations, such as bandwidths within ±1 nm of the target wavelength. It can also have a wide bandwidth, such as if a pulsed laser is used as a coherent light source. In some embodiments, the wavelength of the first light source 102 is 785 nm (± 5 nm), with a maximum output power of 300 mW. In some embodiments, the first light source 102 is a laser.

[0048] The second light source 106 is typically a white light source, or alternatively, is typically configured to output light of a different wavelength than the first light source 102. In some embodiments, the second light source 106 can be configured to emit light within a wavelength range of 350 nm to 850 nm. In this regard, the light emitted by the second light source 106 can be a collection of multiple wavelengths or a single wavelength between 350 nm and 850 nm. Figure 1 As shown, light emitted by the second light source 106 is generally directed by the second optics 108 toward 120 .

[0049] The first optics 104 typically includes one or more optical components for filtering, focusing, and / or otherwise modifying light emitted by the first light source 102 and / or reflected from the first light source 102 off the target 120. In some embodiments, the first optics 104 includes one or more lenses and / or mirrors for focusing and / or directing light from the first light source 102 onto the target 120. In some embodiments, the first optics 104 includes one or more filters for filtering light emitted by the first light source 102 and reflected from the target 120. In some embodiments, the first optics 104 includes one or more filters for reducing or preventing light from the second light source 106 or other background light from entering the first camera 110. In some embodiments, the first optics 104 includes a bandpass filter centered around or around the wavelength of the first light source 102. In some embodiments, the first optics 104 includes a polarizer for reducing specular reflections from the target 120. In some such embodiments, the polarizer can be located on a rotatable mount that enables the polarizer to be rotated.

[0050] Second optics 108 also typically includes one or more optical components for filtering, focusing, and / or otherwise modifying light emitted by second light source 106 and / or reflected from second light source 106 off target 120. In some embodiments, second optics 108 includes one or more lenses and / or mirrors for focusing and / or directing light from second light source 106 onto target 120. In some embodiments, second optics 108 includes one or more filters for filtering light emitted by second light source 106 and / or reflected from target 120. In some embodiments, second optics 108 includes one or more filters for reducing or preventing light from first light source 102 or other background light from entering second camera 112. In some embodiments, second optics 108 includes a bandpass filter centered around or around the wavelength of second light source 106. In some embodiments, second optics 108 includes a polarizer for reducing specular reflections from target 120. In some such embodiments, the polarizer can be located on a rotatable mount that enables the polarizer to rotate.

[0051] Although Figure 1 Although not shown, it should be understood that the first optics 104 and / or the second optics 108 may include one or more components positioned between the respective first and second light sources 102, 106 and the target 120, and / or may include one or more components positioned between the target 120 and the respective first and second cameras 110, 112. In some embodiments, the first and / or second light sources 102, 106 are fixedly coupled to each other so as to move in tandem with the other light source, for example, in response to user manipulation. For example, a user may move a surgical microscope and, in doing so, cause the first and / or second light sources 102, 106 to move simultaneously with each other while keeping both the first and second cameras 110, 112 focused on the target 120. In some embodiments, the first and second cameras 110, 112 are focused simultaneously. In some embodiments, when the first camera 110 is added to the microscope, the optics of the first camera 110 co-align it with the second camera 112, so that the two cameras are focused together.

[0052] The first camera 110 and the second camera 112 are generally any suitable image capture devices. In some embodiments, the first camera 110 is specifically configured to capture images of the target 120 within the wavelength range emitted by the first light source 102. Similarly, in some embodiments, the second camera 112 can be specifically configured to capture images of the target 120 within the wavelength range emitted by the second light source 106. In some embodiments, the second camera 112 is an imaging device coupled to, embedded in, or otherwise integrated with a medical imaging device. For example, the second camera 112 can be associated with a surgical microscope, an endoscope, an exoscope, a robotic surgical platform, and the like.

[0053] In some embodiments, the first camera 110 is configured to capture raw LSCI. In some embodiments, the first camera 110 is or includes a 10-bit or higher resolution charge coupled device (CCD) camera having an exposure time in the range of about 1 ms to about 20 ms. In other embodiments, the first camera 110 can be or include a near infrared (NIR) enhanced complementary metal oxide semiconductor (CMOS) camera. In some embodiments, the first camera 110 and / or the second camera 112 can operate at a frame rate of approximately 10 to 160 frames per second; however, higher frame rates can be used depending on the application. As described herein, the images captured by both the first camera 110 and the second camera 112 can include still images or can be recorded continuously to create a video.

[0054] In some embodiments, although not shown, system 100 may further include a third camera for capturing ICGA images. In some such embodiments, ICGA images are represented as raw fluorescence intensity images collected by a built-in fluorescence camera. In some embodiments, the third camera may include a NIR camera. Such fluorescence imaging includes, for example, ICGA. In some embodiments, including simultaneous laser speckle contrast imaging and additional imaging, a single camera may be used to record both fluorescence images and raw laser speckle images by interleaving laser speckle and fluorescence image acquisition. Additionally or alternatively, in some embodiments, a single camera may be used to perform laser speckle contrast imaging, fluorescence imaging, and white light imaging as described above.

[0055] In general, the remote computing device 114 is any computing device that is external to or remote from the first camera 110 and / or the second camera 112. The computing device 114 may be coupled to the first camera 110 and / or the second camera 112 via one or more communication links. The present disclosure contemplates that the communication link is any suitable communication link. For example, the communication link may be implemented by any medium that facilitates the exchange of data between network elements, including but not limited to wired, wireless, and optical links. The remote computing device 114 may generally include processing circuitry including a processor and memory, wherein the memory stores instructions for performing the various methods and processes described herein. hereinafter referenced Figure 4 Details of the remote computing device 114 are provided. As shown, the remote computing device 114 is generally configured to receive images (e.g., LSCI and white light images of the target 120) captured by the first camera 110 and the second camera 112 for processing and / or storage. In addition, in some embodiments, the remote computing device 114 can command various other components of the system 100 (e.g., the first light source 102, the second light source 106, the first camera 110, and / or the second camera 112) to capture images. For example, the remote computing device 114 can be configured to activate one or both of the first light source 102 and the second light source 106, and can simultaneously operate the first camera 110 and the second camera 112 to capture images.

[0056] As discussed herein, surgeons often have difficulty understanding the anatomy in LSCI images showing blood flow. However, the system 100 addresses this problem by superimposing an LSCI blood flow image (captured by the first camera 110) on a second image (captured by the second camera 112) showing the anatomy. To superimpose the LSCI image, the LSCI image captured by the first camera 110 can be "thresholded," or subjected to threshold processing, to show only flow between set values ​​(e.g., a "minimum" and a "maximum"). Specifically, the remote computing device 114 can apply a thresholding technique to the image captured by the first camera 110. The remote computing device 114 then spatially registers the thresholded LSCI image with a second image (e.g., a white light image) captured by the second camera 112, and then superimposes the thresholded and registered LSCI image on the second image.

[0057] As described above, the second camera 112 may be an image capture device coupled to or embedded in a medical imaging device. Thus, in various embodiments, the remote computing device 114 can be configured to: superimpose the LSCI image captured by the first camera 110 on an image from a surgical microscope having white light illumination or any wavelength of white light from 350 nm to 850 nm, as captured by the second camera 112; superimpose the LSCI image captured by the first camera 110 on an image from an endoscope having white light illumination or any wavelength of white light from 350 nm to 850 nm, as captured by the second camera 112; superimpose the LSCI image captured by the first camera 110 on an image from an exoscope having white light illumination or any wavelength of white light from 350 nm to 850 nm, as captured by the second camera 112; or superimpose the LSCI image captured by the first camera 110 on an image from a robotic surgical platform having white light illumination or any wavelength of white light from 350 nm to 850 nm, as captured by the second camera 112.

[0058] Example Configuration

[0059] Now refer to Figure 2A 、 Figure 2B and Figure 3 , which shows a schematic diagram of various configurations of the system 100 according to some embodiments. Specifically, Figure 2A and Figure 2B An example configuration of system 100 attached to a microscope is shown. Figure 3 An example embodiment of the system 100 as described herein is shown. It will be understood that during testing, it was found that the system 100 did not interfere with the sterile drape or normal operation of the microscope. In this example, a λ=785 nm laser diode 212—e.g., the first light source 102—with a maximum output power of 300 mW is attached to an additional laser adapter 210 (e.g., an MM6 micromanipulator, Carl Zeiss Meditec Inc., Oberkochen, Germany). As in this example, the nm laser diode 212 can be attached externally or integrated inside the microscope. The laser adapter 210 is mounted to the bottom of the microscope so that a steering mirror (not shown) directs the light downward toward the surgeon's field of view. At a working distance of 35 cm, the beam size is approximately 2 cm. The maximum irradiance is 0.10 W / cm 2 , which is much lower than the American National Standards Institute (ANSI) skin wavelength of 0.3W / cm at 785nm. 2 limit. 32

[0060] The backscattered laser light is directed via a camera adapter 208 to an NIR-enhanced CMOS camera 202 (e.g., Basler AG, Ahrensburg, Germany) mounted on the side observer port on the same side as the craniotomy. This enables the observer to participate during the study. During acquisition, the pixel area is slightly cropped to capture only the pixels above the brain tissue. A filter wheel 206 (e.g., CFW6, Thorlabs Inc.) and a polarizer 204 (e.g., LPNIR100, Thorlabs Inc.) are positioned between the camera adapter 208 and the camera 202. The filter wheel 206 holds various neutral density filters for controlling the power output of the nm laser diode 212. The polarizer 204 is integrated into a motorized rotary mount (e.g., RSC-100, Pacific Laser Equipment Inc., Santa Ana, California, USA) to reduce specular reflections. A bandpass filter (FF01-788 / 3-25, Semrock Inc., Rochester, NY, USA) was added in front of the NIR-enhanced CMOS camera 202 (not shown) to enable simultaneous LSCI acquisition during indocyanine green illumination and to block non-laser light and avoid interference from normal white light illumination during the entire procedure.

[0061] It should be understood that Figure 2A and Figure 2B In the example shown, the laser diode 212 can be the same as or equivalent to the first light source 102; the polarizer 204 and the filter wheel 206 can together form the first optical device 104; and the camera 202 can be the same as or equivalent to the first camera 110. In some embodiments, one or more of the camera 202, the polarizer 204, and the filter wheel 206 can be coupled to the microscope via a C-mount adapter or cage rods. In some embodiments, the second light source 106, the second optical device 108, and the second camera 112 are integrated into the surgical operating microscope and are therefore not shown. Figure 2A and Figure 2B Also not shown, the camera 202 and the second camera 112 may be connected to an external computer.

[0062] computing device

[0063] Now refer to Figure 4 , shows a computing device 400 for implementing the image analysis techniques described herein, according to some embodiments. In some embodiments, the remote computing device 114 is the same as or functionally equivalent to the computing device 400. Therefore, it should be understood that Figure 4It can be considered a detailed block diagram of the remote computing device 114. More generally, the computing device 400 is a computing device configured to obtain laser speckle images and / or white light images from the first camera 110 and / or the second camera 112 in order to generate and display a blood flow visualization.

[0064] Computing device 400 is shown as including processing circuitry 402, which includes a processor 404 and memory 410. Processor 404 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, processor 404 is configured to execute program code stored on memory 410 to cause computing device 400 to perform one or more operations described in more detail below. It should be understood that in embodiments where computing device 400 is part of another computing device, the components of computing device 400 can be shared or identical with the host device. For example, if computing device 400 is implemented via a server, computing device 400 can utilize the processing circuitry, processor, and / or memory of the server to perform the functions described herein.

[0065] Memory 410 may include one or more devices (e.g., memory units, storage devices, storage devices, etc.) for storing data and / or computer code to complete and / or facilitate the various processes described in this disclosure. In some embodiments, memory 410 includes tangible (e.g., non-transitory) computer-readable media that stores code or instructions that can be executed by processor 404. Tangible computer-readable media refers to any physical medium that can provide data that enables computing device 400 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. Therefore, memory 410 may include random access memory (RAM), read-only memory (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 410 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 410 may be communicatively connected to processor 404 , such as via processing circuitry 402 , and may include computer code for executing (eg, by processor 404 ) one or more processes described herein.

[0066] Although shown as separate components, it should be understood that the processor 404 and / or memory 410 can be implemented using various types and quantities of processors and memories. For example, the processor 404 can represent a single processing device or multiple processing devices. Similarly, the memory 410 can represent a single memory device or multiple memory devices. In addition, in some embodiments, the computing device 400 can be implemented in a single computing device (e.g., a server, a shell, etc.). In other embodiments, the computing device 400 can be distributed across multiple servers or computers (e.g., which can exist in distributed locations). For example, the computing device 400 can include multiple distributed computing devices (e.g., multiple processors and / or memory devices) that communicate with each other and operate in collaboration. For example, but not by way of limitation, the application is divided in a manner that allows concurrent and / or parallel processing of application instructions. Alternatively, the data processed by the application is divided in a manner that allows two or more computers to process different parts of the data set concurrently and / or in parallel.

[0067] Memory 410 is shown as including an image analyzer 412 that processes image data obtained from one or both of first camera 110 and second camera 112. In some embodiments, image data is received from first camera 110 and / or second camera 112 and stored in database 414 for later evaluation. As described herein, "image data" generally includes one or both of a laser speckle image captured by first camera 110 and a white light image captured by second camera 112. In some embodiments, computing device 400 communicates directly with first camera 110 and, therefore, receives the laser speckle image of a target area (e.g., target 120) of a subject directly from first camera 110. Similarly, computing device 400 can communicate directly with second camera 112 to receive the white light image. In some embodiments, one or both of the laser speckle image captured by first camera 110 and the white light image captured by second camera 112 are received indirectly, for example, via another computing device.

[0068] The image analyzer 412 is generally configured to implement the Figure 6) . Generally speaking, the image analyzer 412 obtains both a laser speckle image and a white light image of a target area of ​​a subject and performs various post-processing techniques. As described above, the laser speckle image generally captures blood flow in the subject, while the white light image generally captures the subject's anatomical structure in the area associated with the laser speckle image of blood flow. After receiving the raw laser speckle image—as a static image, a series of static images, or as a video feed—the image analyzer 412 can derive a laser speckle contrast image, or "LSCI image." In some embodiments, the image analyzer 412 derives the laser speckle contrast image using a sliding pixel window. In some embodiments, the image analyzer 412 applies thresholding to the laser speckle contrast image, as described in detail below. In some embodiments, the image analyzer 412 applies a color map to the laser speckle contrast image.

[0069] In some embodiments, the image analyzer 412 is configured to register the laser speckle contrast image with the white light image, and / or vice versa. In some such embodiments, the laser speckle contrast image and the white light image are spatially registered with each other, for example, using an affine transformation. In some embodiments, the laser speckle contrast image and the white light image are spatially registered using a lookup table that maps pixels of the laser speckle contrast image and the white light image to each other. The co-registered laser speckle contrast image can then be overlaid on the white light image. In some embodiments, the co-registered and overlaid laser speckle contrast and white light images are used to generate display data that continuously depicts blood flow in the overlaid tissue. In some embodiments, the image analyzer 412 generates the display data and then presents the display data via the user interface 422 described below.

[0070] The computing device 400 is also shown as including a communication interface 420 that facilitates communication between the computing device 400 and any external components or devices. For example, the communication interface 420 may provide a means for transmitting data to the first camera 110 and / or the second camera 112 or receiving data from the first camera and / or the second camera. Thus, the communication interface 420 may be or may include a wired or wireless communication interface (e.g., a jack, antenna, transmitter, receiver, transceiver, wired terminal, etc.) for data communication, or a combination of wired and / or wireless communication interfaces. In some embodiments, communication via the communication interface 420 is direct (e.g., local wired or wireless communication) or via a network (e.g., a WAN, the Internet, a cellular network, etc.). For example, the communication interface 420 may include one or more Ethernet ports for communicatively coupling the computing device 400 to a network (e.g., the Internet). In another example, the communication interface 420 may include a Wi-Fi transceiver for communicating via a wireless communication network. In yet another example, the communication interface 420 may include a cellular or mobile phone communication transceiver.

[0071] In some embodiments, the computing device 400 is communicatively coupled to a user interface 422 via a communication interface 420 (e.g., via a wired connection). Generally speaking, the user interface 422 is an electronic device that allows a user to interact with the computing device 400, for example, by presenting data and / or receiving user input. To this end, the user interface 422 typically includes at least a display (e.g., a screen) for displaying data. For example, the user interface 422 may include an LED or LCD screen for displaying data (e.g., graphics, text, video, etc.). Specifically, the user interface 422 may be configured to display at least blood flow visualization data (e.g., video) generated by the image analyzer 412. In some embodiments, the user interface 422 also includes at least one user input device for receiving user input. For example, the user interface 422 may include one or more of a keyboard, a mouse, a numeric keypad, arrow keys, buttons, etc. In some embodiments, the user interface 422 is a computing device separate from the computing device 400 that includes its own processor and / or memory. The user interface 422 may include, for example, a mobile phone, an electronic tablet computer, a laptop computer, or a desktop computer. In some implementations, user interface 422 may be connected wirelessly (eg, via the Internet) rather than directly to computing device 400 .

[0072] Image analysis

[0073] As described above, the remote computing device 114 processes the raw laser speckle image collected by the first light source 102 / camera 202 to calculate the laser speckle pattern according to the equation Calculate the spatial speckle contrast value (K) within a sliding moving window (e.g., a 7x7 pixel window), where σ s is the spatial standard deviation, and is the average intensity within the area. In some embodiments, the image captured by the first camera 110 / camera 202 (e.g., "Image 1") can be spatially transformed into an image captured by the second camera 112 (e.g., "Image 2"). In other embodiments, the image captured by the second camera 112 (e.g., "Image 2") can be spatially transformed into an image captured by the first light source 102 / camera 202 (e.g., "Image 1"). In other embodiments, no spatial transformation is applied. One example of a spatial transformation that can be applied is an affine transformation.

[0074] For relative blood flow measurements, speckle contrast was converted to correlation time (τ) by evaluating the average decay time of the speckle electric field autocorrelation function. c ), we assume that the instrument factor is unity. Speckle correlation time τ c is a more quantitative measure of blood flow; inverse correlation time (ICT = 1 / τ c ) is commonly used as a measure of blood flow in vessels or perfusion in the parenchyma. To display ICT time course data, the first five seconds of data are used as a normalization factor to more easily visualize flow changes relative to baseline values. To overlay LSCI with images from the built-in microscope white light camera, the video output of the surgical microscope system is continuously recorded. LSCI images, white light reflectance images, and ICGA images are spatially co-registered by applying an affine transformation to all corresponding images.

[0075] Now refer to Figure 5 , shows a flow chart of a process 500 for visualizing blood flow according to some embodiments. In some embodiments, the process 500 is implemented by a remote computing device 114 (e.g., computer device 400) as described herein. It should be understood that certain steps of the process 500 may be optional, and in some embodiments, the process 500 may be implemented using fewer than all steps. It should also be understood that Figure 5 The order of the steps shown in is not intended to be limiting.

[0076] At step 502, a laser speckle contrast image (e.g., LSCI image) of blood flow is obtained. In some embodiments, the laser speckle contrast image is derived from the raw laser speckle image captured by the first camera 110. In some such embodiments, the laser speckle contrast image is derived from the raw laser speckle image using a sliding pixel window. As described above, in some embodiments, the spatial speckle contrast value (K) is calculated according to the equation Calculated from the raw laser speckle image within a sliding moving window (e.g., a 7x7 pixel window), where σ s is the spatial standard deviation, and is In some embodiments, as described below with reference to Figure 6 As described above, thresholding is applied to the laser speckle contrast image. In some embodiments, also as described below with reference to Figure 6 As described above, a color map is applied to the laser speckle contrast image.

[0077] At step 504, a white light image of tissue of the subject in an area associated with blood flow is obtained. In some embodiments, the white light image is captured by the second camera 112. As described herein, a "white light" image refers to an image of a target area (e.g., tissue) illuminated with substantially white light. Generally speaking, the white light image captures the subject's anatomical structure in an area associated with the laser speckle contrast image of blood flow. In some embodiments, "tissue" refers to vasculature or brain tissue.

[0078] At step 506, the laser speckle contrast image and the white light image are spatially registered (e.g., co-registered) with each other. In some embodiments, the laser speckle contrast image and the white light image are spatially registered using an affine transformation. In some embodiments, the laser speckle contrast image and the white light image are spatially registered using a lookup table that maps pixels of the laser speckle contrast image and the white light image to each other. In some embodiments, spatially registering the laser speckle contrast image and the white light image includes creating a lookup table based on the spatial transformation used to register the laser speckle contrast image and the white light image.

[0079] At step 508, the spatially registered laser speckle contrast image is overlaid on the white-light image. In some embodiments, overlaying the spatially registered laser speckle contrast image and the white-light image includes using the lookup table created at step 506 to map corresponding pixels from the laser speckle contrast image to corresponding pixels from the white-light image. In some embodiments, overlaying the spatially registered laser speckle contrast image and the white-light image includes contrast stretching the laser speckle contrast image, mapping the laser speckle contrast image to an n-bit color map, and / or performing a weighted sum with the white-light image.

[0080] At step 510, display data is generated that continuously depicts blood flow (e.g., a laser speckle contrast image) superimposed on tissue. Generally, the display data includes a spatially registered and superimposed laser speckle contrast image and a white light image. In some embodiments, the display data includes a static image of blood flow (e.g., from the laser speckle contrast image) superimposed on tissue (e.g., from the white light image). In some embodiments, the display data includes a series of images and / or videos showing blood flow over tissue. Figure 7D An example of display data is shown in .

[0081] At step 512, the display data is presented via a user interface. Specifically, the display data can be presented to a user (e.g., a physician) via the user interface in real time or near real time. In this way, the user can see ("visualize") blood flow through / under the tissue in real time or near real time. Figure 7D An example of display data is shown in .

[0082] Now refer to Figure 6 , shows a flow chart of a process 600 for visualizing blood flow according to some embodiments. In some embodiments, the process 600 is implemented by a remote computing device 114 (e.g., computer device 400) as described herein. It should be understood that certain steps of the process 600 may be optional, and in some embodiments, the process 600 may be implemented using fewer than all steps. It should also be understood that Figure 6 The order of the steps shown in is not intended to be limiting.

[0083] At step 602, the first camera 110 captures a raw laser speckle image of a target area of ​​a subject. In some embodiments, the target area of ​​the subject is illuminated via a first light source 102, which can be a laser as discussed above or another device that produces coherent light. In some embodiments, light from the first light source 102 passes through various filters and / or other optical devices, such as first optical device 104. Generally speaking, the first light source 102 is configured to illuminate the target area to visualize blood flow. In some embodiments, the light reflects off the target, and backscattered light is filtered or reduced using a first filter configured to pass a wavelength or range of wavelengths output by the first light source 102 while blocking wavelengths output by the second light source 106. In some embodiments, the filter is configured to enable simultaneous LSCI acquisition during indocyanine green illumination and to block non-laser light. In some embodiments, the backscattered light is polarized using a polarizing filter. In some embodiments, the first camera 110 captures the raw laser speckle image after filtering and polarization to reduce backscatter.

[0084] At step 604 , the raw laser speckle image is transmitted to the remote computing device 114 or another computing device for post-processing.

[0085] At step 606, the computing device 400 (e.g., the remote computing device 114) derives a laser speckle contrast image, or "LSCI image," from the raw laser speckle image. In some embodiments, the laser speckle contrast image is based on a sliding pixel window. However, in other embodiments, the image may not be acquired or processed based on a sliding pixel window. In some embodiments, the laser speckle contrast image is a spatial laser speckle contrast image. Thus, various embodiments may be based on various neighborhood schemes. For example, in some embodiments, the laser speckle contrast image may be derived based on temporal speckle contrast analysis or spatiotemporal laser speckle analysis. For non-spatial speckle contrast analysis, in some implants, pseudo-color is applied to the LSCI image.

[0086] At step 608, the computing device 400 (e.g., the remote computing device 114) thresholds the LSCI image between a minimum speckle contrast value and a maximum speckle contrast value. In some embodiments, the laser speckle contrast image has laser speckle contrast values ​​between a predetermined minimum speckle contrast value greater than zero and a predetermined maximum speckle contrast value. In some embodiments, if the minimum speckle contrast value used for thresholding is zero, no values ​​are discarded (relative to the low threshold) because the theoretical minimum value for speckle contrast values ​​is zero. However, in other embodiments, the minimum value is greater than zero, in which case the system may discard values ​​below the selected minimum value. This is distinct from transparency. In some embodiments, transparency applies only to values ​​between a selected minimum speckle contrast value and a selected maximum speckle contrast value and may refer to the amount of transparency to be applied when the speckle contrast value is superimposed on a white light image of tissue. For example, 0% transparency would mean that the speckle contrast value is not visible and only the tissue is visible, while 100% transparency would mean that the speckle contrast value is visible but the tissue is not.

[0087] At step 610, computing device 400 (eg, remote computing device 114) applies a color map to the LSCI image. In some embodiments, the color map is an 8-bit color map; however, the color map can be any n-bit color map.

[0088] At step 612, the thresholded and / or color-mapped LSCI image is registered with a second image (e.g., a white light image) captured by the second camera 112, as described below. In some embodiments, the LSCI image and the second image are spatially registered using an affine transformation. In some embodiments, the LSCI image and the second image are spatially registered using a lookup table that maps pixels of the laser speckle contrast image and the white light image to one another.

[0089] In conjunction with processing of the first image (e.g., the raw laser speckle image), at step 614, the second camera 112 captures a second, white-light image of the target area of ​​the subject. As described above, white light can be emitted by the second light source 106, passed through the second optics 108, and onto the target area of ​​the subject. In some embodiments, the white light reflected from the tissue is filtered using a filter configured to pass one or more wavelengths between 350 nm and 850 nm. In some embodiments, a polarizing filter is used to polarize the reflected white light.

[0090] As described herein, a "target region" of a subject is typically a tissue region. "Tissue" can include any part of the body and can be internal (e.g., the surface of the brain) or external (e.g., the skin or the eye). It will be appreciated that in some embodiments, a single camera can be used to record both the laser speckle contrast image and the white light image. This can be achieved by interleaving the acquisition of the laser speckle image and the white light image. For example, the laser speckle image can be acquired using the first optics 104 in front of a single camera, and then the first optics 104 can be switched with the second optics 108 and the white light image recorded on the single camera. During this interleaving process, the light source 102 and the second light source 106 can illuminate the tissue continuously or in a controlled manner, such that the first light source 102 illuminates during the capture of the laser speckle image and the second light source 106 illuminates during the capture of the white light image.

[0091] The second image can then be transmitted to the remote computing device 114 for additional processing. At step 616, the remote computing device 114 spatially registers the second image with the first LSCI image. In some embodiments, the LSCI image and the second image are spatially registered using an affine transformation. In some embodiments, the LSCI image and the second image are spatially registered using a lookup table that maps pixels of the laser speckle contrast image and the white light image to one another.

[0092] At step 618, the spatially registered, thresholded, and color-mapped LSCI image is overlaid onto the second image. In this manner, the remote computing device 114 can generate a corresponding continuous stream of red, green, and blue (RGB) images depicting blood flow in the overlaid tissue. In some embodiments, a "continuous image stream" is defined as at least one frame / image per second. In some embodiments, a "continuous image stream" is a video with a duration greater than 0.5 seconds and / or is continuous. However, in other embodiments, the duration can be 10 seconds, 30 seconds, 60 seconds, or longer.

[0093] By now, it should be understood that, in some embodiments, process 600 can be repeated continuously to generate a real-time or near-real-time video feed that superimposes LSCI images on white-light images to visualize blood flow within the context of the subject's anatomy. In some implants, as described above, the superimposed LSCI and white-light images / video are presented via a user interface, e.g., in real-time or near-real-time. As used herein, "real-time" is clinically defined as allowing a healthcare provider using the visualization system to visualize blood flow (e.g., pulsation) in the video stream simultaneously with the blood flow as it progresses within the patient's body. In some embodiments, real-time is at least five frames per second; however, even if the superimposed image is displayed at five frames per second or higher, the LSCI images or white-light images may be acquired at slower rates than five frames per second. In some embodiments, the video stream includes a field of view greater than 5 mm x 5 mm. In some embodiments, the video stream includes RBG images that record blood flow cessation caused by surgical intervention. For example, LSCI images can be acquired continuously so that the surgeon can immediately see whether their actions have resulted in the desired blood flow obstruction (e.g., clamping).

[0094] In some embodiments, in response to the laser speckle contrast image having a laser speckle contrast value between a predetermined minimum speckle contrast value and a predetermined maximum speckle contrast value, the video stream includes a blood flow greater than a minimum blood flow, the minimum blood flow being greater than or equal to zero and less than a maximum blood flow. In some embodiments, in response to the laser speckle contrast image having a laser speckle contrast value between a predetermined minimum speckle contrast value and a predetermined maximum speckle contrast value, the video stream does not include a blood flow less than the minimum blood flow or greater than the maximum blood flow. In some embodiments, in response to the laser speckle contrast image having a laser speckle contrast value between a predetermined minimum speckle contrast value and a predetermined maximum speckle contrast value, the video stream includes a blood flow greater than a minimum blood flow, the minimum blood flow being greater than zero and less than the maximum blood flow. In some embodiments, in response to the laser speckle contrast image having a laser speckle contrast value between a predetermined minimum speckle contrast value and a predetermined maximum speckle contrast value, the video stream does not include a blood flow less than the minimum blood flow or greater than the maximum blood flow.

[0095] In some embodiments, a third camera is used to capture fluorescence images, for example, simultaneously with the laser speckle image and the white light image. In some embodiments, the third camera is a NIR camera. Fluorescence imaging includes, for example, ICGA. In some embodiments, laser speckle contrast imaging and additional imaging are performed simultaneously, where the laser speckle contrast image is based on the laser speckle contrast imaging, and the additional imaging includes at least one of Doppler imaging, ultrasound imaging, percutaneous transfemoral DSA, or a combination thereof. In some embodiments, a single camera can be used to record both the fluorescence image and the original laser speckle image by interleaving the laser speckle and fluorescence image acquisitions. In some embodiments, a single camera can be used to perform laser speckle contrast imaging, fluorescence imaging, and white light imaging as described above.

[0096] In some embodiments, although Figure 6 Although not shown, process 600 can further include spatially registering the laser speckle contrast image, the white light image, and the fluorescence image with one another. In some embodiments, process 600 can further include simultaneously performing multispectral reflectance imaging (MSRI) and laser speckle contrast imaging, wherein the laser speckle contrast image is based on the laser speckle contrast imaging. In some embodiments, process 600 can further include simultaneously performing hyperspectral imaging and laser speckle contrast imaging, wherein the laser speckle contrast image is based on the laser speckle contrast imaging. In some embodiments, prior to capturing the laser speckle and / or white light images, the first field of view of the first camera 110 is aligned with the second field of view of the second camera 112. In some embodiments, the first trajectory of the first light source 102 is aligned with the second field of view.

[0097] 7A to 7D An example application of process 600 is shown, in which an example LSCI image is thresholded and superimposed on an example visible white light reflectance image.First, an LSCI image is acquired. Figure 7A An example LCSI image is shown in Figure 2 . Next, a threshold is applied to the LSCI image so that only speckle contrast values ​​corresponding to flow values ​​within a specific range (i.e., high flow in the vessel) are retained. The threshold is applied to both the LSCI image and the raw camera intensity pixels. By thresholding the raw camera intensity pixels to include only well-illuminated areas, the LSCI image reduces artifacts caused by poor lighting. By thresholding the LSCI image between the minimum and maximum speckle contrast values, the contrast of the LSCI image is enhanced for visualization, allowing areas of specific blood flow to be optimized for mapping onto the color lookup table. In addition to thresholding, a 2D Gaussian blur filter is applied to smooth the LSCI image. Figure 7B An example thresholded image is shown in .

[0098] Next, the laser speckle contrast values ​​within the threshold limits are mapped onto a color map. In some embodiments, the color map is user-configured. Example color maps can include grayscale, inverse grayscale, jet or reverse jet, parula or reverse parula, etc. During this step, the LSCI image is also spatially registered with the white light image so that the pixels are aligned in the final overlaid image. Figure 7C An example white light image is shown in . In general, spatially registering an LSCI image and a white light image is referred to herein as "co-registration". Spatial alignment is performed by mapping the LSCI onto the white light image using a geometric transformation (such as an affine transformation). After applying a threshold and a color map, the LSCI image is merged with the white light image. For this step, the transparency of the thresholded and registered LSCI image can be adjusted to produce different visualization effects. In some embodiments, the thresholded and registered LSCI image is fully visible on top of the white light image. Alternatively, the thresholded and registered LSCI image can be partially transparent to show the anatomical structure beneath the thresholded and registered LSCI image. Figure 7D An example LCSI overlay image is shown in .

[0099] As discussed above, processing the LSCI frames by thresholding the raw intensity and speckle contrast values, registering the thresholded LSCI image with the white light image, and overlaying the thresholded and registered LSCI image onto the white light image to create an overlay image can be performed by the remote computing device 114 or any other suitable computing device. In some embodiments, the LSCI image and the white light image are captured and / or processed continuously (e.g., at video rate) and can be continuously displayed to the neurosurgeon or other user, such as in real time on a monitor.

[0100] The original laser speckle image (I), the speckle contrast image (K), the white light image (W), the low light intensity threshold (t1), the Gaussian blur standard deviation (σ), the lookup table that maps pixels from K(x,y) to W(x,y) based on the spatial transformation calculated during image registration (LUT), the minimum and maximum speckle contrast values ​​to be displayed (K 最小 and K 最大 ), the minimum transparency and maximum transparency of the speckle contrast overlay (α 最小 and α 最大 ), below which transparency is set to alpha that defines a colormap where each row defines an RGB color (CMAP) 最大 (K α ), a 256×3 matrix of speckle contrast values, and pseudo code for computer-implemented image analysis (e.g., process 500 and / or process 600) is provided below. The method output includes an overlay image (O) that merges the speckle contrast image and the white light image into a single RGB image.

[0101] 1. If I(x, y) ≤ t1

[0102] 2. Then set K(x, y) = 0

[0103] 3. Let K = blur(K, σ), where blur() is a two-dimensional Gaussian blur filter

[0104] 4. For (x,y) in K

[0105] 5. Then (x',y')=LUT(x,y)

[0106] 6. Make K(x',y')=K(x,y)

[0107] 7. For (x,y) in K'

[0108] 8. Then scale = (K′(x, y) - Kmin) / (Kmax - Kmin)

[0109] 9. Set index = int(255 × scale + 0.5) so that {index|0≤index≤255}

[0110] 10. Make

[0111] α=K′(x, y)×(αmax-αmin)+αmax-Kα×(αmax-αmin) / (Kα-Kmax

[0112] 11. Let O(x, y, :) = (1-α) × W(x, y, :) + α × CMAP(index, :)

[0113] As shown in the figure, a threshold is applied to K based on the value of I. Next, a two-dimensional (2D) Gaussian blur filter is applied to smooth the LSCI image. The laser speckle contrast values ​​K(x,y) are then mapped to a coordinate space W(x,y) aligned with the white light image calculated using a lookup table. The laser speckle values ​​are then thresholded and scaled, mapped to an 8-bit color map, and assigned a transparency associated with the white light image.

[0114] Experimental results

[0115] To test the system 100 and corresponding methods, as described herein, experimental surgical procedures were performed on five different subjects. Table 1 below provides a summary of the patient details.

[0116] Table 1. – Patient details

[0117]

[0118] ACOM = anterior communicating artery; CN = cranial nerve; CTA = computed tomography angiography; DSA = digital subtraction angiography; ICA = internal carotid artery; ICGA = indocyanine green angiography; MCA = middle cerebral artery; MRA = magnetic resonance angiography; SCA = superior cerebellar artery.

[0119] Prior to the surgical procedure, the field of view of the camera used for LSCI (e.g., the first camera 110) is co-aligned and centered with the built-in microscope camera (e.g., the second camera 112). In addition, the laser beam is located at the center of the built-in microscope camera's field of view. After the craniotomy is performed, the microscope is positioned above the patient at the discretion of the neurosurgeon. When the microscope is positioned above the patient, LSCI can be performed at any time by turning on the laser illumination. LSCI does not interfere with the neurosurgeon's workflow and is performed at multiple critical moments throughout the surgical procedure. The neurosurgery co-investigator performed most of the surgery using the surgical microscope eyepiece and could observe the LSCI data in real time on a monitor mounted next to the surgical microscope, which displayed superimposed blood flow images.

[0120] Now refer to Figure 8 , showing images of "Patient 2" before and after aneurysm clipping and at individual time points during ICGA. Specifically, Figure 8 The images are shown before aneurysm clipping (Pre-clip), after aneurysm clipping (Post-clip), and during ICGA during dye washout (ICGA 洗入 ) and maximum fluorescence signal (ICGA 最大 Images from "Patient 2" acquired at 4:00 p.m. (Images acquired from "Patient 2" at 4:00 p.m.). Visible light images were acquired with the built-in microscope white light camera (white light); laser speckle contrast imaging (LSCI) images were acquired with a NIR-enhanced CMOS camera suitable for the microscope; and ICGA images were acquired with the built-in microscope NIR camera. The LSCI overlay image was created by thresholding the LSCI image and overlaying it onto the pseudo-colored white light image. Scale bar = 1 cm. Figure 8 A montage of white light and LSCI overlay images before, during, and after the clipping procedure is shown. Figure 8 Also shown are white light images, LSCI overlay images, and a montage of ICGA images during injection of ICG dye.

[0121] Specifically, white light images and LSCI images were acquired throughout the duration of aneurysm clipping, and ICGA images were available only during the injection of indocyanine green dye after aneurysm clip placement. During this surgical procedure, a temporary clip was placed on the carotid artery in the patient's neck after pre-clip images but before aneurysm clipping. Figure 8 The pre-clip LSCI images in Figure 4 show that there is high flow in the aneurysm before clipping, and LSCI has the spatial resolution to allow flow in small vessels over the optic nerve (as determined by Figure 8 LSCI was used to visualize the filling of the aneurysm and the pulsatile motion of blood flow within the aneurysm during the cardiac cycle.

[0122] This was particularly evident when a temporary clip was placed on the carotid artery in the patient's neck, causing blood flow to be reduced in the aneurysm. The advantage of integrating the LSCI instrument into the microscope, compared to a stand-alone device, is that images can be acquired during microscope operation without interrupting the surgical workflow. This advantage was demonstrated when a clip was placed on the aneurysm and the LSCI blood flow map immediately showed that blood flow in the aneurysm had ceased. Figure 8 Approximately five minutes after clipping, ICGA was used to confirm successful aneurysm occlusion and confirm the patency of the surrounding vessels. Figure 8 The maximum fluorescence signal (ICGA 最大 ) during which time the ICGA image showed cessation of blood flow in the aneurysm.

[0123] Now refer to Figure 9A and Figure 9B , shows an example graph of relative CBF during a clipping procedure according to some embodiments. Specifically, Figure 9A and Figure 9B Shown in 110 seconds ( Figure 9A ) and zoom in to the first 20 seconds ( Figure 9B Time course of relative CBF within the aneurysm from "Patient 2" during the clipping procedure (Figure 2). Relative CBF is normalized to the first five seconds of data. The pulsatile nature of blood flow in the aneurysm is clearly visible before and after the temporary clip is placed on the carotid artery. The reduction in CBF following temporary carotid artery clipping is immediately apparent. The cessation of blood flow following clipping is also evident. All transients following aneurysm clipping (t = 45 seconds) are motion artifacts.

[0124] in this regard, Figure 9A and Figure 9B Flow dynamics within the aneurysm were quantified in . Pulsatile flow in the aneurysm was seen before and after a temporary clip was placed on the carotid artery in the neck. After placement of the temporary clip on the carotid artery, mean CBF was reduced by approximately 70%, and pulsatile flow within the aneurysm was clearly visible with a zero value of <5% and variable peaks of 50-80% of baseline. After placement of the clip on the aneurysm, blood flow was significantly reduced, and the pulsatile flow completely disappeared. The transient spike after clip placement was due to motion artifact from the surgeon mechanically pushing on the aneurysm. After repositioning the microscope, it was apparent that CBF within the aneurysm was absent and within the lower limit of single-exposure LSCI measurements (approximately 4% of the initial CBF).

[0125] Now refer to Figure 10 , shows a plurality of example images captured from a patient during ICGA according to some embodiments. Specifically, Figure 10 Including during ICGA at the start of injection (ICGA 开始 ), dye wash-in (ICG 洗入 ) and maximum fluorescence signal (ICGA 最大 ) from "Patient 4". Figure 10 A montage of white-light images, ICGA images, and LSCI blood flow images throughout the ICGA procedure is shown, with green pseudocolor used for the LSCI overlay. Visible-light images were acquired from the built-in microscope white-light camera (white light); laser speckle contrast imaging (LSCI) images were acquired with a NIR-enhanced CMOS camera adapted for the microscope; and ICGA images were acquired with the built-in microscope NIR camera. The LSCI overlay image was created by thresholding the LSCI image and overlaying it onto the white-light image. Scale bar = 1 cm.

[0126] Now refer to Figure 11A and Figure 11B , shows example images comparing LSCI overlays with ICGA overlays according to some embodiments. Specifically, Figure 11A and Figure 11B Provided from "Patient 4" ( Figure 11A ) Laser Speckle Contrast Imaging (LSCI) superposition and ( Figure 11B ) Indocyanine green angiography (ICGA) overlay contrast. These images were created by overlaying LSCI data and ICGA data onto the built-in microscope white light camera and applying a green pseudocolor. Arrows emphasize LSCI's ability to detect blood flow in sidewall vessels. Scale bar is one centimeter.

[0127] Now refer to Figure 12A and Figure 12B , shows images captured during arteriovenous malformation (AVM) resection from "Patient 5," according to various embodiments. Specifically, Figure 12A Included are several example images of arteriovenous malformation (AVM) resection in accordance with some embodiments. Figure 12B is an example graph of average speckle contrast values ​​before and after AVM resection according to some embodiments. Figure 12A , a white light image showing the draining veins of the AVM (outline) before the AVM is resected is shown. In addition, Figure 12A Includes grayscale LSCI visualization captured simultaneously with the white light image. The box on the vein represents Figure 12B The target area is drawn in . Figure 12A Also included are light images showing the draining veins after AVM resection and grayscale LSCI visualizations captured simultaneously with the white light images. The boxes in these images define Figure 12B Therefore, Figure 12B is a graph of the mean speckle contrast values ​​from the orange highlighted box before and after AVM resection.

[0128] Now refer to Figure 13A and Figure 13B , shows the time course of fluorescence intensity changes during bolus administration of ICG and LSCI measures of relative blood flow in the same target area according to some embodiments. Specifically, Figure 13A Included are several example images demonstrating changes in fluorescence intensity during a bolus administration of indocyanine green (ICG) and LSCI measurements of relative blood flow to the same target area, according to some embodiments. Figure 13B FIG is an example graph of fluorescence intensity changes during bolus administration of ICG and LSCI measurements of relative blood flow in the same target area according to some embodiments. Figure 13B (middle) highlighted in Figure 13A middle. Figure 13A The bottom includes Figure 13A The top ICGA image is an LSCI overlay image at the same time. Figure 13B The three target regions selected in the LSCI overlay shown in Figure 13A The same area as highlighted in . Figure 13B The time course of changes in ICG fluorescence intensity (top) and relative blood flow measured by LSCI (bottom) during ICG bolus administration were quantified.

[0129] Results and Discussion

[0130] Figure 12A and Figure 12B Showing the long-term monitoring of the AVM drainage vein of "Patient 5" by LSCI ( Figure 12A capacity of the traffic in the overview). Figure 12A A white light image and a grayscale speckle contrast image captured at the same time point before AVM resection are shown; due to the AVM, the draining vessels were arterialized before resection. Figure 12A Shown are white light and grayscale speckle contrast images after resection captured at the same time points of one hour and 35 minutes, respectively. Figure 12B Drawn Figure 12A The average speckle contrast value in the target area highlighted in orange in Figure 3 demonstrates that the flow in the draining vein after AVM resection is lower than the flow in the draining vein before resection, indicating that flow no longer bypasses the capillary network through the AVM.

[0131] The results of the present study indicate that LSCI can be used to monitor CBF continuously in real time. Figure 8 The embodiments discussed herein demonstrate that, when integrated into a surgical microscope and superimposed on the surgeon's surgical field, LSCI can continuously monitor CBF during critical portions of neurosurgery. LSCI revealed high blood flow within the aneurysm before clipping and immediate cessation of aneurysm blood flow after clipping, while surrounding vessels remained perfused. ICGA was then used to confirm the patency of the surrounding vessels, but this required the administration of a dye. This demonstrates that LSCI complements ICGA; both can be used to determine perfusion of vessels within the surgical field.

[0132] Figure 9A and Figure 9B The results shown in demonstrate that LSCI enables quantification of flow in an aneurysm relative to a baseline value. LSCI can detect a pulsatile flow profile within the aneurysm prior to clipping. After clipping, LSCI showed a >96% reduction in blood flow in the aneurysm relative to the initial flow, with no pulsatile flow. The uncertainty in the relative flow measured by LSCI can be approximately 5% because LSCI is sensitive to any form of motion within the tissue; thus, an aneurysm can be completely occluded, but the LSCI signal will not be reduced by 100% from baseline. It is expected that the LSCI signal will still be sensitive to the Brownian motion of scattered particles within the aneurysm, but that the signal will be significantly smaller than the flow from red blood cells into the aneurysm. While further work is needed to determine the percentage of blood flow reduction that will allow surgeons to be confident that the aneurysm is completely occluded, Figure 10 Preliminary evidence was provided that a 96% reduction in aneurysm blood flow as measured by LSCI indicated successful aneurysm occlusion.

[0133] Delineation of CBF within the aneurysm Figure 9A and Figure 9B The waveforms in the match those measured with Doppler ultrasonography and Doppler velocity lines. Figure 9A and Figure 9B We emphasize that LSCI allows for continuous CBF measurements within aneurysms throughout neurosurgical procedures and thus LSCI can be used to improve our understanding of hemodynamics in aneurysms and validate computational fluid dynamics models of aneurysm growth and rupture.

[0134] Figure 12A and Figure 12B demonstrated the ability of LSCI to long-term monitor blood flow in surface vessels during AVM resection. Figure 12A Specifically, it was shown that the surface vessels immediately adjacent to the AVM were initially arterialized, and then had reduced flow after AVM resection. This suggests that LSCI has the potential to quantify flow in both feeding and draining vessels in real time during AVM resection, which can take several hours, thereby providing surgeons with important and actionable information regarding surgical success. Future work will aim to establish the reproducibility of such flow measurements as the surgical environment changes.

[0135] Figure 13A and Figure 13B The complementary nature of the information obtained with LSCI and ICGA when integrated into a surgical operating microscope was further demonstrated. ICGA intensity is a more direct measure of cerebral blood volume (CBV), while LSCI is directly sensitive to motion and is therefore a more direct measure of CBF. ICGA washout can also be used to identify feeding and draining vessels in certain surgical procedures, and the temporal dynamics of fluorescence intensity can be used to estimate CBF. Figure 13A and Figure 13B The time course of fluorescence intensity changes during a bolus administration of ICG is shown, along with the LSCI measure of relative blood flow in the same target region. In this particular example, the ICG fluorescence signal saturates in the largest vessel, but it is still clear that the rise time of the ICG signal in this vessel is faster than that in the two smaller vessels, indicating higher flow. LSCI signals from the same region reveal similar information, but in a different way. LSCI signals are steady-state, meaning they are a direct measure of flow that is relatively constant over the measurement period. However, the relative flow across each target region is evident from the steady-state values ​​of the speckle decorrelation time. Therefore, while LSCI cannot quantify absolute CBF, it can be used to estimate relative CBF over time or across spatial regions.

[0136] Despite the differences between LSCI and ICGA, LSCI can be used to create images that look very similar to ICGA images. Figures 11A to 11B The results of the comparison of the simultaneous LSCI and ICGA images shown with the embodiments described herein demonstrate the complementary nature of the information provided by LSCI during ICGA. Figure 11A ) and ICGA superimposed images ( Figure 11B ) shows similar spatial information when rendered with a similar green colormap and superimposed on the surgeon's view.

[0137] Because ICGA uses fluorescent dyes as contrast agents, ICGA is better able to visualize blood flow in larger vessels, while LSCI uses the inherent properties of blood flow to scatter laser light. In contrast, LSCI has advantages in visualizing blood flow in small vessels, as shown in Figure 11 on a vessel located in the side wall marked by a blue arrow; and in Figure 12 where LSCI shows CBF in a small vessel supplying the optic nerve. Figure 8 ICGA also has the advantage of providing directionality of blood flow during dye wash-in.

[0138] One limitation of LSCI is that it is sensitive to motion from both blood flow and the surgeon's mechanical forces on the brain tissue. Therefore, the LSCI overlay video cannot distinguish between the two sources of motion. However, surgeon-induced motion can be avoided by the surgeon pausing for a moment and observing the LSCI overlay without pushing on the tissue.

[0139] The embodiments described herein demonstrate the potential of LSCI for continuous CBF monitoring during neurovascular surgery. Integrating the LSCI device into the surgical operating microscope enables continuous CBF visualization and allows for simultaneous acquisition of LSCI and ICGA. Figure 9A 、 Figure 9B The time courses of relative blood flow shown in Figure 11 and the LSCI superposition presented herein demonstrate the ability of LSCI to monitor CBF continuously and in real time. Figure 8 、 Figure 10 , Figure 11 and Figure 13A The sequence of simultaneous LSCI images and ICGA images shown in demonstrates that LSCI and ICGA provide complementary information about CBF, as both can be used to determine perfusion in vessels.

[0140] The embodiments demonstrate that LSCI can provide continuous, real-time visualization of CBF without disrupting the surgeon's workflow or requiring contrast agents, and is therefore a promising tool for continuous CBF monitoring during surgery. By integrating the LSCI device into the surgical operating microscope, the embodiments performed LSCI during critical parts of neurovascular surgery and provided the surgeon with immediate, actionable information regarding surgical success. The embodiments allow for the simultaneous acquisition of LSCI and ICGA, demonstrating that LSCI and ICGA are complementary tools for visualizing CBF to aid surgical decision-making.

[0141] Configuration of certain embodiments

[0142] The construction and arrangement of the system and method as shown in various embodiments are only illustrative. Although only some embodiments are described in detail in the present disclosure, many modifications are possible (for example, the size, dimensions, structure, shape and ratio, parameter value, installation arrangement, use of material, color, orientation, etc. of various elements). For example, the positioning of elements can be reversed or otherwise changed, and the property or quantity of discrete elements or positioning can be changed or changed. Therefore, all such modifications are intended to be included in the scope of the present disclosure. According to alternative embodiments, the order or sequence of any process or method step can be changed or reordered. Without departing from the scope of the present disclosure, other replacements, modifications, changes and omissions can be made in the design, operating conditions and arrangement of the embodiments.

[0143] The present disclosure contemplates methods, systems, and program products on any machine-readable medium for completing various operations. The embodiments of the present disclosure can be implemented using existing computer processors, 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. Embodiments within the scope of the present disclosure include program products that include a machine-readable medium for carrying or storing machine-executable instructions or data structures thereon. Such machine-readable media 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 machine-readable media 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.

[0144] 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 properly views the connection as a machine-readable medium. Therefore, any such connection is properly referred to as a machine-readable medium. Combinations of the foregoing 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, special-purpose computer, or special-purpose processing machine to perform a specific function or group of functions.

[0145] Although the accompanying drawings illustrate a specific order of method steps, the order of the steps may vary 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 designer choices. All such variations are within the scope of this disclosure. Similarly, software implementations may be accomplished using standard programming techniques as well as rule-based logic and other logic to complete the various connection steps, processing steps, comparison steps, and decision steps.

[0146] 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 aspects only and is not intended to be limiting.

[0147] As used in the specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates 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 embodiment includes the from the one particular value and / or to the other particular value. Similarly, when a value is expressed as an approximation using the antecedent "about," it should be understood that the particular value forms another embodiment. It should be further understood that the endpoints of each range are significant both in relation to the other endpoint and independently of the other endpoint.

[0148] "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.

[0149] Throughout the description and claims of this specification, the word "comprising" and variations thereof, such as "including" 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 embodiment. "Such as" is not used in a limiting sense, but rather for illustrative purposes.

[0150] The present invention discloses components that can be used to perform the methods and systems 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 of them is specifically contemplated and described herein for use in all methods and systems. This applies to all aspects of this patent application, including but not limited to the steps in the methods disclosed herein. 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 embodiment or combination of embodiments of the disclosed methods.

[0151] Example Implementation

[0152] Example 1. A method for visualizing blood flow, comprising: [A] simultaneously illuminating: (a) a blood flow with first light from a first light source, and (b) a tissue with second light from a second light source, wherein: (c)(i) the first light source is a coherent light source and the first light has a first wavelength, and (c)(ii) the second light source is a white light source and the second light has one or more wavelengths between 350 nm and 850 nm; [B] in response to illuminating the blood flow with the first light, (a) filtering backscattered light from the blood flow with a first filter configured to pass the first wavelength, and (b) polarizing the backscattered light with a first polarizer; [C] in response to filtering and polarizing the backscattered light, recording a raw laser speckle image with a first camera; [D] in response to illuminating the tissue with the second light, recording a laser speckle image with a second camera. [E] deriving a laser speckle contrast image from the raw laser speckle image, wherein: (a) the laser speckle contrast image is based on a sliding pixel window, and (b) the laser speckle contrast image has a laser speckle contrast value between a predetermined minimum speckle contrast value greater than zero and a predetermined maximum speckle contrast value; [F] spatially registering the laser speckle contrast image and the white light image with each other; [G] in response to spatially registering the laser speckle contrast image with the white light image, overlaying the laser speckle contrast image with the white light image to generate a corresponding continuous red, green, blue (RGB) image stream depicting the blood flow of the overlaid tissue; [H] outputting the continuous RBG image stream depicting the blood flow of the overlaid tissue as a video stream, wherein the video stream has a duration greater than 0.5 seconds and is continuous.

[0153] Example 2. A method for visualizing blood flow, comprising: [A] illuminating: (a) a blood flow with first light from a first light source, and (b) a tissue with second light from a second light source, wherein: (c)(i) the first light comprises a first wavelength, and (c)(ii) the second light has one or more wavelengths between 350 nm and 850 nm; [B] in response to illuminating the blood flow with the first light, (a) filtering backscattered light from the blood flow with a first filter configured to pass the first wavelength, and (b) polarizing the backscattered light with a first polarizer; [C] in response to filtering and polarizing the backscattered light, recording a raw laser speckle image with a first camera; [D] in response to illuminating the tissue with the second light, recording an image with a second camera; [E] obtaining a laser speckle pattern from the raw laser speckle image. [F] spatially registering the laser speckle contrast image and the image of the second camera with each other; [G] in response to spatially registering the laser speckle contrast image with the image of the second camera, overlaying the laser speckle contrast image with the image of the second camera to generate a corresponding continuous red, green, blue (RGB) image stream depicting the blood flow of the overlaid tissue; [H] outputting the continuous RBG image stream depicting the blood flow of the overlaid tissue as a video stream, wherein the duration of the video stream is greater than 0.5 seconds and is continuous.

[0154] Example 3. A method for visualizing blood flow, comprising: [A] simultaneously illuminating: (a) a blood flow with first light from a first light source, and (b) a tissue with second light from a second light source, wherein: (c)(i) the first light source is a coherent light source and the first light has a first wavelength, and (c)(ii) the second light source is a white light source and the second light has one or more wavelengths between 350 nm and 850 nm; [B] in response to illuminating the blood flow with the first light, (a) filtering backscattered light from the blood flow with a first filter configured to pass the first wavelength, and (b) polarizing the backscattered light with a first polarizer; [C] in response to filtering and polarizing the backscattered light, recording a raw laser speckle image with a first camera; [D] in response to illuminating the tissue with the second light, recording a white light image with a second camera. [E] deriving a laser speckle contrast image from the raw laser speckle image, wherein: (a) the laser speckle contrast image is based on a sliding pixel window, and (b) the laser speckle contrast image has a laser speckle contrast value between a predetermined minimum speckle contrast value greater than or equal to zero and a predetermined maximum speckle contrast value; [F] spatially registering the laser speckle contrast image and the white light image with each other; [G] in response to spatially registering the laser speckle contrast image with the white light image, overlaying the laser speckle contrast image with the white light image to generate a corresponding continuous red, green, blue (RGB) image stream depicting the blood flow of the overlaid tissue; [H] outputting the continuous RBG image stream depicting the blood flow of the overlaid tissue as a video stream, wherein the video stream has a duration greater than 0.5 seconds and is continuous.

[0155] Example 4. A method for visualizing blood flow, comprising: [A] illuminating: (a) a blood flow with first light from a first light source, and (b) a tissue with second light from a second light source, wherein: (c)(i) the first light source is a coherent light source and the first light has a first wavelength, and (c)(ii) the second light source is a white light source and the second light has one or more wavelengths between 350 nm and 850 nm; [B] in response to illuminating the blood flow with the first light, (a) filtering backscattered light from the blood flow with a first filter configured to pass the first wavelength, and (b) polarizing the backscattered light with a first polarizer; [C] in response to filtering and polarizing the backscattered light, recording a raw laser speckle image with a first camera; [D] in response to illuminating the tissue with the second light, recording a white light image with a second camera. [E] deriving a laser speckle contrast image from the raw laser speckle image, wherein: (a) the laser speckle contrast image is based on a sliding pixel window, and (b) the laser speckle contrast image has a laser speckle contrast value between a predetermined minimum speckle contrast value greater than or equal to zero and a predetermined maximum speckle contrast value; [F] spatially registering the laser speckle contrast image and the white light image with each other; [G] in response to spatially registering the laser speckle contrast image with the white light image, overlaying the laser speckle contrast image with the white light image to generate a corresponding continuous red, green, blue (RGB) image stream depicting the blood flow of the overlaid tissue; [H] outputting the continuous RBG image stream depicting the blood flow of the overlaid tissue as a video stream, wherein the video stream has a duration greater than 0.5 seconds and is continuous.

[0156] Example 5. A method for visualizing blood flow, comprising: [A] illuminating: (a) a blood flow with first light from a first light source, and (b) a tissue with second light from a second light source, wherein: (c)(i) the first light comprises a first wavelength, and (c)(ii) the second light has one or more wavelengths between 350 nm and 850 nm; [B] in response to illuminating the blood flow with the first light, (a) filtering backscattered light from the blood flow with a first filter configured to pass the first wavelength, and (b) polarizing the backscattered light with a first polarizer; [C] in response to filtering and polarizing the backscattered light, recording a raw laser speckle image with a camera; [D] in response to illuminating the tissue with the second light, recording a non-raw laser speckle image with the camera; [E] deriving a non-raw laser speckle image from the raw laser speckle image

[0014] A laser speckle contrast image, wherein: (a) the laser speckle contrast image is based on a sliding pixel window, and (b) the laser speckle contrast image has a laser speckle contrast value between a predetermined minimum speckle contrast value greater than or equal to zero and a predetermined maximum speckle contrast value; [F] spatially registering the laser speckle contrast image and the non-original laser speckle image with each other; [G] in response to spatially registering the laser speckle contrast image with the non-original laser speckle image, overlaying the laser speckle contrast image with the non-original laser speckle image to generate a corresponding continuous stream of red, green, blue (RGB) images depicting blood flow in the overlaid tissue; [H] outputting the continuous stream of RGB images depicting blood flow in the overlaid tissue as a video stream, wherein the video stream has a duration greater than 0.5 seconds and is continuous.

[0157] Example 6. A method for visualizing blood flow, comprising: [A] illuminating: (a) a blood flow with first light from a first light source, and (b) a tissue with second light from a second light source, wherein: (c)(i) the first light comprises a first wavelength, and (c)(ii) the second light has one or more wavelengths between 350 nm and 850 nm; [B] in response to illuminating the blood flow with the first light, (a) filtering backscattered light from the blood flow with a first filter configured to pass the first wavelength, and (b) polarizing the backscattered light with a first polarizer; [C] in response to filtering and polarizing the backscattered light, recording a raw laser speckle image with a first camera; [D] in response to illuminating the tissue with the second light, recording an image with a second camera; [E] deriving a laser speckle contrast image from the raw laser speckle image, wherein the laser speckle contrast image has a laser speckle contrast value between a predetermined minimum speckle contrast value greater than or equal to zero and a predetermined maximum speckle contrast value; [F] spatially registering the laser speckle contrast image and the image of the second camera with each other; [G] in response to spatially registering the laser speckle contrast image with the image of the second camera, overlaying the laser speckle contrast image with the image of the second camera to generate a corresponding continuous red, green, blue (RGB) image stream depicting the blood flow of the overlaid tissue; [H] outputting the continuous RBG image stream depicting the blood flow of the overlaid tissue as a video stream, wherein the duration of the video stream is greater than 0.5 seconds and is continuous.

[0158] Example 7. A method for visualizing blood flow, comprising: [A] illuminating: (a) a blood flow with first light from a first light source, and (b) a tissue with second light from a second light source, wherein: (c)(i) the first light comprises a first wavelength, and (c)(ii) the second light has one or more wavelengths between 350 nm and 850 nm; [B] in response to illuminating the blood flow with the first light, (a) filtering backscattered light from the blood flow with a first filter configured to pass the first wavelength, and (b) polarizing the backscattered light with a first polarizer; [C] in response to filtering and polarizing the backscattered light, recording a raw laser speckle image with a first camera; [D] in response to illuminating the tissue with the second light, a second camera recording an image; [E] deriving a laser speckle contrast image from the raw laser speckle image, wherein: (a) the laser speckle contrast image is based on a sliding pixel window, and (b) the laser speckle contrast image has a laser speckle contrast value between a predetermined minimum speckle contrast value greater than or equal to zero and a predetermined maximum speckle contrast value; [F] spatially registering the laser speckle contrast image and the image of the second camera with each other; [G] in response to spatially registering the laser speckle contrast image with the image of the second camera, superimposing the laser speckle contrast image with the image of the second camera to generate an image stream depicting the blood flow superimposed on the tissue; [H] outputting the image stream depicting the blood flow superimposed on the tissue as a video stream.

[0159] Example 8. A method for visualizing blood flow, comprising: [A] illuminating: (a) a blood flow with first light from a first light source, and (b) a tissue with second light from a second light source, wherein: (c)(i) the first light comprises a first wavelength, and (c)(ii) the second light has one or more wavelengths between 350 nm and 850 nm; [B] in response to illuminating the blood flow with the first light, (a) filtering backscattered light from the blood flow with a first filter configured to pass the first wavelength, and (b) polarizing the backscattered light with a first polarizer; [C] in response to filtering and polarizing the backscattered light, recording a raw laser speckle image with a first camera; [D] in response to illuminating the tissue with the second light, recording a raw laser speckle image with a second polarizer. [E] deriving a laser speckle contrast image from the raw laser speckle image, wherein: (a) the laser speckle contrast image is based on a sliding pixel window, and (b) the laser speckle contrast image has a laser speckle contrast value between a predetermined minimum speckle contrast value greater than or equal to zero and a predetermined maximum speckle contrast value; [F] registering the laser speckle contrast image and the image of the second camera with each other; [G] in response to registering the laser speckle contrast image with the image of the second camera, superimposing the laser speckle contrast image with the image of the second camera to generate a red, green, blue (RGB) image depicting the blood flow of the superimposed tissue; [H] outputting the RBG image depicting the blood flow of the superimposed tissue.

[0160] Example 9. The method of any one of Examples 1 to 8, comprising outputting the video stream in real time while illuminating the blood flow and the tissue.

[0161] Example 10. The method of any one of examples 1 to 9, wherein the spatially registered laser speckle contrast image and white light image are based on an affine transformation.

[0162] Example 11. A method according to any one of Examples 1 to 10, wherein the second camera is included in one of a surgical microscope, an endoscope, an exoscope, and a robotic surgical platform.

[0163] Example 12. The method of any one of Examples 1 to 11, wherein the video stream comprises a field of view greater than 5 mm x 5 mm.

[0164] Example 13. A method according to any one of Examples 1 to 12, wherein: [A] in response to the laser speckle contrast image having a laser speckle contrast value between a predetermined minimum speckle contrast value and a predetermined maximum speckle contrast value, the video stream includes a blood flow greater than a minimum blood flow, and the minimum blood flow is greater than or equal to zero and less than a maximum blood flow; [B] in response to the laser speckle contrast image having a laser speckle contrast value between a predetermined minimum speckle contrast value and a predetermined maximum speckle contrast value, the video stream does not include a blood flow less than the minimum blood flow or greater than the maximum blood flow.

[0165] Example 14. A method according to any one of Examples 1 to 12, wherein: [A] in response to the laser speckle contrast image having a laser speckle contrast value between a predetermined minimum speckle contrast value and a predetermined maximum speckle contrast value, the video stream includes a blood flow greater than a minimum blood flow, and the minimum blood flow is greater than zero and less than a maximum blood flow; [B] in response to the laser speckle contrast image having a laser speckle contrast value between a predetermined minimum speckle contrast value and a predetermined maximum speckle contrast value, the video stream does not include a blood flow less than the minimum blood flow or greater than the maximum blood flow.

[0166] Example 15. A method according to any one of Examples 1 to 14, comprising, in response to illuminating the tissue with the second light, (a) filtering the reflected white light reflected from the tissue with a second filter configured to pass one or more wavelengths between 350 nm and 850 nm, and (b) polarizing the reflected white light reflected from the tissue with a second polarizer.

[0167] Example 16. The method of any one of Examples 1 to 15, wherein the first filter is configured to block one or more wavelengths of the second light between 350 nm and 850 nm. However, in other embodiments, the first filter is configured to enable simultaneous LSCI acquisition during indocyanine green illumination and block non-laser light.

[0168] Example 17. The method of any one of Examples 1 to 16, wherein the first light source and the second light source are fixedly coupled to each other to move in tandem with one another in response to user manipulation of the first light source and the second light source.

[0169] Example 18. The method of any one of Examples 1 to 17, comprising applying a color map to the laser speckle contrast image.

[0170] Example 19. The method of any one of Examples 1 to 18, comprising spatially registering the laser speckle contrast image and the white light image with one another based on a lookup table that maps pixels of the laser speckle contrast image and the white light image with one another.

[0171] Example 20. A method according to any one of Examples 1 to 19, comprising: [A] separating the laser speckle contrast image having a laser speckle contrast value between the predetermined minimum speckle contrast value and the predetermined maximum speckle contrast value from the laser speckle contrast image not having a laser speckle contrast value between the predetermined minimum speckle contrast value and the predetermined maximum speckle contrast value; [B] in response to separating the laser speckle contrast image, spatially aligning the laser speckle contrast image and the white light image with each other.

[0172] Example 21. The method of any one of Examples 1 to 20, comprising, in response to spatially registering the laser speckle contrast image and the white light image with each other, separating the laser speckle contrast image having laser speckle contrast values ​​between the predetermined minimum speckle contrast value and the predetermined maximum speckle contrast value from the laser speckle contrast image not having laser speckle contrast values ​​between the predetermined minimum speckle contrast value and the predetermined maximum speckle contrast value.

[0173] Example 22. The method of any one of Examples 1 to 21, comprising simultaneously performing fluorescence imaging and laser speckle contrast imaging, wherein the laser speckle contrast image is based on the laser speckle contrast imaging.

[0174] Example 23. The method of Example 22, further comprising simultaneously recording the raw laser speckle image with the first camera, the white light image with the second camera, and the fluorescence image with a third camera. In some embodiments, the third camera may include a NIR camera.

[0175] Example 24. The method of any one of Examples 1 to 23, comprising spatially registering the laser speckle contrast image, the white light image, and the fluorescence image with one another.

[0176] Example 25. The method of any one of examples 1 to 24, comprising simultaneously performing multispectral reflectance imaging (MSRI) and laser speckle contrast imaging, wherein the laser speckle contrast image is based on the laser speckle contrast imaging.

[0177] Example 26. The method according to any one of Examples 1 to 25, comprising simultaneously performing hyperspectral imaging and laser speckle contrast imaging, wherein the laser speckle contrast image is based on the laser speckle contrast imaging.

[0178] Example 27. A method according to any one of Examples 1 to 26, comprising: [A] aligning a first field of view of the first camera with a second field of view of the second camera; [B] aligning a first trajectory of the first light source with the second field of view.

[0179] Example 28. The method of any one of Examples 1 to 27, wherein the video stream includes RBG images recording blood flow cessation caused by the surgical intervention. For example, LSCI images can be acquired continuously so that the surgeon can immediately see whether her or his actions have caused the desired blood flow occlusion (e.g., clipping).

[0180] Example 29. The method of any one of Examples 1 to 28, comprising determining a transparency level of the laser speckle contrast image, the laser speckle contrast image having a laser speckle contrast value between the predetermined minimum speckle contrast value and the predetermined maximum speckle contrast value.

[0181] Example 30. The method of any one of Examples 1 to 29, wherein the laser speckle contrast image is a spatial laser speckle contrast image.

[0182] Example 31. A method for visualizing blood flow, comprising: [A] determining a laser speckle contrast imaging (LSCI) image of blood flow; [B] applying a threshold to the LSCI image to separate a first LSCI image from a second LSCI image, wherein the first LSCI image corresponds to a higher blood flow level than the second LSCI image; [C] applying pseudo color to the first LSCI image; [D] superimposing the first LSCI image with a white light image acquired simultaneously with the speckle image corresponding to the first LSCI image.

[0183] Example 32. At least one non-transitory machine-readable medium comprising a plurality of instructions that, in response to being executed on a computing device, cause the computing device to perform the method of any one of Examples 1 to 31.

[0184] Example 33. A processor-based system arranged to perform the method according to any one of examples 1 to 31.

[0185] Example 34. An apparatus comprising means for performing any of Examples 1 to 31.

[0186] Example 35. A blood flow visualization system comprising: [A] a first light source and a second light source; [B] a first filter and a first polarizer; [C] a first camera and a second camera; and [D] at least one machine-readable medium having data stored thereon that, if used by at least one machine, causes the at least one machine to perform a method comprising: [D][i] simultaneously illuminating: (a) a blood flow with a first light from the first light source, and (b) a tissue with a second light from a second light source, wherein: (c)(i) the first light source is a coherent light source and the first light has a first wavelength, and (c)(ii) the second light source is a white light source and the second light has one or more wavelengths between 350 nm and 850 nm; [D][ii] in response to illuminating the blood flow with the first light, (a) filtering backscattered light from the blood flow with a first filter configured to pass the first wavelength, and (b) polarizing the backscattered light with a first polarizer; [D][iii] in response to filtering and polarizing the backscattered light and recording a raw laser speckle image with the first camera; [D][iv] in response to illuminating the tissue with the second light, recording a white light image with the second camera; [D][v] deriving a laser speckle contrast image from the raw laser speckle image, wherein: (a) the laser speckle contrast image is based on a sliding pixel window, and (b) the laser speckle contrast image has a laser speckle contrast value between a predetermined minimum speckle contrast value greater than zero and a predetermined maximum speckle contrast value; [D][vi] spatially registering the laser speckle contrast image and the white light image with each other; [D][vii] in response to spatially registering the laser speckle contrast image with the white light image, overlaying the laser speckle contrast image with the white light image to generate a corresponding continuous red, green, blue (RGB) image stream depicting the blood flow of the overlaid tissue; [D][viii] outputting the continuous RBG image stream depicting the blood flow of the overlaid tissue as a video stream, wherein the video stream has a duration greater than 0.5 seconds and is continuous.

[0187] Example 36. A blood flow visualization system comprising: [A] a first light source and a second light source, wherein: (a) the first light source is a coherent light source that emits first light having a first wavelength, and (b) the second light source is a white light source that emits second light having one or more wavelengths between 350 nm and 850 nm; [B] a first filter and a first polarizer; [C] a first camera and a second camera; and [D] at least one machine-readable medium having data stored thereon that, if used by at least one machine, causes the at least one machine to perform a method comprising: [D][i] in response to illuminating blood flow with the first light and illuminating tissue with the second light, recording a raw laser speckle image with the first camera and recording a white light image with the second camera; [D][ii] [D] deriving a laser speckle contrast image from the raw laser speckle image, wherein: (a) the laser speckle contrast image is based on a sliding pixel window, and (b) the laser speckle contrast image has a laser speckle contrast value between a predetermined minimum speckle contrast value greater than zero and a predetermined maximum speckle contrast value; [D] [iii] spatially registering the laser speckle contrast image and the white light image with each other; [D] [iv] in response to spatially registering the laser speckle contrast image with the white light image, overlaying the laser speckle contrast image with the white light image to generate a corresponding continuous red, green, blue (RGB) image stream depicting the blood flow of the overlaid tissue; [D] [v] outputting the continuous RBG image stream depicting the blood flow of the overlaid tissue as a video stream, wherein the video stream has a duration greater than 0.5 seconds and is continuous.

[0188] Example 37. A system according to Example 35 or 36, wherein the at least one machine-readable medium has data stored thereon, which, if used by the at least one machine, causes the at least one machine to perform a method comprising outputting the video stream in real time while illuminating the blood flow and the tissue.

[0189] Example 38. A system according to any of Examples 35 to 37, wherein the spatially registered laser speckle contrast image and white light image are based on an affine transformation.

[0190] Example 39. A system according to any of Examples 35 to 38, wherein the second camera is included in one of a surgical microscope, an endoscope, an exoscope, and a robotic surgical platform.

[0191] Example 40. A system according to any one of Examples 35 to 39, wherein the video stream includes a field of view greater than 5 mm x 5 mm.

[0192] Example 41. A system according to any one of Examples 35 to 40, wherein: [A] in response to the laser speckle contrast image having a laser speckle contrast value between a predetermined minimum speckle contrast value and a predetermined maximum speckle contrast value, the video stream includes a blood flow greater than a minimum blood flow, and the minimum blood flow is greater than or equal to zero and less than a maximum blood flow; [B] in response to the laser speckle contrast image having a laser speckle contrast value between a predetermined minimum speckle contrast value and a predetermined maximum speckle contrast value, the video stream does not include a blood flow less than the minimum blood flow or greater than the maximum blood flow.

[0193] Example 42. A system according to any one of Examples 35 to 41, comprising a second filter and a second polarizer; wherein the second filter is configured to pass the one or more wavelengths between 350 nm and 850 nm, and the second polarizer is configured to polarize the reflected white light reflected from the tissue with the second polarizer.

[0194] Example 43. A system according to any of Examples 35 to 42, wherein the first filter is configured to block one or more wavelengths of the second light between 350 nm and 850 nm.

[0195] Example 44. A system according to any one of Examples 35 to 43, wherein the first light source and the second light source are fixedly coupled to each other to move in tandem with one another in response to user manipulation of the first light source and the second light source.

[0196] Example 45. A system according to any one of Examples 35 to 44, wherein the at least one machine-readable medium has data stored thereon that, if used by the at least one machine, causes the at least one machine to perform a method comprising applying a color map to the laser speckle contrast image.

[0197] Example 46. A system according to any one of Examples 35 to 45, wherein the at least one machine-readable medium has data stored thereon, and if the data is used by the at least one machine, the data causes the at least one machine to perform a method comprising spatially registering the laser speckle contrast image and the white light image with each other based on a lookup table, wherein the lookup table maps pixels of the laser speckle contrast image and the white light image to each other.

[0198] Example 47. A system according to any one of Examples 35 to 46, wherein the at least one machine-readable medium has data stored thereon, which, if used by the at least one machine, causes the at least one machine to perform a method comprising: [A] separating the laser speckle contrast image having a laser speckle contrast value between the predetermined minimum speckle contrast value and the predetermined maximum speckle contrast value from the laser speckle contrast image not having a laser speckle contrast value between the predetermined minimum speckle contrast value and the predetermined maximum speckle contrast value; and [B] in response to separating the laser speckle contrast image, spatially aligning the laser speckle contrast image and the white light image with each other.

[0199] Example 48. A system according to any one of Examples 35 to 47, wherein the at least one machine-readable medium has data stored thereon that, if used by the at least one machine, causes the at least one machine to perform a method comprising, in response to spatially registering the laser speckle contrast image and the white light image with each other, separating the laser speckle contrast image having a laser speckle contrast value between the predetermined minimum speckle contrast value and the predetermined maximum speckle contrast value from the laser speckle contrast image not having a laser speckle contrast value between the predetermined minimum speckle contrast value and the predetermined maximum speckle contrast value.

[0200] Example 49. A system according to any one of Examples 35 to 48, wherein the at least one machine-readable medium has data stored thereon, and if the data is used by the at least one machine, the data causes the at least one machine to perform a method comprising simultaneously performing fluorescence imaging and laser speckle contrast imaging, wherein the laser speckle contrast image is based on the laser speckle contrast imaging.

[0201] Example 50. The system of Example 49, wherein the at least one machine-readable medium has data stored thereon that, if used by the at least one machine, causes the at least one machine to perform a method comprising simultaneously recording the raw laser speckle image with the first camera, the white light image with the second camera, and the fluorescence image with a third camera.

[0202] Example 51. A system according to Example 49 or 50, wherein the at least one machine-readable medium has data stored thereon, and if the data is used by the at least one machine, the data causes the at least one machine to perform a method comprising spatially aligning the laser speckle contrast image, the white light image, and the fluorescence image with each other.

[0203] Example 52. A system according to any one of Examples 35 to 51, wherein the at least one machine-readable medium has data stored thereon, and if the data is used by the at least one machine, the data causes the at least one machine to perform a method comprising simultaneously performing multispectral reflectance imaging (MSRI) and laser speckle contrast imaging, wherein the laser speckle contrast image is based on the laser speckle contrast imaging.

[0204] Example 53. The system of any one of Examples 35 to 52, wherein the at least one machine-readable medium has data stored thereon that, if used by the at least one machine, causes the at least one machine to perform a method comprising simultaneously performing hyperspectral imaging and laser speckle contrast imaging, wherein the laser speckle contrast image is based on the laser speckle contrast imaging.

[0205] Example 54. A system according to any one of Examples 35 to 53, wherein the video stream includes RBG images recording blood flow cessation caused by surgical intervention.

[0206] Example 55. The system of any of Examples 35 to 54, wherein the at least one machine-readable medium has data stored thereon that, if used by the at least one machine, causes the at least one machine to perform a method comprising determining a transparency level of the laser speckle contrast image, the laser speckle contrast image having a laser speckle contrast value between the predetermined minimum speckle contrast value and the predetermined maximum speckle contrast value.

[0207] Example 56. A system according to any one of Examples 35 to 55, wherein the laser speckle contrast image is a spatial laser speckle contrast image.

[0208] Example 57. At least one machine-readable medium having data stored thereon, which, if used by at least one machine, causes the at least one machine to perform a method comprising: [A] determining a laser speckle contrast imaging (LSCI) image of blood flow; [B] applying a threshold to the LSCI image to separate a first LSCI image from a second LSCI image, wherein the first LSCI image corresponds to a higher level of blood flow than the second LSCI image; [C] applying a pseudo color to the first LSCI image; and [D] superimposing the first LSCI image with a white light image acquired simultaneously with the speckle image corresponding to the first LSCI image.

[0209] Example 58. A method for visualizing blood flow, comprising: [A] receiving a laser speckle contrast imaging (LSCI) image of blood flow; [B] receiving a white light image of tissue, wherein the white light image captures anatomical structure; [C] registering the LSCI image and the white light image with each other; [D] superimposing the registered LSCI image and the white light image; and [E] generating display data that continuously depicts the blood flow of the superimposed tissue, wherein the display data includes the registered LSCI image and the white light image.

[0210] Example 59. A method according to Example 57 or 58, wherein the display data continuously depicts the blood flow superimposed on the tissue in real time during the surgical procedure.

[0211] Example 60. The method of any one of Examples 57 to 59, further comprising displaying the display data on a display device.

[0212] Example 61. A method according to any one of Examples 57 to 60, wherein the tissue includes a vasculature.

[0213] Example 62. A method according to any one of Examples 57 to 61, wherein the tissue is brain tissue.

[0214] Example 63. A method according to any one of Examples 57 to 62, wherein the step of aligning the LSCI image and the white light image with each other includes creating a lookup table based on a spatial transformation for aligning the LSCI image and the white light image.

[0215] Example 64. A method according to any one of Examples 57 to 63, wherein the step of superimposing the registered LSCI image and the white light image includes using the lookup table to map corresponding pixels from the LSCI image to corresponding pixels from the white light image.

[0216] Example 65. A method according to any one of Examples 57 to 64, wherein the step of superimposing the aligned LSCI image and the white light image further includes contrast stretching the LSCI image, mapping the LSCI image to an n-bit color map, and performing a weighted sum with the white light image.

[0217] Example 66. At least one non-transitory machine-readable medium comprising a plurality of instructions that, in response to being executed on a computing device, cause the computing device to perform the method of any one of Examples 57 to 65.

[0218] Example 67. A system for visualizing blood flow, comprising: [A] a first light source and a second light source, the first light source being configured to illuminate the blood flow and the second light source being configured to illuminate tissue with white light; [B] a first camera and a second camera, wherein the first camera is configured to record a raw laser speckle image of the blood flow and the second camera is configured to record a white light image of the tissue; and [C] a computing device comprising a processor and a memory having computer-executable instructions stored thereon, the computer-executable instructions, when executed by the processor The processor is caused to: [C][i] receive the raw laser speckle image of the blood flow; [C][ii] derive a laser speckle contrast imaging (LSCI) image; [C][iii] receive the white light image of the tissue, the white light image capturing anatomical structure; [C][iv] register the LSCI image and the white light image with each other; [C][v] overlay the registered LSCI image and white light image; and [C][vi] generate display data continuously depicting the blood flow of the tissue that is overlaid, wherein the display data includes the registered LSCI image and white light image.

[0219] Example 68. A system according to Example 67, wherein the system is a surgical microscope, an endoscope, an exoscope, or a robotic surgical platform.

[0220] Example 69. A method comprising: performing the blood flow visualization method of any one of Examples 57 to 65; and continuously monitoring the blood flow superimposed on the tissue during a surgical procedure.

[0221] Example 70. The method of Example 69, wherein the surgical procedure is brain surgery.

[0222] Example 71. The method of Example 69, wherein the surgical procedure is cerebral aneurysm clipping.

[0223] Example 72. The method of Example 69, wherein the surgical procedure is arteriovenous malformation (AVM) resection.

[0224] Example 73. A blood flow visualization system comprising: a first light source; a first filter and a first polarizer; a first camera; and at least one machine-readable medium having data stored thereon, the at least one machine-readable medium having data that, if used by at least one machine, causes the at least one machine to perform a method comprising: illuminating a blood flow with first light from the first light source, wherein the first light source is a coherent light source and the first light has a first wavelength; in response to illuminating the blood flow with the first light, (a) filtering backscattered light from the blood flow with a first filter configured to pass the first wavelength, and (b) polarizing the backscattered light with the first polarizer; in response to filtering and polarizing the backscattered light, recording a raw laser speckle image with the first camera; receiving a laser speckle image from a second camera a laser speckle contrast image derived from the raw laser speckle image, wherein: (a) the laser speckle contrast image is based on a sliding pixel window, and (b) the laser speckle contrast image has a laser speckle contrast value between a predetermined minimum speckle contrast value greater than zero and a predetermined maximum speckle contrast value; spatially registering the laser speckle contrast image and the white light image with each other; in response to spatially registering the laser speckle contrast image with the white light image, overlaying the laser speckle contrast image with the white light image to generate a corresponding continuous red, green, blue (RGB) image stream depicting the blood flow of the overlaid tissue; and outputting the continuous RBG image stream depicting the blood flow of the overlaid tissue as a video stream, wherein the video stream has a duration greater than 0.5 seconds and is continuous.

[0225] Example 74. A blood flow visualization system comprising: a first light source for illuminating a blood flow with a first light, wherein the first light source is a coherent light source and the first light has a first wavelength; a first filter and a first polarizer, wherein the first filter and the first polarizer are respectively used to (a) filter backscattered light from the blood flow with the first filter configured to pass the first wavelength, and (b) polarize the backscattered light with the first polarizer; a first camera; and at least one machine-readable medium having data stored thereon, which, if used by at least one machine, causes the at least one machine to perform a method comprising: recording a raw laser speckle image with the first camera in response to filtering and polarizing the backscattered light; receiving a laser speckle image from a second camera; a laser speckle contrast image derived from the raw laser speckle image, wherein: (a) the laser speckle contrast image is based on a sliding pixel window, and (b) the laser speckle contrast image has a laser speckle contrast value between a predetermined minimum speckle contrast value greater than zero and a predetermined maximum speckle contrast value; spatially registering the laser speckle contrast image and the white light image with each other; in response to spatially registering the laser speckle contrast image with the white light image, overlaying the laser speckle contrast image with the white light image to generate a corresponding continuous red, green, blue (RGB) image stream depicting the blood flow of the overlaid tissue; and outputting the continuous RBG image stream depicting the blood flow of the overlaid tissue as a video stream, wherein the video stream has a duration greater than 0.5 seconds and is continuous.

Claims

1. A method for visualizing blood flow, the method comprising: Obtain laser speckle contrast imaging (LSCI) images of blood flow; obtaining a white light image of tissue that captures the anatomy of the subject in a region associated with the LSCI image of the blood flow; spatially registering the LSCI image and the white light image with each other; Superimpose spatially registered LSCI images and white light images; as well as Display data continuously depicting the blood flow superimposed on the tissue is generated, wherein the display data includes the spatially registered LSCI image and white light image.

2. The method of claim 1, wherein the display data continuously depicts the blood flow superimposed on the tissue in real time during a surgical procedure. The method according to claim 1 , further comprising displaying the display data on a user interface.

4. The method of any one of claims 1 to 3, wherein the tissue comprises vasculature.

5. The method according to any one of claims 1 to 3, wherein the tissue is brain tissue.

6. The method of any one of claims 1 to 5, wherein spatially registering the LSCI image and the white-light image with each other comprises creating a lookup table based on a spatial transformation for registering the LSCI image and the white-light image.

7. The method of claim 6, wherein superimposing the spatially registered LSCI image and white light image comprises using the lookup table to map corresponding pixels from the LSCI image to corresponding pixels from the white light image.

8. The method of claim 7, wherein superimposing the spatially registered LSCI image and white light image further comprises contrast stretching the LSCI image, mapping the LSCI image to an n-bit color map, and performing a weighted sum with the white light image.

9. A system for blood flow visualization, the system comprising: a first light source configured to illuminate blood flow at a target area of ​​a subject; a first camera configured to record a raw laser speckle image of the blood flow; as well as A computing device comprising a processor and a memory having instructions stored thereon that, when executed by the processor, cause the computing device to: obtaining the original laser speckle image of the blood flow via the first camera; deriving a laser speckle contrast imaging (LSCI) image from the original laser speckle image; obtaining a white light image of tissue at the target area of ​​the subject, the white light image capturing anatomical structure; spatially registering the LSCI image and the white light image with each other; Superimpose spatially registered LSCI images and white light images; as well as Display data continuously depicting the blood flow superimposed on the tissue is generated, wherein the display data includes the spatially registered LSCI image and white light image.

10. The system of claim 9, wherein the system is a surgical microscope, an endoscope, an exoscope, a robotic surgical platform, a stand-alone imaging system, or a system dedicated to blood flow imaging.

11. The system of claim 9 or 10, wherein the display data continuously depicts the blood flow superimposed on the tissue in real time during a surgical procedure.

12. The system of any one of claims 9 to 11, wherein the instructions further cause the computing device to present the display data on a user interface.

13. The system of any one of claims 9 to 12, wherein the tissue comprises vasculature.

14. The system according to any one of claims 9 to 13, wherein the tissue is brain tissue.

15. The system of any one of claims 9 to 14, wherein spatially registering the LSCI image and the white-light image to each other comprises creating a lookup table based on a spatial transformation for registering the LSCI image and the white-light image.

16. The system of claim 15, wherein superimposing the spatially registered LSCI image and white light image comprises using the lookup table to map corresponding pixels from the LSCI image to corresponding pixels from the white light image.

17. The system of claim 16, wherein superimposing the spatially registered LSCI image and white light image further comprises contrast stretching the LSCI image, mapping the LSCI image to an n-bit color map, and performing a weighted sum with the white light image.

18. A method for visualizing blood flow, the method comprising successively: capturing a laser speckle contrast imaging (LSCI) image of blood flow in the subject using a first image capture device; capturing a white light image of the tissue using a second image capture device, the white light image capturing the anatomical structure; Co-registering the LSCI image and the white light image; Superimpose the co-registered LSCI image and white light image; as well as The superimposed and co-registered LSCI image and white light image are displayed via a user interface.

19. The method of claim 18, wherein the tissue comprises vasculature or brain tissue.

20. The method of claim 18 or 19, wherein co-registering the LSCI image and the white-light image with each other comprises creating a lookup table based on a spatial transformation for registering the LSCI image and the white-light image.

Images