An information-providing apparatus and method for generating pulse-compressed ultrafast Doppler images.

Abstract

The present invention provides an information-providing device and method for generating improved ultrafast Doppler images. [Solution] The information providing device may include a processor that transmits an ultrafast ultrasonic signal designed according to the transmission mode to a target region and receives the reflected signal, compresses the pulses of the reflected signal using a decoding filter according to the transmission mode, obtains an image by reconstructing the compressed signal through dynamic beamforming, removes fixed tissue signals in the image using a clutter filter, and inversely compensates for displacements estimated by motion tracking to the region of interest in the image, including dynamic blood flow signals, thereby generating a pulse-compressed ultrafast Doppler image.

Description

[Technical Field]

[0001] The present invention relates to an information providing device and method for generating pulse-compressed ultrafast Doppler images. [Background technology]

[0002] Diabetes affected approximately 537 million adults in 2021, and because untreated diabetes can lead to serious complications, 240 million undiagnosed individuals are at life-threatening risk. Chronic kidney disease (CKD), particularly diabetic nephropathy, accounts for 27.8% of diabetic complications, is the leading cause of death in diabetic patients, and causes irreversible kidney damage requiring lifelong dialysis or kidney transplantation. Therefore, preserving kidney function before it deteriorates is paramount. To assess kidney function, current clinical practice measures or estimates the glomerular filtration rate (GFR), which is the degree to which waste products are removed from blood or urine samples. Since the glomerular filtration rate is an indicator of delayed kidney damage, it is not easy to take preventive measures or early intervention until signs are detected. Furthermore, anemia symptoms in patients with chronic kidney disease who have lost 20-50% of their kidney function become more severe as kidney function deteriorates, and blood sampling is burdensome for most severely ill patients.

[0003] On the other hand, since renal filtration is primarily driven by microcirculation within the glomeruli, non-invasive imaging of renal microcirculation can serve as a leading indicator to detect kidney damage and prevent significant functional loss.

[0004] Existing clinical angiography techniques have limitations in visualizing the microcirculation of the kidney. Both computed tomography angiography (CTA) and magnetic resonance angiography (MRA) have limited spatiotemporal resolution and are not suitable for identifying delicate interlobular vessels, nor are they sensitive to microvascular hemodynamics. Moreover, CTA and MRA contrast agents are contraindicated in patients with chronic kidney disease and kidney damage because residual contrast agents may contribute to contrast-induced nephropathy or renal fibrosis.

[0005] Doppler ultrasound imaging can visualize the time-varying renal hemodynamics without contrast agents. However, while existing Doppler ultrasound images capture major blood flow, they lack sufficient sequential samples for blood flow estimation, resulting in inadequate contrast with slower microvascular flow.

[0006] Ultrafast Doppler imaging (UFD) overcomes these barriers, significantly increasing the sample size to ultrafast scales (e.g., 6,667 Hz pulse repetition frequency (PRF) for a depth of 100 mm) through accelerated frame acquisition, enabling the revelation of microvessel contrasts at a scale of less than 1 mm. Leveraging these advantages, it has been discovered that ultrafast Doppler imaging can be used to investigate a wide range of pathological vascular changes in organs such as the brain, myocardium, and liver.

[0007] Nevertheless, while existing ultrafast Doppler imaging is promising for visualizing human microvessels, imaging organs located deep within the body, such as the kidneys, remains challenging. Generally, ultrafast Doppler imaging techniques transmit plane waves to accelerate frame acquisition, but the lack of focus and low acoustic pressure result in weak echo signals. Furthermore, implementing high-frequency ultrasonic transducers to improve spatial resolution leads to significant tissue attenuation, limiting the penetration depth.

[0008] Therefore, existing ultrafast Doppler imaging techniques must compromise with low spatial resolution, either by using low-frequency ultrasound transducers due to relatively shallow penetration depths or by involving invasive procedures such as surgical incisions or ultrasound contrast injections. While this allows for increased transmitted acoustic power, it is limited in terms of acoustic radiation safety to prevent tissue damage. Thus, there is a pressing need for the development of new ultrafast Doppler imaging methods that can non-invasively image the entire human kidney with the highest resolution and signal-to-noise ratios (SNRs). [Overview of the Initiative] [Problems that the invention aims to solve]

[0009] The object of the present invention is to provide an information-providing device and method for generating improved ultrafast Doppler images.

[0010] The object of the present invention is to provide an information-providing device and method for evaluating ultrafast Doppler images that can replace existing diagnostic methods for chronic kidney disease that depend on glomerular filtration rate.

[0011] The objectives of the present invention are not limited to those mentioned above, and any other objectives not mentioned can be clearly understood by a person ordinary in the art to which the present invention pertains from the following description. [Means for solving the problem]

[0012] According to one aspect of the present invention, an information-providing device is provided that includes a processor that transmits an ultrafast ultrasonic signal designed according to a transmission mode to a target region, receives the reflected signal, compresses the pulses of the reflected signal using a decoding filter according to the transmission mode, obtains an image by reconstructing the compressed signal through dynamic beamforming, removes fixed tissue signals in the image using a clutter filter, and inversely compensates for displacements estimated by motion tracking to the region of interest in the image, including dynamic blood flow signals, thereby generating a pulse-compressed ultrafast Doppler image.

[0013] The processor can evaluate the pulse-compressed ultrafast Doppler image using hemodynamic parameters relating to vascular area and perfusion, and vascular skeletal parameters relating to vascular density and vascular curvature.

[0014] The processor can identify hemodynamic parameters relating to vascular area based on the area of ​​the target region and the vascular area.

[0015] The processor can identify hemodynamic parameters related to perfusion based on the area of ​​the target region and the intensity of the dynamic blood flow signal.

[0016] The processor can identify vascular skeletal-mediated variables relating to vascular density based on the area and number of vascular branches of the target region.

[0017] The processor can identify vascular skeletal parameters relating to vascular curvature based on the linear distance between the two ends of the blood vessel and the length of each vascular branch.

[0018] The aforementioned transmission mode may be barker mode or golay mode.

[0019] The processor can compress the pulses of the reflected signal by utilizing a decoding filter designed to remove the side lobes of the reflected signal in the Barker mode.

[0020] The processor can compress the pulses of the reflected signal by utilizing a decoding filter designed in the opposite phase of the ultrafast ultrasonic signal in the Goray mode.

[0021] The processor may include a sequence unit that defines detailed parameters necessary to generate the pulse-compressed ultra-high-speed Doppler image and constructs an event sequence that operates step by step; and a kernel unit in which kernel functions defined to process the event sequence generated in the sequence are configured in parallel.

[0022] An information providing method performed by an information providing apparatus according to an embodiment of the present invention includes: transmitting an ultra-high-speed ultrasonic signal designed according to a transmission mode to a target area and receiving a reflected signal that is reflected; compressing the pulse of the reflected signal using a decoding filter according to the transmission mode; obtaining an image in which the compressed signal is reconstructed through dynamic beamforming; removing fixed tissue signals in the image using a clutter filter; and generating a pulse-compressed ultra-high-speed Doppler image by compensating in reverse the estimated displacement by motion tracking for an area of interest in the image including a dynamic blood flow signal.

[0023] The information providing method may further include evaluating the pulse-compressed ultra-high-speed Doppler image using hemodynamic mediator variables related to vascular area and perfusion and vascular skeleton mediator variables related to vascular density and vascular tortuosity.

[0024] The step of evaluating the pulse-compressed ultra-high-speed Doppler image may include identifying a hemodynamic mediator variable related to vascular area based on the area of the target area and the vascular area.

[0025] The step of evaluating the pulse-compressed ultra-high-speed Doppler image may include identifying a hemodynamic mediator variable related to perfusion based on the area of the target area and the intensity of the dynamic blood flow signal.

[0026] The step of evaluating the pulse-compressed ultra-high-speed Doppler image may include identifying a vascular skeleton mediator variable related to vascular density based on the area of the target area and the number of vascular branches.

[0027] The step of evaluating the pulse-compressed ultrafast Doppler image may include identifying vascular skeletal parameters relating to vascular curvature based on the linear distance between the two ends of the vessel and the length of each vascular branch.

[0028] The step of compressing the pulses of the reflected signal may include a step of compressing the pulses of the reflected signal using a decoding filter designed to remove the side lobes of the reflected signal in the Barker mode.

[0029] The step of compressing the pulses of the reflected signal may include, in the Goley mode, a step of compressing the pulses of the reflected signal using a decoding filter designed in the opposite phase to the ultrafast ultrasonic signal. [Effects of the Invention]

[0030] An information-providing device according to one embodiment of the present invention effectively improves the penetration depth and signal-to-noise ratio of ultrafast Doppler images, overcoming tissue attenuation and enabling high-contrast and high-resolution imaging of complex microvessels in deep organs.

[0031] According to one embodiment of the present invention, it is possible to demonstrate pulse-compressed ultrafast Doppler imaging that effectively expands the image depth for deep organ images and improves microvascular flow sensitivity.

[0032] According to one embodiment of the present invention, pulse compression technology can restore long encoded pulses into short pulses and transmit high-energy pulses, resulting in a significant improvement in image depth and microvessel sensitivity beyond the hardware limitations.

[0033] According to one embodiment of the present invention, monitoring decreased blood flow circulation using pulse-compressed ultrafast Doppler images can predict kidney dysfunction due to various complications, and can be widely applied to deep organs other than the kidneys.

[0034] The effects of the present invention are not limited to those described above, but should be understood to include all effects that can be inferred from the configuration of the invention as described in the detailed description or claims. [Brief explanation of the drawing]

[0035] [Figure 1] This is a schematic diagram illustrating an information provision system according to one embodiment of the present invention. [Figure 2] This is a block diagram illustrating the configuration of an information providing device according to one embodiment of the present invention. [Figure 3] This is a diagram illustrating the operation flowchart of an information providing device according to one embodiment of the present invention. [Figure 4] This is a diagram illustrating an ultrafast ultrasonic signal according to one embodiment of the present invention. [Figure 5] This is a diagram illustrating the pulse compression process according to one embodiment of the present invention. [Figure 6] This diagram illustrates the application of a decoding filter in Barker mode according to one embodiment of the present invention. [Figure 7] This is a diagram illustrating how a pulse-compressed ultrafast Doppler image is obtained according to one embodiment of the present invention. [Figure 8] This is a diagram illustrating the operation flowchart of an information providing device according to one embodiment of the present invention. [Figure 9] An example of evaluating pulse-compressed ultrafast Doppler images according to one embodiment of the present invention will be described. [Figure 10] This diagram compares the characteristics of an existing Doppler image with a pulse-compressed ultrafast Doppler image according to one embodiment of the present invention. [Figure 11] This diagram compares existing Doppler images of different locations in deep organs with pulse-compressed ultrafast Doppler images according to one embodiment of the present invention. [Figure 12] This diagram compares existing Doppler images with pulse-compressed ultrafast Doppler images according to one embodiment of the present invention for the left and right portions of deep organs. [Modes for carrying out the invention]

[0036] Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings. The detailed description disclosed below, together with the accompanying drawings, is intended to describe exemplary embodiments of the present invention and is not intended to show only the possible embodiments of the present invention. Parts not relevant to the description may be omitted in order to clearly illustrate the present invention in the drawings, and the same reference numerals may be used throughout the specification for identical or similar components.

[0037] Words and terms used in this specification and claims should not be interpreted restrictively in their usual or dictionary sense, but rather in a sense and concept consistent with the technical idea of ​​the present invention, in accordance with the principle that inventors may define terms and concepts in order to best describe their invention.

[0038] Therefore, the embodiments described herein and the configurations illustrated in the drawings constitute preferred embodiments of the present invention and do not represent the entire technical concept of the present invention; thus, there may be various equivalents and modifications that can be substituted for these configurations at the time of filing of the present invention.

[0039] In this specification, terms such as “includes” or “having” are intended to describe the presence of features, figures, stages, operations, components, parts, or combinations thereof as described in the specification, and should be understood not to preemptively exclude the possibility of the presence or addition of one or more other features, figures, stages, operations, components, parts, or combinations thereof.

[0040] Figure 1 is a schematic diagram illustrating an information provision system according to one embodiment of the present invention.

[0041] An information provision system according to one embodiment of the present invention is a system 1 (hereinafter also referred to as system 1) that generates pulse-compressed ultrafast Doppler imaging (PC-UFD). In this case, the information provision system 1 according to one embodiment of the present invention may include an ultrasonic device 10 and an information provision device 100.

[0042] According to one embodiment of the present invention, the ultrasonic device 10 is a device that sends an ultrasonic signal to a target area through a transducer and then receives the reflected signal that returns. The ultrasonic device 10 can operate in multiple modes, for example, the basic mode B mode (brightness mode), the Doppler mode which utilizes the Doppler effect, etc.

[0043] At this time, Doppler mode has two types: color Doppler mode, which can indicate the direction of blood flow with hue and the speed of blood flow with brightness, and power Doppler mode, which can indicate blood flow even more sensitively than color Doppler mode.

[0044] While various ultrasonic devices known to the public can be used, a detailed explanation of them will be omitted.

[0045] According to one embodiment of the present invention, the information providing device 100 is connected to the ultrasonic device 10 by wired / wireless communication to receive reflected signals, and can generate ultrasonic images in real time and provide them to the user.

[0046] According to one embodiment of the present invention, the information providing device 100 is a device that generates pulse-compressed ultrafast Doppler images, and can be implemented in a computer, server, smartphone, tablet PC, smart pad, notebook computer, etc. In this case, the information provided by the information providing device in one embodiment of the present invention may be pulse-compressed ultrafast Doppler image information, but is not limited thereto.

[0047] In one embodiment of the present invention, the ultrasonic device 10 and the information providing device 100 may be implemented as separate devices, or they may be implemented as a single device; the form of implementation is not limited to just one of these.

[0048] As mentioned above, ultrafast Doppler imaging technology has been introduced for measuring micro-blood flow, but there are still limitations to imaging the micro-blood flow in organs located deep within the body.

[0049] An information-providing device according to one embodiment of the present invention utilizes pulse compression techniques to effectively improve the penetration depth and signal-to-noise ratio of ultrafast Doppler images, overcoming the resolution and hardware limitations, and enabling high-contrast and high-resolution imaging of complex microvessels in deep organs by overcoming tissue attenuation.

[0050] The configuration and operation of an information-providing device according to one embodiment of the present invention will be described in detail below with reference to the drawings.

[0051] Figure 2 is a block diagram illustrating the configuration of an information providing device according to one embodiment of the present invention.

[0052] An information providing device 100 according to one embodiment of the present invention includes an input unit 110, a communication unit 120, a display unit 130, a storage unit 140, and a processor 150.

[0053] The input unit 110 generates input data in response to user input to the information providing device 100. For example, user input may be user input to start the operation of the information providing device 100, but it can also be applied without limitation to any other user input necessary for generating pulse-compressed ultrafast Doppler images and evaluating the generated images.

[0054] The input unit 110 includes at least one input means. The input unit 110 may include a keyboard, keypad, dome switch, touch panel, touch key, mouse, menu button, etc.

[0055] The communication unit 120 communicates with external devices such as the ultrasound device 10 and a server in order to send and receive ultra-high-speed ultrasound signals, reflected signals, clutter filters, tissue signals, blood flow signals, pulse-compressed ultra-high-speed Doppler images, etc.

[0056] Specifically, the communication unit 120 can perform PCIe (PCI express) communication (6.6 GB / s) for high-bandwidth / high-capacity channel data transmission and reception. Typical interface specifications are, for example, 0.98 GB / s per lane* (maximum 16 lanes) for the 3rd generation standard, 1.97 GB / s per lane* (maximum 16 lanes) for the 4th generation standard, and 3.94 GB / s per lane* (maximum 16 lanes) for the 5th generation standard. In this case, USB specifications are 0.64 GB / s for the 3.2-1st generation standard, 1.28 GB / s for the 3.2-2nd generation standard, 2.56 GB / s per lane for the 3.2-2X2 generation standard, and 2.56~5.12 GB / s for the 4-v1.0 standard.

[0057] In addition, the communication unit 120 can perform wireless communication such as 5G (5th generation communication), LTE-A (long term evolution-advanced), LTE (long term evolution), Wi-Fi (wireless fidelity), and Bluetooth (registered trademark).

[0058] The display unit 130 displays display data generated by the operation of the information providing device 100. The display unit 130 can display a screen showing pulse-compressed ultrafast Doppler images, a screen showing evaluation information evaluating acquired images, a screen for receiving user input, and so on.

[0059] The display unit 130 includes liquid crystal displays (LCDs), light-emitting diode (LED) displays, organic light-emitting diode (OLED) displays, micro-electro-mechanical systems (MEMS) displays, and electronic paper displays. The display unit 130 can be combined with the input unit 110 to be implemented as a touchscreen.

[0060] The storage unit 140 stores the operating program for the information providing device 100. The storage unit 140 includes non-volatile storage that can store data (information) regardless of whether power is supplied, and volatile memory where data is loaded for processing by the processor 150 and data cannot be stored unless power is supplied. Storage can be flash memory, HDD (hard-disc drive), SSD (solid-state drive), ROM (Read Only Memory), etc., and memory can be a buffer, RAM (Random Access Memory), etc.

[0061] The storage unit 140 can store ultrafast ultrasound signals, reflected signals, clutter filters, tissue signals, blood flow signals, pulse-compressed ultrafast Doppler images, and the like. The storage unit 140 can also store calculation programs necessary for the process of performing pulse compression, image reconstruction, tissue signal removal, motion tracking, generation of pulse-compressed ultrafast Doppler images, identification of hemodynamic parameters, identification of vascular and skeletal parameters, and the like.

[0062] The processor 150 can execute software such as programs to control at least one other component of the information providing device 100 (e.g., hardware or software component), and can perform various data processing or calculations.

[0063] Since parallel computing is crucial in image processing, processor 150 can utilize multi-core computing devices such as server CPUs and GPUs.

[0064] Furthermore, the processor 150 can be divided into 1) a sequence section that constitutes the computation process and 2) a kernel section that executes the sequence like a function for a specific purpose.

[0065] In other words, the sequence unit can define the detailed parameters necessary to generate pulse-compressed ultrafast Doppler images and configure a step-by-step event sequence. Specifically, the sequence unit can configure the overall image processing flow step by step and utilize object-oriented programming languages ​​such as MATLAB, Python, or C++, which are convenient for macroscopic understanding and debugging of the entire image processing process.

[0066] The sequence unit predefines the detailed parameters necessary for the probe to be used, transmit / receive pulses, data buffer, and control of the ultrasound device, and can configure an event sequence that operates sequentially according to the ultrasound imaging stage-by-stage procedure. Each event can be divided into hardware events of the ultrasound device, such as ultrasound transmission / reception, and software events of the computing device, such as pulse compression, image reconstruction, and blood flow signal filtering. The actual processing performed by the software events can proceed to calls to kernel functions in the kernel unit.

[0067] The kernel section can consist of kernel functions configured in parallel to process the event sequences generated by the sequence. The programming code (script) processed by the kernel section is C++-based, which has high computational speed, and primarily uses parallel programming languages ​​such as Intel-SSE and Nvidia-CUDA. Each time it is called by an event in the sequence section, it can perform high-speed calculations using the input parameters passed to it, output the processing result, and repeat this process.

[0068] A processor 150 according to one embodiment of the present invention can transmit an ultrafast ultrasonic signal designed according to the transmission mode to a target region and receive the reflected signal, compress the pulses of the reflected signal using a decoding filter according to the transmission mode, acquire an image by reconstructing the compressed signal through dynamic beamforming, remove fixed tissue signals in the image using a clutter filter, and inversely compensate for displacements estimated by motion tracking for the region of interest in the image, including dynamic blood flow signals, thereby generating a pulse-compressed ultrafast Doppler image. At this time, the operations such as receiving each reflected signal, compressing the pulses of the reflected signal, acquiring a reconstructed image, removing fixed tissue signals, and creating a pulse-compressed ultrafast Doppler image including dynamic blood flow signals can be viewed as an event sequence configured by the sequence unit described above.

[0069] A processor 150 according to one embodiment of the present invention can evaluate the pulse-compressed ultrafast Doppler image using hemodynamic parameters relating to vascular area and perfusion, and vascular skeletal parameters relating to vascular density and vascular curvature.

[0070] On the other hand, the processor 150 can perform at least part of the data analysis, processing, and result information generation necessary to carry out the above operations by utilizing at least one of the following as rule-based or artificial intelligence algorithms: machine learning, neural networks, or deep learning algorithms. Examples of neural networks include models such as CNN (Convolutional Neural Network), DNN (Deep Neural Network), and RNN (Recurrent Neural Network).

[0071] Figure 3 is a diagram illustrating the operation flowchart of an information providing device according to one embodiment of the present invention.

[0072] A processor 150 according to one embodiment of the present invention can transmit an ultra-high-speed ultrasonic signal designed according to the transmission mode to a target region and receive the reflected signal (S10).

[0073] Ultra-high-speed ultrasonic signals are binary-coded signals depending on the transmission mode, which can be either barker mode or golay mode. Examples of ultra-high-speed ultrasonic signals in each mode are shown in Figure 4.

[0074] Ultrafast ultrasonic signals coded with Barker modes can be designed by combining Barker codes with fundamental wavelets. Ultrafast ultrasonic signals coded with Goley modes can be designed by combining Goley codes with fundamental wavelets, and in particular, can consist of two signal pairs with complementary codes.

[0075] In this case, Barker codes and Gorey codes can consist of various lengths (for example, in the case of Barker, codes with lengths of 2-bit, 3-bit, 4-bit, 5-bit, 7-bit, 11-bit, and 13-bit are known). However, the length of each code can be freely selected and is not limited to just one.

[0076] Barker mode offers better temporal resolution because it acquires more frames per unit of time than Goley mode. On the other hand, Goley mode has the advantage of easier pulse compression and a deeper contrast-to-noise ratio. Therefore, Barker mode or Goley mode can be selected depending on the target region.

[0077] The target region is the area where deep organs are located, and it refers to the area where we aim to visualize blood flow.

[0078] A processor 150 according to one embodiment of the present invention can compress the pulses of the reflected signal using a decoding filter according to the transmission mode (S20).

[0079] Pulse compression essentially involves 1D synthesis of each column of received channel data using a decoding filter. Through pulse compression, it is possible to improve the signal-to-noise ratio and image depth without increasing peak acoustic power.

[0080] Decoding filters can also be designed differently depending on the transmission mode, but in Barker mode, a mismatch filter based on an integrated sidelobe level minimization approach was adopted to suppress sidelobes generated during compression. Therefore, in Barker mode, the processor 150 can compress the pulses of the reflected signal using a decoding filter (also called a mismatch filter) designed to remove sidelobes from the reflected signal. An example of a mismatch filter adopted in Barker mode is shown in Figure 6.

[0081] On the other hand, in Goley mode, the reflected signals consist of complementary signal pairs, and the sidelobes automatically disappear when the two compressed channel data are summed. Therefore, in Goley mode, the processor 150 can compress the pulses of the reflected signals by using a decoding filter (also called a matching filter) designed in the opposite phase of the ultrafast ultrasonic signal. Specifically, in Goley mode, decoding can be performed using a complementary decoding filter pair corresponding to a complementary ultrafast ultrasonic signal pair. An example of a decoding filter is shown in Figure 5.

[0082] A processor 150 according to one embodiment of the present invention can acquire an image by reconstructing a compressed signal through dynamic beamforming (S30).

[0083] Dynamic beamforming can be implemented in a variety of ways, for example, by time-delay-based beamforming.

[0084] In time-delay-based beamforming, decoded channel data can be reconstructed with complex intensity data using a phase-rotation-based plane-wave composite beamformer. This method describes the time delay calculation of each transducer element for each acquisition event by inversely mapping pixel intensity and phase information through a back projection scheme. If signals compressed at different ultrasonic angles are acquired, each can be reconstructed individually and then accumulated to form a single in-phase / quadrature (IQ) intensity data frame. The beamforming is illustrated in Figure 7.

[0085] A processor 150 according to one embodiment of the present invention can remove image-fixed tissue signals using a clutter filter (S40).

[0086] Clutter filters designed to remove fixed tissue signals from reconstructed images and leave only dynamic blood signals can be implemented in various ways. For example, they can be implemented as singular value decomposition (SVD) based spatiotemporal clutter filters.

[0087] The frames of the image reconstructed through the S30 stage can consist of blood flow, tissue, and noise. When ranking the frames in order of common characteristics, consistently appearing tissue is ranked higher, followed by blood flow and then noise. Therefore, the singular value decomposition-based spatiotemporal clutter filter can identify eigenvalue thresholds based on inflection point estimation and distinguish between tissue signals and blood flow signals within a frame based on these thresholds.

[0088] To estimate the inflection point, the eigenvalues ​​are displayed on a logarithmic scale, and a linear plot is drawn connecting the first and last ranks. The inflection point can then be identified as the furthest point on the eigenvalue curve in this linear plot.

[0089] A processor 150 according to one embodiment of the present invention can generate a pulse-compressed ultrafast Doppler image by inversely compensating for the displacement estimated by motion tracking of a region of interest in the image that includes a dynamic blood flow signal (S50).

[0090] A region of interest can be set in the first frame of an image containing dynamic blood flow signals, and the same region of interest can be set in subsequent frames to estimate two-dimensional displacement. Such displacements are accumulated to calculate the cumulative displacement relative to the first frame, and each cumulative displacement can be compensated for with a negative number in the corresponding blood signal frame to stabilize the relative motion of the first frame.

[0091] The 2D motion was stabilized by inversely compensating for the displacement estimated in sequential frames, and as a result, the generated pulse-compressed ultrafast Doppler image can be sharper.

[0092] According to one embodiment of the present invention, pulse-compressed ultrafast Doppler imaging (PC-UFD) can be demonstrated, which effectively expands the image depth for deep organ images and improves microvascular flow sensitivity.

[0093] According to one embodiment of the present invention, pulse compression technology can restore long encoded pulses into short pulses and transmit high-energy pulses, resulting in a significant improvement in image depth and microvessel sensitivity beyond the hardware limitations.

[0094] Figure 4 is a diagram illustrating an ultrafast ultrasonic signal according to one embodiment of the present invention.

[0095] Figure 4 illustrates the process of acquiring ultrafast ultrasonic signals, as previously explained in relation to S10 in Figure 3.

[0096] For ultrafast ultrasonic signal acquisition, a plane wave beam can be transmitted at nine angles (-12°, -9°, -6°, -3°, 0°, +3°, +6°, +9°, +12°) and repeated at the maximum permissible pulse repetition frequency (PRF) at the desired imaging depth (e.g., 6,667 Hz for a depth of 80 mm). A single US ultrasonic frame can be constructed through the transmission and reception of the plane wave beam tuned at nine angles.

[0097] On the other hand, each pulse design can be designed using a programmable digital pulse waveform generator, which is essentially supported by the programmable ultrasonic device 10. The basic ultrasonic signal (standard) is a 5.2 MHz, two-half-period short ultrasonic pulse.

[0098] In this case, the number and angle of the plane wave beams, the pulse repetition frequency, and the conditions of the basic ultrasonic signal are not limited to the examples given above, and the same applies hereafter.

[0099] In Barker mode, the longest length is achieved, and the 13-bit Barker code, which provides the highest sidelobe suppression among known Barker codes, can be referenced for design. Ultrafast ultrasonic signals in Barker mode can be generated by combining a 13-bit binary Barker code with a basic wavelet (e.g., 1.5λ (0.45 μm)). Received channel data can be stored in a receive buffer pre-allocated by each transmission mode.

[0100] In Goley mode, the pairs of transmitted pulses are designed in a similar manner, but can be generated by combining the same basic wavelets and 16-bit binary Goley code used in Barker mode. Goley decoding requires two complementary sequence transmissions for each pulse lookup. This doubles the transmit-receive cycle duration compared to non-coded or Barker coding methods, and halves the pulse repetition frequency and frame rate to 3,333 Hz and 300 Hz, respectively.

[0101] Figure 5 is a diagram illustrating the pulse compression process according to one embodiment of the present invention.

[0102] Figure 5, as explained earlier in relation to S20 in Figure 3, specifically shows the reflected signals before and after pulse compression. Comparing the received reflected signals before and after pulse compression, it can be seen that the signal intensity after pulse compression is even stronger, indicating that image depth and microvessel sensitivity can be greatly improved beyond the hardware limits.

[0103] Figure 6 is a diagram illustrating the application of a Barker mode decoding filter according to one embodiment of the present invention.

[0104] As previously explained in relation to S20 in Figure 3, in Barker mode, a mismatch filter based on an integrated sidelobe level minimization approach was adopted to suppress the sidelobes generated during compression.

[0105] When an encoded ultrafast ultrasonic signal a in Barker mode is decoded through a matching filter b and a mismatch filter c, it can be seen that the signal d compressed by the matching filter b exhibits side lobes around the main signal. Conversely, the signal e compressed by the mismatch filter c, which minimizes the side lobe level, is found to have suppressed side lobes.

[0106] In fact, when images f and g are constructed using this signal, it can be seen that image g is even sharper.

[0107] Figure 7 is a diagram illustrating the process of acquiring a pulse-compressed ultrafast Doppler image according to one embodiment of the present invention.

[0108] Viewed from the left in Figure 7, the reflected signal can be compressed using a decoding filter and processed into an ultrasound intensity frame via dynamic beamforming. Subsequently, the stabilized blood signal can be filtered using spatiotemporal clutter filtering and 2D motion stabilization, and a microvascular image of the final deep organ can be generated through power aggregation.

[0109] The improved pulse-compressed ultrafast Doppler image in Figure 7 illustrates the complex renal vessels, particularly the interlobular vessels in the renal cortex that are less than 400 μm in diameter.

[0110] A pulse-compressed ultrafast Doppler image (PC-UFD) according to one embodiment of the present invention demonstrates that it is possible to visualize the entire renal blood vessel, distinguish cortical blood vessels smaller than 400 μm, and quantify their hemodynamic and morphological characteristics.

[0111] Figure 8 is a diagram illustrating the operation flowchart of an information providing device according to one embodiment of the present invention.

[0112] This diagram describes a method for generating and evaluating pulse-compressed ultrafast Doppler images.

[0113] A processor 150 according to one embodiment of the present invention can acquire a pulse-compressed ultrafast Doppler image (S810). The pulse-compressed ultrafast Doppler image may be an image acquired through the process described earlier with reference to Figure 3.

[0114] A processor 150 according to one embodiment of the present invention can identify hemodynamic parameters relating to vascular area based on the area of ​​the target region and the vascular area (S821).

[0115] The hemodynamic parameter relating to vascular area can be calculated using the following equation 1. On the other hand, when applied to 3D images, the hemodynamic parameter relating to vascular area is named VVO (vessel volume occupancy), and when applied to 2D images, it is named CVO (cortical vessel occupancy). Hereafter, VVO and CVO will be used interchangeably, but this is merely a difference between 3D (volume) and 2D (cross-sectional area), and they will be considered to have the same meaning.

[0116]

number

[0117] V vessel V is the blood vessel area, V target This represents the area of ​​the target region. For example, if the target deep organ is the kidney, the area of ​​the target region could be the volume of the kidney.

[0118] Each area can be identified by counting the number of pixels corresponding to blood vessels or target regions within each frame.

[0119] A processor 150 according to one embodiment of the present invention can identify hemodynamic parameters related to perfusion based on the area of ​​the target region and the intensity of the dynamic blood flow signal (S822).

[0120] The fractional moving blood volume (FMBV) related to perfusion can be calculated using the following equation 2.

[0121]

number

[0122] ΣrPD is the intensity of the dynamic blood flow signal, V target This represents the area of ​​the target region.

[0123] FMBV indicates the level of relative perfusion normalized by high blood signals in major arteries and veins. Specifically, ΣrPD can be the sum of all values ​​weighted by signal intensity across the vascular area. For example, intensities above -6 dB can be assigned a 100% value for blood-filled vessels, and intensities below -18 dB can be assigned a 0% value.

[0124] A processor 150 according to one embodiment of the present invention can identify vascular skeletal-mediated variables relating to vascular density based on the area of ​​the target region and the number of vascular branches (S823).

[0125] The vascular skeletal-mediated variable (vessel number density, VND) related to vascular density can be calculated by the following equation 3.

[0126]

number

[0127] N b V is the number of blood vessel branches, target This represents the area of ​​the target region.

[0128] A processor 150 according to one embodiment of the present invention can identify vascular skeletal parameters relating to vascular curvature based on the linear distance between the ends of the blood vessel and the length of each vascular branch (S824).

[0129] The mean vessel tortuosity (MVT) related to vascular curvature can be calculated using the following equation 4.

[0130]

number

[0131] MVT represents the actual vascular branch length L for each branch. b and the linear distance d between the two endpoints b The ratio can be calculated by determining the ratio of each branch and then dividing the sum of the ratios of all branches by the total number of branches.

[0132] The steps S821 to S824 are in a parallel relationship, and any one of them may be performed first.

[0133] A processor 150 according to one embodiment of the present invention can evaluate pulse-compressed ultrafast Doppler images using hemodynamic and vascular / skeletal parameters (S830).

[0134] Figure 9 illustrates an example in which a pulse-compressed ultrafast Doppler image according to one embodiment of the present invention was evaluated.

[0135] Clinical imaging of the kidneys was obtained from four healthy volunteers and eleven hospitalized patients diagnosed with chronic kidney disease. Subsequently, participants were divided into three groups based on estimated glomerular filtration rate (eGFR): a normal group (n=4), a CKD stage 3 group (n=4), and a CKD stage 5 group (n=5).

[0136] Existing ultrafast Doppler images (none) generally showed low contrast, and blurring of vascular structures was observed (Figure 9a-1, b-1, c-1). Therefore, it was difficult to determine whether the absence of visible blood vessels was due to their actual absence or to obstruction by depth limitations, resulting in reduced sensitivity to differences between diseased groups (CKD G3, CKD G5) and normal groups.

[0137] On the other hand, encoded ultrafast Doppler images (Barker, Golay) with superior microvascular sensitivity and contrast further emphasized vascular changes due to the progression of chronic kidney disease (Figures 9a-2, a-3, b-2, b-3, c-2, c-3).

[0138] Barker-coded and Goley-coded ultrafast Doppler images obtained from healthy supporters were characterized by a rich and well-defined vascular network throughout the kidney (Figures 9a-2 and a-3).

[0139] Compared to the densely clustered interlobular vascular populations in the cortical region of healthy kidneys, blood vessels appeared relatively sparse in kidneys with CKD stage 3, highlighting a moderate reduction in vascular structure (Figure 9b). Specifically, arcuate and interlobular vessels were generally thinner, and the branching pattern into finer interlobular vessels became even simpler, which is considered an indication of the gradual sparseness of blood vessels associated with the progression of chronic kidney disease.

[0140] A severe reduction in renal circulation was evident in all aspects of vascular area, number of vessels, and strength in kidneys with CKD stage 5 (Figure 9c). Because there were very few vessels in the cortical region, extremely rare protruding interlobar vessels remained. The rough morphology and weakened connectivity in the 2D cross-sectional images suggest a twisted volumetric deformation of the vessels.

[0141] Quantitative vascular biomarkers were derived from the key features observed in malignant vascular changes, and statistically significant differences between participant groups were further examined (Figure 9d). Generally, even within the same participant group, biomarkers measured higher in coded ultrafast Doppler images than in uncoded ultrafast Doppler images. Consequently, the progression of chronic kidney disease was more pronounced in coded ultrafast Doppler images, along with the ambiguous changes in biomarkers observed in uncoded ultrafast Doppler images.

[0142] As vascular sensitivity improved, coded ultrafast Doppler images sensed a much larger vascular area, directly impacting chronic kidney disease indicators (Figure 9d). The ratio of CVO in coded ultrafast Doppler images to uncoded ultrafast Doppler images gradually increased with the progression of chronic kidney disease, increasing 2-fold in healthy supporters, 2.3-fold in CKD stage 3 patients, and 3.4-fold in CKD stage 5 patients. The difference between participant groups was smallest for uncoded FMBV among the quantitative indicators, while the amplification of coded FMBV was the highest (4.2-fold, 4.5-fold, and 8.3-fold in the normal, CKD 3, and CKD 5 groups, respectively).

[0143] These results directly demonstrate the difference in renal perfusion across severity levels, thanks to an effective improvement in perfusion sensitivity. The associated decrease in VND supports the common finding of vascular sparseness, characterized by fewer vascular segments and fewer branches. The overall decrease in MVT and the decrease in renal function in coded UFD images suggest simplification of renal vessels in the 2D plane. Mann-Whitney U tests, without paired pairs between normal and chronic kidney disease patients, and between normal and CKD stage 3 patients, examined statistically meaningful differences in five quantitative measures for Barker and Goley coded UFD. Strong monotonic proportionality and linear relationships were also found between the four measured quantitative measures and glomerular filtration rate (eGFR).

[0144] The above information is shown in Table 1 below.

[0145] [Table 1]

[0146] Clinical images of 13 primary kidneys from healthy supporters and hospitalized chronic kidney disease patients showed pathological vascular scarcity in hemodynamics and morphology as chronic kidney disease progressed, and we were able to conclude that this was strongly correlated with a decrease in estimated glomerular filtration rate (eGFR).

[0147] Similar trends of decline were observed in xenografts from three transplant kidney beneficiaries with other grades of CKD, confirming the potential of this technology to accurately monitor renal perfusion and identify pathological vascular changes in a clinical setting.

[0148] By using pulse-compressed ultrafast Doppler images to monitor decreased blood flow, we expect to be able to predict renal dysfunction caused by various complications and to have broad applicability to abdominal organs in addition to the kidneys.

[0149] Figure 10 is a diagram comparing the characteristics of an existing Doppler image with a pulse-compressed ultrafast Doppler image according to one embodiment of the present invention.

[0150] Figure 10a is an image of the renal blood vessels of the right kidney of a healthy volunteer. Continuous acquisition of three transmission modes (B-mode, Barker mode, and Golay mode) was initiated at the moment when the renal blood vessels appeared across the entire field of view (FOV) for 300 frames each at 600 Hz. The kidney was imaged in various planes, including all cross-sections, sagittal planes, and dorsal longitudinal sections (specific diagrams of these are shown in Figures 11 and 12). As representative images, Figure 10a shows the existing UFD (none) and two PC-UFD images (Barker and Golay) of the right kidney in the sagittal plane.

[0151] Overlapping B-mode images of the kidney clearly show the hierarchical renal vessels extending from the renal sinus to the renal vesicle. Uncoded ultrafast Doppler images exhibit considerable attenuation due to their low contrast, showing only some of the major vessels and some interlobular vessels near the superficial anterior vesicle. In contrast, Barker and Goley-coded ultrafast Doppler images perfectly display vivid vascular contrast, revealing the intricate and rich vascular network that branches complexly from the renal sinus to the terminal renal cortex. Notably, the images show abundant interlobular vessel clusters extending not only near the anterior capsule but also from a depth of 75 mm to the posterior capsule. Renal vessels were masked using a customized vascular masking algorithm.

[0152] The 30 dB vascular pixel distribution of each transmission mode emphasizes a larger PD intensity and a wider vascular region in the pulse-compressed ultrafast ultrasound image than in the existing ultrafast ultrasound image (Figure 10b).

[0153] To quantify the vascular enhancement, the vascular regions (8.8 cm 2 ) of the ultrafast ultrasound image coded with Gorey and the vascular regions (5.2 cm 2 ) of the ultrafast ultrasound image coded with Barker were measured to be 4.2 times and 2.5 times larger, respectively, than the vascular region (2.1 cm 2 ) of the existing ultrafast ultrasound image (Figure 10c).

[0154] In terms of the vascular contrast ratio, the average PD intensity is highest with Gorey (median, 14.9 dB; Q1 - Q3, 11.9 - 18.6 dB), followed by Barker (median, 12.3 dB; interquartile range (Q1 - Q3), 9.5 - 15.8 dB), which is higher than that of the existing (median, 7.6 dB; Q1 - Q3, 5.8 - 10.4 dB).

[0155] Such enhancement is generally confirmed on both sides of the kidney (see Figure 12) and is also confirmed among many volunteers. The depth extension using the pulse-compressed ultrafast Doppler image is much more prominent than the commercial microvascular imaging (MVI) technology supported by a clinical USI system (Logiq Fortis, GE Healthcare, USA) (Figure 10d). Also, the interlobular vessels described can be further distinguished from the arteries and veins flowing peripherally and the interlobular veins returning to the sinusoids through autocorrelation substrate orientation estimation.

[0156] Focusing on interlobular vessels in the frontal cortex region commonly observed in existing and pulse-compressed ultrafast Doppler images (upper white dotted box in Figure 10a; enlarged view of e1-e3 in Figure 10e), we extracted transverse vessel profiles of three adjacent interlobular vessels to compare spatial resolution. Subtle differences in vessel diameter were observed in transmission mode (none: 0.65, 0.60, and 0.64 mm; Barker: 0.74, 0.55, and 0.70 mm; Goley: 0.70, 0.59, and 0.63 mm). This indicates preserved spatial resolution.

[0157] In contrast, interlobular vessels less than 1 mm in size in the occipital cortex region are observable only in pulse-compressed ultrafast Doppler images (f1-f3 in Figure 10f). This clearly demonstrates the advantage of pulse-compressed ultrafast Doppler imaging in that it can obtain greater image depth while maintaining spatial resolution.

[0158] Figure 11 is a diagram comparing existing Doppler images of different locations in deep organs with pulse-compressed ultrafast Doppler images according to one embodiment of the present invention.

[0159] The kidneys were imaged in a variety of planes, including all cross-sections, sagittal planes, and dorsal longitudinal sections.

[0160] Figure 11 is a diagram of the kidney imaged in various planes, including transverse, sagittal, and dorsal longitudinal sections. Figure 11a shows a transverse ultrasound Doppler image of the kidney (none) and pulse-compressed ultrasound Doppler images in Barker and Golay modes (Barker, Golay). Figure 11b similarly shows a sagittal view of the kidney, and Figure 11c shows a dorsal view of the kidney.

[0161] Figure 12 is a diagram comparing existing Doppler images with pulse-compressed ultrafast Doppler images according to one embodiment of the present invention for the left and right portions of deep organs.

[0162] While embodiments of the present invention have been described, the spirit of the present invention is not limited by the embodiments presented herein. Those skilled in the art who understand the spirit of the present invention can easily propose other embodiments by adding, changing, deleting, or adding components, all within the same spirit, and these too can be said to fall within the spirit of the present invention.

[0163] The following national research and development projects supported this application: 1. Project ID: 1711137875, Project Number: KMDF_PR_20200901_0008-02, Department: Multi-Department, Project Management (Specialized) Organization: General Department Research and Development Foundation for Medical Devices, Research Project Name: General Department Research and Development Project for Medical Devices (R&D) (Ministry of Science and ICT, Ministry of Health and Welfare, Ministry of Industry), Research Project Name: (Participation 1) Development and Commercialization of Peripheral Microvascular Ultrasound and Photoacoustic Fusion Imaging Equipment, Project Implementing Organization: Pohang University of Technology, Research Period: 2020.09.01~2024.12.31 2. Project ID: 2340004730, Project Number: 2020R1A6A1A03047902, Department: Ministry of Education, Project Management (Specialized) Organization: Korea Research Foundation, Research Project Name: Construction of Science and Engineering Research Infrastructure, Research Project Name: Medical Device Innovation Center, Project Implementing Organization: Pohang University of Technology, Research Period: 2024.03.01~2025.02.28 3. Project ID: 2710015764, Project Number: 2023R1A2C3004880, Department: Ministry of Science and ICT, Project Management (Specialized) Organization: Korea Research Foundation, Research Project Name: Individual Basic Research (Ministry of Science and ICT), Research Project Title: Multiscale Multimode Optical-Ultrasonic Imaging via Transparent Ultrasonic Transducer, Project Implementing Organization: Pohang University of Technology, Research Period: 2024.03.01~2025.02.28 4. Project ID: 2710014986, Project Number: 2021M3C1C3097624, Department: Ministry of Science and ICT, Project Management (Specialized) Organization: Korea Research Foundation, Research Project Name: STEAM Research, Research Topic: Development of a Cancer Target Photoacoustic / Ultrasonic Multiplexed Imaging System, Project Implementing Organization: Pohang University of Technology, Research Period: 2024.01.01~2024.12.31 5. Project ID: 1711070442, Project Number: 2011-1-00783-007, Department: Ministry of Science and ICT, Project Management (Specialized) Organization: Information and Communication Technology Promotion Center, Research Project Name: Information and Communication Technology Human Resource Development (R&D), Research Project Name: Future IT Convergence Research Institute, Project Implementing Organization: Pohang University of Technology Industry-Academia Cooperation Group, Research Period: 2018.01.01~2020.12.31 6. Project ID: 2710003818, Project Number: 00335346, Department: Ministry of Science and ICT, Project Management (Specialized) Organization: Korea Research Foundation, Research Project Name: Individual Basic Research (Ministry of Science and ICT), Research Project Title: Development of a Real-Time Ultra-High-Speed ​​Ultrasound Microvascular Imaging System for Early Detection of Diabetic Kidney Disease, Project Implementing Organization: Pohang University of Technology, Research Period: 2024.05.01~2025.04.30 7. Project ID: 2710001181, Project Number: 00211941, Department: Ministry of Science and ICT, Project Management (Specialized) Organization: Korea Research Foundation, Research Project Name: Individual Basic Research (Ministry of Science and ICT), Research Project Title: Development of Local Ultrasound Therapy and Real-Time 3D, High-Resolution Small Animal Ultrasound Brain Imaging Platform for the Treatment of Mental Illness, Project Implementing Organization: Daegu-Kyungbuk Institute of Science and Technology, Research Period: 2024.03.01~2025.02.28 8. Project ID: 2710008944, Project Number: 2018R1A5A1025511, Department: Ministry of Science and ICT, Project Management (Specialized) Organization: Korea Research Foundation, Research Project Name: Group Research Support, Research Project Name: Magnetic-Based Life Care Research Center, Project Implementing Organization: Daegu Institute of Science and Technology, Research Period: 2024.03.01~2025.02.28 [Explanation of symbols]

[0164] 1…Information provision system 10…Ultrasonic device 100…Information provision device 110…Input unit 120…Communication unit 130…Display unit 140…Storage unit 150…Processor

Claims

1. In an information provision device, A super-high-speed ultrasonic signal designed according to the transmission mode is transmitted to the target area and the reflected signal is received. The pulses of the reflected signal are compressed using a decoding filter corresponding to the transmission mode. By obtaining an image of the compressed signal reconstructed through dynamic beamforming, A clutter filter is used to remove the tissue signals fixed in the aforementioned image. An information-providing device including a processor that generates pulse-compressed ultrafast Doppler images by inversely compensating for displacements estimated by motion tracking to the region of interest within the image, which includes dynamic blood flow signals.

2. The aforementioned processor, The information providing device according to claim 1, which evaluates the pulse-compressed ultrafast Doppler image using hemodynamic parameters relating to vascular area and perfusion, and vascular skeletal parameters relating to vascular density and vascular curvature.

3. The aforementioned processor, The information providing device according to claim 2, which identifies hemodynamic parameters relating to vascular area based on the area of ​​the target region and the vascular area.

4. The aforementioned processor, The information providing device according to claim 2, which identifies hemodynamic mediating variables related to perfusion based on the area of ​​the target region and the intensity of the dynamic blood flow signal.

5. The aforementioned processor, The information providing device according to claim 2, which identifies vascular skeletal-mediated variables relating to vascular density based on the area and number of vascular branches of the target region.

6. The aforementioned processor, The information-providing device according to claim 2, which identifies vascular skeletal-mediated variables relating to vascular curvature based on the linear distance between the two ends of a blood vessel and the length of each vascular branch.

7. The information providing device according to claim 1, characterized in that the transmission mode is barker mode or golay mode.

8. The aforementioned processor, The information providing device according to claim 7, wherein in the Barker mode, the pulses of the reflected signal are compressed using a decoding filter designed to remove the side lobes of the reflected signal.

9. The aforementioned processor, The information providing device according to claim 7, wherein in the Goray mode, the pulse of the reflected signal is compressed using a decoding filter designed in the opposite phase to the ultrafast ultrasonic signal.

10. The aforementioned processor, The information providing device according to claim 1, characterized in that it includes a sequence unit that defines the detailed parameters necessary for generating the pulse-compressed ultrafast Doppler image and constitutes a stepwise operating event sequence, and a kernel unit in which kernel functions defined for processing the event sequence generated by the sequence are configured in parallel.

11. In an information provision method carried out by an information provision device, The step involves transmitting an ultra-high-speed ultrasonic signal, designed according to the transmission mode, to the target region and receiving the reflected signal. A step of compressing the pulses of the reflected signal using a decoding filter corresponding to the transmission mode, The step of obtaining an image by reconstructing the compressed signal through dynamic beamforming, A step of removing tissue signals fixed in the image using a clutter filter, An information-providing method comprising the step of generating a pulse-compressed ultrafast Doppler image by inversely compensating for displacements estimated by motion tracking of the region of interest within the image, which includes dynamic blood flow signals.

12. The information-providing method according to claim 11, further comprising the step of evaluating the pulse-compressed ultrafast Doppler image using hemodynamic parameters relating to vascular area and perfusion and vascular skeletal parameters relating to vascular density and vascular curvature.

13. The step of evaluating the pulse-compressed ultrafast Doppler image is: The information provision method according to claim 12, further comprising the step of identifying hemodynamic mediating variables relating to vascular area based on the area of ​​the target region and the vascular area.

14. The step of evaluating the pulse-compressed ultrafast Doppler image is: The information-providing method according to claim 12, further comprising the step of identifying hemodynamic mediating variables relating to perfusion based on the area of ​​the target region and the intensity of the dynamic blood flow signal.

15. The step of evaluating the pulse-compressed ultrafast Doppler image is: The information-providing method according to claim 12, further comprising the step of identifying vascular skeletal-mediated variables relating to vascular density based on the area and number of vascular branches of the target region.

16. The step of evaluating the pulse-compressed ultrafast Doppler image is: The information-providing method according to claim 12, further comprising the step of identifying vascular skeletal-mediated variables relating to vascular curvature based on the linear distance between the two ends of the blood vessel and the length of each vascular branch.

17. The information provision method according to claim 11, characterized in that the transmission mode is barker mode or golay mode.

18. The step of compressing the pulse of the reflected signal is as follows: The information-providing method according to claim 17, further comprising the step of compressing the pulses of the reflected signal using a decoding filter designed to remove side lobes of the reflected signal in the Barker mode.

19. The step of compressing the pulse of the reflected signal is as follows: The information provision method according to claim 17, wherein the Goray mode includes a step of compressing the pulses of the reflected signal using a decoding filter designed in the opposite phase to the ultrafast ultrasonic signal.

Images