Vascular image measurement signal enhancement method and device, electronic equipment and storage medium

Abstract

The present disclosure provides a blood vessel image measurement signal enhancement method, device, electronic equipment and storage medium, the method comprising: generating blood vessel image measurement signals of multiple depth positions of the blood vessel, sequentially determining each blood vessel image measurement signal as a target blood vessel image measurement signal to be processed, and the signal enhancement process for each target blood vessel image measurement signal comprises the following steps: calculating the signal prediction value of the target blood vessel image measurement signal based on the reference blood vessel image signal and the attenuation coefficient; calculating the process error of the target blood vessel image measurement signal based on the system random noise and the process error of the blood vessel image measurement signal of the previous depth position; calculating the gain value of the target blood vessel image measurement signal based on the preset background noise and the process error of the target blood vessel image measurement signal; and calculating the enhanced blood vessel image measurement signal based on the target blood vessel image measurement signal, the signal prediction value and the gain value of the target blood vessel image measurement signal.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of electronic devices, and in particular to a blood vessel image measurement signal enhancement method and device, an electronic device, and a storage medium. BACKGROUND

[0002] Optical coherence tomography (OCT) based angiography (OCTA) is a method for displaying blood vessel distribution by detecting blood flow information, without the need for contrast agents, which extends the application of OCT from structural imaging to functional imaging. Based on OCTA technology, the blood perfusion of tissues can be quantitatively evaluated: the measurement of vascular density (VD) is the most typical measurement parameter, capturing the loss of blood vessel network in the vasculature to different degrees; the morphological features of the blood vessel network can also be monitored, capturing pathological changes in blood vessel morphology and spatial arrangement.

[0003] Current blood vessel imaging techniques include digital subtraction angiography, magnetic resonance angiography, and CT angiography, but these methods have low resolution and cannot image microvessels. Today, in the field of blood vessel imaging, a plurality of interference spectra of the same part of a blood vessel are collected based on an optical coherence tomography device, the plurality of interference spectra are interference spectra of different depth positions of the blood vessel, the collected interference spectra are subjected to fast Fourier transform, and then the amplitude is taken to obtain a plurality of B-scan structural diagrams of the same part of the blood vessel. Then, by subtracting two adjacent B-scan images, the static tissue is removed, and a blood vessel image measurement signal of a plurality of depth positions of the blood vessel is obtained.

[0004] OCT has depth resolution, i.e., depth direction tomography. Since the propagation distance of light in tissue is limited, as the depth increases, the signal intensity of the OCT image decreases, and the intensity of the background noise does not change with the increase in depth. Therefore, the proportion of noise in the deep part of the image will increase, and the SNR of the image will decrease. OCTA is a technology derived from OCT images, so the quality of blood vessel imaging also decreases with the increase in depth, making it difficult to visualize blood vessels in the deeper part. For the above reasons, the blood vessel image measurement signal obtained by subtracting two B-scan images to remove static tissue will be affected by background noise, which will further result in poor quality of the blood vessel image. SUMMARY

[0005] The present disclosure provides a blood vessel image measurement signal enhancement method, device, electronic device, and storage medium.

[0006] According to a first aspect of the present disclosure, a blood vessel image measurement signal enhancement method is provided, comprising:

[0007] The blood vessel image measurement signals at multiple depth positions of the blood vessel are generated based on multiple interference spectra of the same part of the blood vessel collected by the optical coherence tomography device;

[0008] Each blood vessel image measurement signal is sequentially determined as a target blood vessel image measurement signal to be processed, and a signal enhancement process is performed for each target blood vessel image measurement signal to obtain an enhanced blood vessel image measurement signal of each target blood vessel image measurement signal.

[0009] The signal enhancement process for each target blood vessel image measurement signal includes the following steps:

[0010] The reference blood vessel image signal corresponding to the target blood vessel image measurement signal and the attenuation coefficient corresponding to the reference blood vessel image signal are determined, wherein the reference blood vessel image signal is the enhanced blood vessel image measurement signal of the blood vessel image measurement signal at the previous depth position of the target blood vessel image measurement signal.

[0011] The signal prediction value of the target blood vessel image measurement signal is calculated based on the reference blood vessel image signal and the attenuation coefficient corresponding to the reference blood vessel image signal.

[0012] The systematic random noise and the process error of the blood vessel image measurement signal at the previous depth position are determined.

[0013] The process error of the target blood vessel image measurement signal is calculated based on the systematic random noise and the process error of the blood vessel image measurement signal at the previous depth position.

[0014] The gain value of the target blood vessel image measurement signal is calculated based on the preset background noise and the process error of the target blood vessel image measurement signal.

[0015] The enhanced blood vessel image measurement signal of the target blood vessel image measurement signal is calculated based on the target blood vessel image measurement signal, the signal prediction value of the target blood vessel image measurement signal, and the gain value of the target blood vessel image measurement signal.

[0016] In the embodiments of the present disclosure, the signal prediction value of the target blood vessel image measurement signal is calculated based on the following formula:

[0017]

[0018] wherein, is the signal prediction value of the target blood vessel image measurement signal, is the reference blood vessel image signal, is the longitudinal resolution of the system, is the attenuation coefficient corresponding to the reference blood vessel image signal.

[0019] In the embodiments of the present disclosure, the system random noise of the blood vessel image measurement signal at the previous depth position is determined by the following formula:

[0020]

[0021] wherein, is the system random noise of the blood vessel image measurement signal at the previous depth position, is the blood vessel image measurement signal at the previous depth position, is the average value of a plurality of blood vessel image measurement signals centered on the blood vessel image measurement signal at the previous depth position.

[0022] In the embodiments of the present disclosure, the process error of the target blood vessel image measurement signal is calculated by the following formula:

[0023]

[0024] wherein, is the current process error of the target blood vessel image measurement signal, is the system random noise of the blood vessel image measurement signal at the previous depth position, is the process error of the blood vessel image measurement signal at the previous depth position.

[0025] In the embodiments of the present disclosure, the gain value of the target blood vessel image measurement signal is calculated by the following formula:

[0026]

[0027] wherein, is the gain value of the target blood vessel image measurement signal, is the process error of the target blood vessel image measurement signal, is the preset background noise.

[0028] In the embodiments of the present disclosure, the enhanced blood vessel image measurement signal of the target blood vessel image measurement signal is calculated by the following formula:

[0029]

[0030] is the enhanced blood vessel image measurement signal of the target blood vessel image measurement signal, is the signal prediction value of the target blood vessel image measurement signal, is the gain value of the target blood vessel image measurement signal, is the target blood vessel image measurement signal.

[0031] In the embodiments of the present disclosure, the blood vessel image measurement signal enhancement method further comprises:

[0032] The process error of the target blood vessel image measurement signal is updated by the following formula:

[0033]

[0034] wherein, is the updated process error of the target blood vessel image measurement signal, is the current process error of the target blood vessel image measurement signal, is the gain value of the target blood vessel image measurement signal;

[0035] The attenuation coefficient corresponding to the enhanced blood vessel image measurement signal of the target blood vessel image measurement signal is calculated by the following formula:

[0036]

[0037] is the attenuation coefficient corresponding to the enhanced blood vessel image measurement signal of the target blood vessel image measurement signal, is the enhanced blood vessel image measurement signal of the target blood vessel image measurement signal, is the blood vessel image measurement signal of the i-th depth position.

[0038] According to a second aspect of the present disclosure, a blood vessel image measurement signal enhancement device is provided, which comprises a measurement signal generation module and a measurement signal enhancement module;

[0039] The measurement signal generation module is configured to generate blood vessel image measurement signals of multiple depth positions of a blood vessel based on multiple interference spectra of the same part of the blood vessel collected by an optical coherence tomography device;

[0040] The measurement signal enhancement module is configured to sequentially determine each blood vessel image measurement signal as a target blood vessel image measurement signal to be processed, and execute a signal enhancement process for each target blood vessel image measurement signal to obtain an enhanced blood vessel image measurement signal of each target blood vessel image measurement signal;

[0041] The reference blood vessel image signal corresponding to the target blood vessel image measurement signal and the attenuation coefficient corresponding to the reference blood vessel image signal are determined, wherein the reference blood vessel image signal is the enhanced blood vessel image measurement signal of the blood vessel image measurement signal of the previous depth position of the target blood vessel image measurement signal;

[0042] The signal prediction value of the target blood vessel image measurement signal is calculated based on the reference blood vessel image signal and the attenuation coefficient corresponding to the reference blood vessel image signal;

[0043] The system random noise and the process error of the blood vessel image measurement signal of the previous depth position are determined;

[0044] calculate a process error of the target blood vessel image measurement signal based on a system random noise of a blood vessel image measurement signal at a previous depth position and a process error of the blood vessel image measurement signal at the previous depth position;

[0045] calculate a gain value of the target blood vessel image measurement signal based on a preset background noise and the process error of the target blood vessel image measurement signal;

[0046] calculate an enhanced blood vessel image measurement signal of the target blood vessel image measurement signal based on the target blood vessel image measurement signal, a signal prediction value of the target blood vessel image measurement signal and the gain value of the target blood vessel image measurement signal.

[0047] In the embodiments of the present disclosure, the signal prediction value of the target blood vessel image measurement signal is calculated based on the following formula:

[0048]

[0049] wherein, is the signal prediction value of the target blood vessel image measurement signal, is a reference blood vessel image signal, is a longitudinal resolution of a system, is an attenuation coefficient corresponding to the reference blood vessel image signal.

[0050] In the embodiments of the present disclosure, the system random noise of the blood vessel image measurement signal at the previous depth position is determined by the following formula:

[0051]

[0052] wherein, is the system random noise of the blood vessel image measurement signal at the previous depth position, is the blood vessel image measurement signal at the previous depth position, is an average value of a plurality of blood vessel image measurement signals centered on the blood vessel image measurement signal at the previous depth position.

[0053] In the embodiments of the present disclosure, the process error of the target blood vessel image measurement signal is calculated by the following formula:

[0054]

[0055] wherein, is the current process error of the target blood vessel image measurement signal, is the system random noise of the blood vessel image measurement signal at the previous depth position, is the process error of the blood vessel image measurement signal at the previous depth position.

[0056] In the embodiments of the present disclosure, the gain value of the target vessel image measurement signal is calculated by the following formula:

[0057]

[0058] wherein, is the gain value of the target vessel image measurement signal, is the process error of the target vessel image measurement signal, is the preset background noise.

[0059] In the embodiments of the present disclosure, the enhanced vessel image measurement signal of the target vessel image measurement signal is calculated by the following formula:

[0060]

[0061] is the enhanced vessel image measurement signal of the target vessel image measurement signal, is the signal prediction value of the target vessel image measurement signal, is the gain value of the target vessel image measurement signal, is the target vessel image measurement signal.

[0062] In the embodiments of the present disclosure, the vessel image measurement signal enhancement device further comprises a process error updating module and an attenuation coefficient calculation module.

[0063] The process error updating module is configured to update the process error of the target vessel image measurement signal by the following formula:

[0064]

[0065] wherein, is the updated process error of the target vessel image measurement signal, is the current process error of the target vessel image measurement signal, is the gain value of the target vessel image measurement signal;

[0066] The attenuation coefficient calculation module is configured to calculate the attenuation coefficient corresponding to the enhanced vessel image measurement signal of the target vessel image measurement signal by the following formula:

[0067]

[0068] is the attenuation coefficient corresponding to the enhanced vessel image measurement signal of the target vessel image measurement signal, is the enhanced vessel image measurement signal of the target vessel image measurement signal, is the vessel image measurement signal at the i-th depth position.

[0069] According to a third aspect of the present disclosure, an electronic device is provided, comprising:

[0070] at least one processor; and a memory connected with the at least one processor in communication;

[0071] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the blood vessel image measurement signal enhancement method provided in the first aspect.

[0072] According to a fourth aspect of the present disclosure, a non-transitory computer readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable a computer to perform the blood vessel image measurement signal enhancement method provided in the first aspect.

[0073] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present disclosure, nor to limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.

[0074] The technical solutions provided by the present disclosure have the beneficial effects that:

[0075] The blood vessel image measurement signal enhancement method provided by the embodiments of the present disclosure can, after obtaining the blood vessel image measurement signals at multiple depth positions of the blood vessel, perform signal enhancement on the blood vessel image measurement signals in a filtering manner, and automatically adjust the filtering scale according to the signal-to-noise ratio. In the high signal-to-noise ratio area, the filtering scale can be reduced, and in the low signal-to-noise ratio area, the filtering scale can be increased to filter out background noise, thereby enhancing the target blood vessel image measurement signal and improving the quality of the blood vessel image. BRIEF DESCRIPTION OF DRAWINGS

[0076] The accompanying drawings serve to better understand the present solutions and do not constitute limitations on the present disclosure. Among them:

[0077] Figure 1 Fig. 1 shows a flowchart of a blood vessel image measurement signal enhancement method provided by an embodiment of the present disclosure;

[0078] Figure 2 Fig. 2 shows a flowchart of another blood vessel image measurement signal enhancement method provided by an embodiment of the present disclosure;

[0079] Figure 3 Fig. 3 shows a schematic diagram of a blood vessel image measurement signal enhancement device provided by an embodiment of the present disclosure;

[0080] Figure 4 Fig. 4 shows a schematic diagram of another blood vessel image measurement signal enhancement device provided by an embodiment of the present disclosure;

[0081] Figure 5A schematic block diagram of an example electronic device that can be used to implement embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0082] Exemplary embodiments of the present disclosure are described herein with reference to the accompanying drawings, which are incorporated in, and constitute a part of, this specification. Various details of the embodiments of the present disclosure are described herein to help the understanding of the present disclosure. Therefore, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, in the following description, descriptions of well-known functions and constructions are omitted for clarity and conciseness.

[0083] Optical coherence tomography (OCT) based angiography (OCTA) is a method for displaying blood vessel distribution by detecting blood flow information, without the need for contrast agents, which extends the application of OCT from structural imaging to functional imaging. Based on OCTA technology, the blood perfusion of the tissue can be quantitatively evaluated: the measurement of vascular density (VD) is the most typical measurement parameter, which captures the different degrees of loss of the vascular network in the vasculature; the morphological features of the vascular network can also be monitored, which captures the pathological changes of the vascular morphology and spatial arrangement.

[0084] Current blood vessel imaging technologies include digital subtraction angiography, magnetic resonance angiography, CT angiography, etc., but these methods have low resolution and cannot image microvessels. Today, in the field of blood vessel imaging, a plurality of interference spectra of the same part of a blood vessel are collected based on an optical coherence tomography device, the plurality of interference spectra are respectively interference spectra of different depth positions of the blood vessel, the collected interference spectra are subjected to fast Fourier transform, and then the amplitude is taken to obtain a plurality of B-scan structural diagrams of the same part of the blood vessel. Then, by subtracting two adjacent B-scan images, the static tissue is removed, and thus a plurality of blood vessel image measurement signals of the blood vessel at different depth positions are obtained.

[0085] OCT has depth resolution capability, i.e., depth direction tomography. Since the propagation distance of light in tissue is limited, as the depth increases, the signal intensity of the OCT image decreases, and the intensity of the background noise does not change with the increase of the depth. Therefore, the proportion of noise in the deep part of the image will increase, and the SNR of the image will decrease. OCTA is a technology derived from OCT images, so the quality of blood vessel imaging also decreases with the increase of the depth, making it difficult to visualize the blood vessels at a deeper position. For the above reasons, the blood vessel image measurement signal obtained by subtracting the static tissue from the two B-scan images will be affected by the background noise, and thus the quality of the blood vessel image is poor.

[0086] The blood vessel image measurement signal enhancement method, device, electronic equipment and storage medium provided by the embodiments of the present disclosure aim to solve at least one of the above technical problems of the prior art.

[0087] Figure 1 A flowchart of a blood vessel image measurement signal enhancement method provided by the embodiments of the present disclosure is shown as Figure 1 The method can mainly include the following steps:

[0088] S110: Based on the plurality of interference spectra of the same part of the blood vessel collected by the optical coherence tomography device, a plurality of blood vessel image measurement signals of different depth positions of the blood vessel are generated.

[0089] Optical coherence tomography (OCT for short) is a technology that uses near-infrared light coherence to irradiate the tissue to be measured, generates interference according to the coherence of light, and uses tissue imaging. OCT is a high-resolution, non-contact biological tissue imaging technology, similar to ultrasound, except that light is used instead of sound waves to produce images. Light is scattered inside the sample, then processed to form high-resolution, depth images to analyze the internal microstructure, live, without physical contact. Lateral scanning can quickly obtain non-invasive two-dimensional and three-dimensional images with clarity exceeding 10 microns.

[0090] In the field of blood vessel imaging, based on the plurality of interference spectra of the same part of the blood vessel collected by the optical coherence tomography device, the plurality of interference spectra are interference spectra of different depth positions of the blood vessel, the collected interference spectra are subjected to fast Fourier transform, and then the amplitudes are taken to obtain a plurality of B-scan structure images of the same part of the blood vessel. Then, by subtracting two adjacent B-scan images, the static tissue is removed, thereby obtaining a plurality of blood vessel image measurement signals of different depth positions of the blood vessel.

[0091] S120: Each blood vessel image measurement signal is sequentially determined as a target blood vessel image measurement signal to be processed, and a signal enhancement process is performed for each target blood vessel image measurement signal to obtain a blood vessel image measurement signal after enhancement of each target blood vessel image measurement signal.

[0092] Here, the signal enhancement process includes Kalman filtering of the blood vessel image measurement signal, and the Kalman filtering algorithm mainly includes two stages of prediction and update. The blood vessel image measurement signal is subject to exponential decay, so the blood vessel image signal of the next depth position can be predicted by the related data of the blood vessel image signal of the previous depth position, wherein the blood vessel image signal obtained by prediction is defined as a signal prediction value of the blood vessel image measurement signal.

[0093] In step S120, each blood vessel image measurement signal is determined as a target blood vessel image measurement signal to be processed in turn. The target blood vessel image measurement signal is signal enhanced by the relevant data of the blood vessel image measurement signal at the previous depth position of the target blood vessel image measurement signal, to obtain the blood vessel image measurement signal after signal enhancement of the target blood vessel image measurement signal; for example, when the target blood vessel image measurement signal is the blood vessel image measurement signal at the second depth position, the blood vessel image measurement signal at the second depth position is signal enhanced by the relevant data of the blood vessel image measurement signal at the first depth position, to obtain the blood vessel image measurement signal after signal enhancement of the blood vessel image measurement signal at the second depth position. It should be noted that when the target blood vessel image measurement signal is the blood vessel image measurement signal at the first depth position, a plurality of data can be set in advance as the relevant data of the blood vessel image measurement signal at the previous depth position of the blood vessel image measurement signal at the first depth position.

[0094] Figure 2 A flowchart of the signal enhancement process for each target blood vessel image measurement signal provided by the embodiments of the present disclosure is shown, as shown in Figure 2 The flowchart mainly includes the following steps:

[0095] S210: determining the reference blood vessel image signal corresponding to the target blood vessel image measurement signal and the attenuation coefficient corresponding to the reference blood vessel image signal.

[0096] Here, the reference blood vessel image signal is the blood vessel image measurement signal after signal enhancement of the blood vessel image measurement signal at the previous depth position of the target blood vessel image measurement signal.

[0097] S220: calculating the signal prediction value of the target blood vessel image measurement signal based on the reference blood vessel image signal and the attenuation coefficient corresponding to the reference blood vessel image signal.

[0098] In the embodiments of the present disclosure, the signal prediction value of the target blood vessel image measurement signal is calculated based on the following formula:

[0099]

[0100] wherein, is the signal prediction value of the target blood vessel image measurement signal, is the reference blood vessel image signal, is the longitudinal resolution of the system, is the attenuation coefficient corresponding to the reference blood vessel image signal.

[0101] S230: determining the system random noise and process error of the blood vessel image measurement signal at the previous depth position.

[0102] In the embodiments of the present disclosure, the system random noise of the blood vessel image measurement signal at the previous depth position is determined by the following formula:

[0103]

[0104] wherein, is the system random noise of the blood vessel image measurement signal at the previous depth position, is the blood vessel image measurement signal at the previous depth position, is the average of a plurality of blood vessel image measurement signals centered on the blood vessel image measurement signal at the previous depth position.

[0105] S240: calculating the process error of the target blood vessel image measurement signal based on the system random noise of the blood vessel image measurement signal at the previous depth position and the process error.

[0106] In the embodiments of the present disclosure, the process error of the target blood vessel image measurement signal is calculated by the following formula:

[0107]

[0108] wherein, is the current process error of the target blood vessel image measurement signal, is the system random noise of the blood vessel image measurement signal at the previous depth position, is the process error of the blood vessel image measurement signal at the previous depth position.

[0109] S250: calculating the gain value of the target blood vessel image measurement signal based on the preset background noise and the process error of the target blood vessel image measurement signal.

[0110] In the embodiments of the present disclosure, the gain value of the target blood vessel image measurement signal is calculated by the following formula:

[0111]

[0112] wherein, is the gain value of the target blood vessel image measurement signal, is the process error of the target blood vessel image measurement signal, is the preset background noise.

[0113] S260: calculating the enhanced blood vessel image measurement signal of the target blood vessel image measurement signal based on the target blood vessel image measurement signal, the signal prediction value of the target blood vessel image measurement signal and the gain value of the target blood vessel image measurement signal.

[0114] In the embodiments of the present disclosure, the enhanced blood vessel image measurement signal of the target blood vessel image measurement signal is calculated by the following formula:

[0115]

[0116] an enhanced blood vessel image measurement signal of the target blood vessel image measurement signal, a signal prediction value of the target blood vessel image measurement signal, a gain value of the target blood vessel image measurement signal, the target blood vessel image measurement signal.

[0117] Optionally, after step S260, the process error of the target blood vessel image measurement signal can also be updated, and the attenuation coefficient corresponding to the enhanced blood vessel image measurement signal of the target blood vessel image measurement signal is calculated.

[0118] In the embodiment of the present disclosure, the process error of the target blood vessel image measurement signal is updated by the following formula:

[0119]

[0120] wherein, an updated process error of the target blood vessel image measurement signal, a current process error of the target blood vessel image measurement signal, a gain value of the target blood vessel image measurement signal. It can be understood that the process error of the blood vessel image measurement signal of the previous depth position of the target blood vessel image measurement signal is also obtained by logical calculation of the above formula.

[0121] In the embodiment of the present disclosure, the attenuation coefficient corresponding to the enhanced blood vessel image measurement signal of the target blood vessel image measurement signal is calculated by the following formula:

[0122]

[0123] an attenuation coefficient corresponding to the enhanced blood vessel image measurement signal of the target blood vessel image measurement signal, an enhanced blood vessel image measurement signal of the target blood vessel image measurement signal, a blood vessel image measurement signal of the i-th depth position. It can be understood that the attenuation coefficient corresponding to the enhanced blood vessel image measurement signal of the blood vessel image measurement signal of the previous depth position of the target blood vessel image measurement signal is also obtained by logical calculation of the above formula.

[0124] The blood vessel image measurement signal enhancement method provided by the embodiments of the present disclosure can enhance the target blood vessel image measurement signal and improve the quality of the blood vessel image.

[0125] The filtering method can be Kalman filtering technology. Kalman filtering technology is a high-efficiency recursion that uses a series of observations and system predictions over time to generate optimal state estimates that are often more accurate than state estimates based on a single measurement. Kalman filtering is divided into two steps: prediction and update. In the prediction stage, Kalman filtering uses information in the previous time step to produce a state estimate and its uncertainty at the current time step. In the update stage, the predicted state estimate, the current measurement, and the weighting factor are used to calculate a more accurate "state estimate".

[0126] Based on the same principle as the blood vessel image measurement signal enhancement method described above, the embodiments of the present disclosure provide a blood vessel image measurement signal enhancement device, Figure 3 A schematic diagram of a blood vessel image measurement signal enhancement device provided by the embodiments of the present disclosure is shown in FIG. 3. Figure 3 As shown in FIG. 3, the blood vessel image measurement signal enhancement device 300 includes a measurement signal generation module 310 and a measurement signal enhancement module 320.

[0127] The measurement signal generation module 310 is configured to generate blood vessel image measurement signals of multiple depth positions of a blood vessel based on multiple interference spectra of the same part of the blood vessel collected by an optical coherence tomography device.

[0128] The measurement signal enhancement module 320 is configured to sequentially determine each blood vessel image measurement signal as a target blood vessel image measurement signal to be processed, and perform a signal enhancement process for each target blood vessel image measurement signal to obtain a blood vessel image measurement signal after signal enhancement of each target blood vessel image measurement signal.

[0129] The reference blood vessel image signal corresponding to the target blood vessel image measurement signal and the attenuation coefficient corresponding to the reference blood vessel image signal are determined, wherein the reference blood vessel image signal is the blood vessel image measurement signal after signal enhancement of the blood vessel image measurement signal of the previous depth position of the target blood vessel image measurement signal.

[0130] The signal prediction value of the target blood vessel image measurement signal is calculated based on the reference blood vessel image signal and the attenuation coefficient corresponding to the reference blood vessel image signal.

[0131] The system random noise and process error of the blood vessel image measurement signal of the previous depth position are determined.

[0132] calculate a process error of the target blood vessel image measurement signal based on a system random noise of a blood vessel image measurement signal at a previous depth position and a process error of the blood vessel image measurement signal;

[0133] calculate a gain value of the target blood vessel image measurement signal based on a preset background noise and the process error of the target blood vessel image measurement signal;

[0134] calculate an enhanced blood vessel image measurement signal of the target blood vessel image measurement signal based on the target blood vessel image measurement signal, a signal prediction value of the target blood vessel image measurement signal and the gain value of the target blood vessel image measurement signal.

[0135] The blood vessel image measurement signal enhancement device provided by the embodiments of the present disclosure can perform signal enhancement on the blood vessel image measurement signal in a filtering manner after obtaining the blood vessel image measurement signals at multiple depth positions of the blood vessel, and automatically adjust the filtering scale according to the signal-to-noise ratio. In a high signal-to-noise ratio area, the filtering scale can be reduced, and in a low signal-to-noise ratio area, the filtering scale can be increased to filter out background noise, so as to enhance the target blood vessel image measurement signal and improve the quality of the blood vessel image.

[0136] The filtering method can be Kalman filtering technology. Kalman filtering technology is a high-efficiency recursion that uses a series of observations and system predictions over time to generate optimal state estimates that are often more accurate than state estimates based on a single measurement. Kalman filtering is divided into two steps: prediction and update. In the prediction stage, Kalman filtering uses information in the previous time step to produce a state estimate and its uncertainty at the current time step. In the update stage, the predicted state estimate, the current measurement and the weighting factor are used to calculate a more accurate "state estimate".

[0137] In the embodiments of the present disclosure, the signal prediction value of the target blood vessel image measurement signal is calculated based on the following formula:

[0138]

[0139] wherein, is the signal prediction value of the target blood vessel image measurement signal, is a reference blood vessel image signal, is a longitudinal resolution of the system, is an attenuation coefficient corresponding to the reference blood vessel image signal.

[0140] In the embodiments of the present disclosure, the system random noise of the blood vessel image measurement signal at the previous depth position is determined by the following formula:

[0141]

[0142] wherein, a system random noise of the blood vessel image measurement signal of the previous depth position, a blood vessel image measurement signal of the previous depth position, an average of a plurality of blood vessel image measurement signals centered on the blood vessel image measurement signal of the previous depth position.

[0143] In the embodiments of the present disclosure, the process error of the target blood vessel image measurement signal is calculated by the following formula:

[0144]

[0145] wherein, a current process error of the target blood vessel image measurement signal, a system random noise of the blood vessel image measurement signal of the previous depth position, a process error of the blood vessel image measurement signal of the previous depth position.

[0146] In the embodiments of the present disclosure, the gain value of the target blood vessel image measurement signal is calculated by the following formula:

[0147]

[0148] wherein, a gain value of the target blood vessel image measurement signal, a process error of the target blood vessel image measurement signal, a preset background noise.

[0149] In the embodiments of the present disclosure, the enhanced blood vessel image measurement signal of the target blood vessel image measurement signal is calculated by the following formula:

[0150]

[0151] an enhanced blood vessel image measurement signal of the target blood vessel image measurement signal, a signal prediction value of the target blood vessel image measurement signal, a gain value of the target blood vessel image measurement signal, a target blood vessel image measurement signal.

[0152] Based on the same principle as the above-mentioned blood vessel image measurement signal enhancement method, the embodiments of the present disclosure provide another blood vessel image measurement signal enhancement device, Figure 4 shows a schematic diagram of another blood vessel image measurement signal enhancement device provided by the embodiments of the present disclosure, like Figure 4As shown, the blood vessel image measurement signal enhancement device 300 further comprises a process error updating module 330 and an attenuation coefficient calculating module 340 on the basis of comprising the measurement signal generating module 310 and the measurement signal enhancing module 320.

[0153] The process error updating module 330 is configured to update the process error of the target blood vessel image measurement signal according to the following formula:

[0154]

[0155] wherein, is the updated process error of the target blood vessel image measurement signal, is the current process error of the target blood vessel image measurement signal, is the gain value of the target blood vessel image measurement signal.

[0156] The attenuation coefficient calculating module 340 is configured to calculate the attenuation coefficient corresponding to the enhanced blood vessel image measurement signal of the target blood vessel image measurement signal according to the following formula:

[0157]

[0158] wherein, is the attenuation coefficient corresponding to the enhanced blood vessel image measurement signal of the target blood vessel image measurement signal, is the enhanced blood vessel image measurement signal of the target blood vessel image measurement signal, is the blood vessel image measurement signal at the i th depth position.

[0159] It can be understood that the above-mentioned modules of the blood vessel image measurement signal enhancement device in the embodiments of the present disclosure have the functions of realizing the corresponding steps of the above-mentioned blood vessel image measurement signal enhancement method. The functions can be realized by hardware, or realized by hardware executing corresponding software. The hardware or software comprises one or more modules corresponding to the above-mentioned functions. The above-mentioned modules can be software and / or hardware, and the above-mentioned modules can be realized individually or realized in an integrated manner. The function description of each module of the blood vessel image measurement signal enhancement device can be referred to the corresponding description of the blood vessel image measurement signal enhancement method, which will not be described here.

[0160] In the technical solutions of the present disclosure, the collection, storage, use, processing, transmission, provision and disclosure of the personal information of the customer involved in the technical solutions comply with the relevant laws and regulations and do not violate public order and good customs.

[0161] According to the embodiments of the present disclosure, the present disclosure further provides an electronic device, a readable storage medium and a computer program product.

[0162] Figure 5A schematic block diagram of an example electronic device that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit the implementations of the present disclosure described and / or claimed in this document.

[0163] As shown in Figure 5 , the electronic device 500 includes a computing unit 501 that can perform various appropriate actions and processes in accordance with a computer program stored in a read-only memory (ROM) 502 or a computer program loaded into a random access memory (RAM) 503 from a storage unit 508. Various programs and data required for the operation of the electronic device 500 can also be stored in the RAM 503. The computing unit 501, the ROM 502, and the RAM 503 are connected to each other through a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0164] Various components in the electronic device 500 are connected to the I / O interface 505, including an input unit 506, such as a keyboard, a mouse, etc.; an output unit 507, such as various types of displays, a speaker, etc.; the storage unit 508, such as a magnetic disk, an optical disk, etc.; and a communication unit 509, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 509 allows the electronic device 500 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0165] The computing unit 501 can be various general and / or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 501 performs various methods and processes described above, such as the blood vessel image measurement signal enhancement method. For example, in some embodiments, the blood vessel image measurement signal enhancement method can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 508. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 500 via the ROM 502 and / or the communication unit 509. When the computer program is loaded onto the RAM 503 and executed by the computing unit 501, one or more steps of the blood vessel image measurement signal enhancement method described above can be performed. Alternatively, in other embodiments, the computing unit 501 can be configured to perform the blood vessel image measurement signal enhancement method by any other suitable means, such as by means of firmware.

[0166] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a programmable logic device (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0167] Program code for carrying out methods of the present disclosure can be written in any combination of one or more programming languages. The program code can be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the program code, when executed by the processor or controller, produces a means for implementing the functions / acts specified in the flowcharts and / or block diagrams. The program code can be executed entirely on a machine, partially on a machine, partially on a machine as a stand-alone software package, partially on a machine and partially on a remote machine or entirely on a remote machine or server.

[0168] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0169] To provide interaction with a customer, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the customer; and a keyboard and pointing device (e.g., a mouse or trackball) through which the customer provides input to the computer. Other types of devices can also be used to provide interaction with the customer; for example, feedback provided to the customer can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the customer can be received in any form (including voice input, speech input, or tactile input).

[0170] The systems and technologies described herein can be implemented in computing systems that include back-end components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include front-end components (e.g., a client computer with a graphical client interface or web browser through which a client can interact with the implementations of the systems and technologies described herein), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0171] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0172] It should be understood that the various forms of flow shown above can be used to reorder, add, or delete steps. For example, the steps described in the present disclosure can be performed in parallel, in series, or in a different order, as long as the desired results of the technology disclosed in the present disclosure can be achieved, which is not limited herein.

[0173] The above detailed description does not constitute a limitation on the protection scope of the present disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for enhancing vascular image measurement signals, comprising: Based on multiple interference spectra of the same part of the blood vessel acquired by optical coherence tomography equipment, vascular image measurement signals at multiple depth positions of the blood vessel are generated. Each of the vascular image measurement signals is sequentially determined as the target vascular image measurement signal to be processed, and a signal enhancement process is performed for each target vascular image measurement signal to obtain an enhanced vascular image measurement signal for each target vascular image measurement signal. The signal enhancement process for each of the target blood vessel image measurement signals includes the following steps: Determine the reference vascular image signal corresponding to the target vascular image measurement signal and the attenuation coefficient corresponding to the reference vascular image signal, wherein the reference vascular image signal is the enhanced vascular image measurement signal of the vascular image measurement signal at the previous depth position of the target vascular image measurement signal; Based on the reference vascular image signal and the attenuation coefficient corresponding to the reference vascular image signal, the signal prediction value of the target vascular image measurement signal is calculated; The system random noise and process error of the vascular image measurement signal at the previous depth position are determined; The process error of the target blood vessel image measurement signal is calculated based on the system random noise and process error of the blood vessel image measurement signal at the previous depth position. The gain value of the target blood vessel image measurement signal is calculated based on the preset background noise and the process error of the target blood vessel image measurement signal. Based on the target vascular image measurement signal, the signal prediction value of the target vascular image measurement signal, and the gain value of the target vascular image measurement signal, the enhanced vascular image measurement signal of the target vascular image measurement signal is calculated.

2. The method according to claim 1, characterized in that, The predicted signal value of the target blood vessel image measurement signal is calculated based on the following formula: in, The predicted signal value of the measured signal for the target blood vessel image. The reference vascular image signal, For the system's vertical resolution, The attenuation coefficient is the one corresponding to the reference vascular image signal.

3. The method according to claim 1, characterized in that, The system random noise of the vascular image measurement signal at the previous depth position is determined by the following formula: in, The system random noise of the vascular image measurement signal at the previous depth position. The measurement signal is the vascular image signal at the previous depth position. It is the average value of multiple vascular image measurement signals centered on the vascular image measurement signal at the previous depth position.

4. The method according to claim 3, characterized in that, The process error of the target blood vessel image measurement signal is calculated using the following formula: in, The current process error of the target blood vessel image measurement signal. The system random noise of the vascular image measurement signal at the previous depth position. The process error for measuring the signal of the blood vessel image at the previous depth position.

5. The method according to claim 1, characterized in that, The enhanced vascular image measurement signal of the target vascular image is calculated using the following formula: The enhanced vascular image measurement signal is the target vascular image measurement signal. The predicted signal value of the measured signal for the target blood vessel image. The gain value of the signal measured for the target blood vessel image. The signal is measured for the target blood vessel image.

6. The method according to claim 1, characterized in that, Also includes: The process error of the target blood vessel image measurement signal is updated using the following formula: in, The updated process error is the measurement signal of the target blood vessel image. The current process error of the target blood vessel image measurement signal. Measure the gain value of the signal for the target blood vessel image; The attenuation coefficient of the enhanced blood vessel image measurement signal is calculated using the following formula: The attenuation coefficient corresponding to the enhanced vascular image measurement signal of the target vascular image measurement signal. The enhanced vascular image measurement signal is the target vascular image measurement signal. The signal is the blood vessel image measurement signal at the i-th depth location.

7. A vascular image measurement signal enhancement device, comprising: The measurement signal generation module is used to generate vascular image measurement signals at multiple depth positions of the blood vessel based on multiple interference spectra of the same part of the blood vessel acquired by optical coherence tomography equipment. The measurement signal enhancement module is used to sequentially determine each of the vascular image measurement signals as the target vascular image measurement signals to be processed, and to perform a signal enhancement process for each target vascular image measurement signal to obtain an enhanced vascular image measurement signal for each target vascular image measurement signal. The signal enhancement process for each of the target blood vessel image measurement signals includes the following steps: Determine the reference vascular image signal corresponding to the target vascular image measurement signal and the attenuation coefficient corresponding to the reference vascular image signal, wherein the reference vascular image signal is the enhanced vascular image measurement signal of the vascular image measurement signal at the previous depth position of the target vascular image measurement signal; Based on the reference vascular image signal and the attenuation coefficient corresponding to the reference vascular image signal, the signal prediction value of the target vascular image measurement signal is calculated; The system random noise and process error of the vascular image measurement signal at the previous depth position are determined; The process error of the target blood vessel image measurement signal is calculated based on the system random noise and process error of the blood vessel image measurement signal at the previous depth position. The gain value of the target blood vessel image measurement signal is calculated based on the preset background noise and the process error of the target blood vessel image measurement signal. Based on the target vascular image measurement signal, the signal prediction value of the target vascular image measurement signal, and the gain value of the target vascular image measurement signal, the enhanced vascular image measurement signal of the target vascular image measurement signal is calculated.

8. An electronic device, comprising: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the vascular image measurement signal enhancement method according to any one of claims 1-6.

9. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to perform the vascular image measurement signal enhancement method according to any one of claims 1-6.

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