79 results about "Flow imaging" patented technology

The invention provides a large-field-of-view high-dynamic myocardial blood flow rate imaging method and device, and relates to the technical field of biomedical optical imagines.The method comprises the steps that imaging parameters of an imaging unit are optimized according to a preset optimization strategy, and the optimized imaging unit is used for collecting laser speckle images of an observation area; a plurality of laser speckle images are obtained; and determining a space speckle contrast matrix and a time speckle contrast matrix of the observation area based on the plurality of laser speckle images, and generating a blood flow index distribution image of the observation area based on the space speckle contrast matrix and the time speckle contrast matrix. According to the large-view-field high-dynamic myocardial blood flow rate imaging method and device, through multi-parameter optimization, the signal-to-noise ratio of myocardial blood flow imaging and the measurable range of the blood flow rate can be effectively increased, and the problem that the myocardial blood flow imaging area is limited is solved.

The invention belongs to the technical field of ultrasonic Doppler blood flow imaging, and particularly relates to a three-dimensional ultrasonic vector Doppler imaging method based on a row-column addressing array. According to the method, three-dimensional ultrasonic vector Doppler imaging is realized by combining a high-frame-rate two-dimensional non-focused wave emission sequence and a row-column addressing array (RCA) of a least square multi-angle Doppler velocity estimator; the method specifically comprises the following steps: acquiring radio frequency data from each oblique non-focused wave emission, and then performing IQ demodulation, beam forming and clutter filtering; performing high-frame-rate multi-angle vector Doppler analysis and speed estimation on a result through RCA; and dual-wavelength anti-aliasing processing is carried out. According to the invention, the imaging speed of more than thousands of frames can be realized, the sensitivity to low-speed flow and the measurement accuracy to high-speed flow are obviously improved, and clinical environment experimental verification is carried out; the method is suitable for clinical application, especially for blood flow dynamic monitoring of large blood vessels, and important support can be provided for blood flow dynamic research and clinical diagnosis.

The invention discloses a method for correcting ultrafast ultrasonic motion displacement based on a VoxelMorph model to solve motion artifacts. Comprising the following steps: acquiring ultrafast ultrasonic data, preprocessing the acquired data to obtain an initial data set, and dividing the initial data set into a training set and a test set; constructing a VoxelMorph motion correction network model based on the lightweight attention module, training the neural network model based on the training set to obtain a motion calibration network model, and testing the motion calibration network model based on the test set to obtain motion calibration data; and performing clutter filtering by using singular value decomposition to separate a blood flow signal and a tissue signal of the calibrated data, extracting the blood flow signal, and performing power Doppler blood flow imaging. According to the method, motion artifacts and random noise occurring in the ultrafast ultrasonic imaging process can be effectively restrained, blur between blood vessels is reduced, and the Doppler blood flow imaging contrast ratio is improved.

The invention relates to a portable device and a method for identifying and rapidly detecting particles in insulating oil. The portable device and the method are combined with a micro-flow imaging technology and a Raman spectrum analysis technology. The device can detect the particles in the insulating oil with high precision and high speed and obtain the physical characteristics and chemical components of the particles. Physical characteristics of particles are detected through a microflow imaging technology, and meanwhile chemical component information of the particles is analyzed through a surface enhanced Raman scattering technology. The device has a real-time online monitoring function, data transmission and remote control can be realized through the wireless communication module, and the detection efficiency and the intelligent level are remarkably improved. And the high-resolution CMOS camera and the SERS module are adopted, so that the detection sensitivity and precision are remarkably improved. In combination with Gaussian blur and histogram equalization technologies, noise can be effectively removed, the contrast of the particle image can be enhanced, and the particles can be accurately identified even under the condition of weak light or low contrast.

Mean corpuscular parameter values for a sample, such as a mean corpuscular hemoglobin or mean corpuscular volume for the red blood cells in a sample, can be calculated based on individual cell corpuscular parameter values for the red blood cells in the sample. These values may be obtained using a machine learning algorithm. Such a machine learning algorithm may be trained using sets of training images annotated with transducer derived mean corpuscular parameter values, thereby allowing a flow imaging based analyzer to provide parameter values which may otherwise not be available with that type of analysis tool.

The invention discloses a high-definition ultrasonic blood flow imaging method and a high-definition ultrasonic blood flow imaging system based on space-time multi-scale flexible registration, which are used for removing adverse effects of motion artifacts and realizing high-definition ultrasonic blood flow imaging, and remarkably improving the ultrasonic blood flow imaging quality of moving organs by utilizing a registration method based on a multi-scale space-time similarity matrix. The method specifically comprises the following steps: a preprocessing module M1 is responsible for mapping acquired N frames of ultrasonic echo IQ complex signals X1 frame by frame from a complex field to a real field to construct a matrix Y1; the similarity calculation module M2 is responsible for calculating a multi-scale space-time similarity matrix # imgabs0 # (i = 1, 2,..., W-C + 1, j = 1, 2,..., H-C + 1, k = 1, 2,..., N-1) of Y1 according to different sliding window sizes C; the clustering module M3 is responsible for performing multi-scale adaptive local space-time clustering on the # imgabs 1 # and labeling the IQ complex signal at each position in the X1 as # imgabs 2 # (p = 1, 2, 3,..., P) based on a clustering result; the registration module M4 is responsible for registering the IQ * complex signal corresponding to each label according to a multi-scale time direction similarity distribution feature and a multi-scale intra-class spatial structure feature; and the result output module M5 is responsible for carrying out wall filtering on the IQ complex signal after multi-scale registration and obtaining a high-definition ultrasonic blood flow imaging result W.

The present disclosure describes a device, system, and methods for low-field magnetic resonance (MR) imaging. For example, a method for low-field MR imaging can include projecting a primary static magnetic field in a field of view, projecting a secondary static magnetic field to pre-polarize a first fluid moving toward the field of view, and acquiring a first image of the first fluid in the field of view based on a first RF pulse sequence. The method can further include projecting a tertiary static magnetic field to pre-polarize a second fluid moving toward the field of view and acquiring a second image of the second fluid in the field of view based on a second RF pulse sequence. The first image can be subtracted from the second image to generate a flow image of an object of interest positioned in the field of view.

Systems and methods for removing the bias induced by noise from power Doppler images to achieve improvements of microvessel image contrast are provided. In one example, the noise-induced bias can be suppressed by utilizing the characteristics of uncorrelated noise in the ultrasound image from data acquired or compounded at different transmitting angles. In another example, the noise-induced bias can be suppressed due to the lack of correlation between adjacent ultrasound images. These example implementations may also be combined, as will be described below.

The invention discloses a tissue viscoelasticity and flow multi-scale imaging method and system, and belongs to the technical field of image processing methods.The method comprises the steps that multi-frequency ultrasonic shear wave displacement data of a target tissue is obtained and divided into short-time scale displacement data and long-time scale displacement data; inputting the displacement data into a multi-scale pyramid shear wave displacement feature convolution module for processing to obtain fused shear wave displacement features; carrying out feature extraction and prediction through a multi-scale shear wave speed feature extraction and prediction module, and generating a shear wave speed two-dimensional distribution diagram of the target tissue; and calculating viscoelasticity parameters and flow parameters by using a fractional order model, and generating viscoelasticity and flow image data reflecting the nonlinear mechanical characteristics of the target tissue. According to the method, the imaging precision and stability under low signal-to-noise ratio data are improved, the resolution and robustness of an imaging result and the shear wave velocity imaging performance are improved, the method is suitable for a complex tissue environment, and a technical support is provided for tissue mechanical property analysis.

The biological imaging analysis device includes a staining module configured to stain cells of a biological sample so as to generate stained cells. The present analysis device also includes an illumination module configured to illuminate the stained cells, and the illumination module includes a plurality of pulsed lights. The present analysis device further includes an imaging module configured to capture an image of the stained cells. A method for flow imaging of a biological sample includes flowing a biological sample containing stained cells through an image capture region of a flow cell. The method also includes illuminating the stained cells in the image capture region with a plurality of pulsed lights using the illumination module. The method further includes capturing an image of the stained cells in the image capture region with the imaging module.

The application discloses a method for constructing a 4D FLOW-based hemodynamic evaluation pulmonary embolism prognosis prediction model and application, relates to the medical image technology field, and comprises the following steps: collecting 4D-Flow images of patients who have been diagnosed with pulmonary embolism from medical institutions to obtain image data A; pre-processing the image data A, and dividing the pre-processed image data A into a training set and a verification set according to a proportion; respectively performing imageomic feature extraction, clinical feature extraction and 4D FLOW hemodynamic feature extraction on the training set and the verification set; screening the imageomic features and the clinical features and 4D FLOW hemodynamic detection indexes to obtain key features; and based on the key features, establishing a multi-omics prediction model for pulmonary embolism prognosis prediction, thereby providing a new imaging reference for pulmonary embolism treatment.

The invention relates to a deep learning fundus blood flow imaging method based on OCT amplitude and phase information, and belongs to the field of fundus blood flow imaging. An artificial neural network is used for fusing multi-modal information from OCT, multiple labels from OCTA are used for optimizing the network, and finally high-precision reconstruction of a blood flow image is achieved. Compared with the prior art, the method has the following outstanding advantages that firstly, phase information which is not fully utilized in a traditional method is creatively integrated, and the microvessel recognition sensitivity is remarkably improved through an amplitude-phase bimodal feature collaborative learning mechanism; secondly, a blood flow texture-blood flow position double-label supervised learning strategy is creatively provided, blood vessel position labels are introduced in a function loss stage, the network is assisted to accurately position the blood flow position, the characterization capacity of the network on capillary and other small blood vessel structures is effectively enhanced, and blood flow microcirculation visualization is achieved; and thirdly, blood flow information can be reconstructed by using single OCT scanning data.

The invention discloses application of phosphatidylserine-hydrocortisone microvesicles in preparation of a medicine for treating microvascular regeneration after cerebral apoplexy, and relates to the technical field of biomedicine. According to the microbubble, the blood brain barrier can be accurately opened through the ultrasonic vacuolation technology, the medicine can be delivered in a targeted mode, nerve protection and function improvement are accurately evaluated through ultrasonic super-resolution micro blood flow imaging, and microvessel regeneration is accurately regulated and controlled based on H3K18 lactic acid modification.

An ultrasound diagnostic apparatus includes an ultrasound probe including a transducer array and a diagnostic apparatus main body including a monitor that are wirelessly connected; and a color flow mode, the ultrasound probe includes a transmission and reception circuit that causes the transducer array to transmit an ultrasonic pulse toward a subject, and performs reception focusing processing on a reception signal output from the transducer array that has received an ultrasound echo from the subject to generate a sound ray signal, a flow image information generation unit that generates flow image information consisting of velocity data and at least one of dispersion data or power data on the basis of the sound ray signal, and a probe-side wireless communication circuit that wirelessly transmits the flow image information, and the diagnostic apparatus main body includes a main body-side wireless communication circuit that receives the flow image information wirelessly transmitted from the probe-side wireless communication circuit of the ultrasound probe, a color flow image generation unit that generates a color flow image on the basis of the flow image information, and a display control unit that displays the color flow image, on the monitor.

The invention belongs to the field of part flaw detection, and particularly relates to a pipe fitting inner wall defect profiling TMR array eddy current imaging detection device and method. Conventional eddy current detection channels are small in number and low in detection efficiency, the length of a defect cannot be judged through an impedance diagram, and the conventional eddy current detection channels are difficult to adapt to defect detection of aluminum pipes with different inner diameters within the range of 120-150 mm due to the influence of a probe structure. According to the invention, the defect detection of the inner wall of the aluminum pipe with the inner diameter of not less than 120mm can be realized, the 100% full coverage detection of the machining area of the inner wall can be realized through spiral scanning, the three-dimensional C-scanning imaging of the machining area of the inner wall can be realized through a positioner-portal frame-array eddy current linkage mode, the shape and size of the defect can be intuitively judged, and the detection accuracy is improved. And meanwhile, the high sensitivity characteristic of the TMR sensor can ensure that closed cracks can be detected.

The application provides a kind of based on augmented reality navigation heart blood flow imaging system and navigation image generation method, it is related to biomedical optical imaging technical field, the system includes: laser speckle image acquisition unit according to electrocardiogram ECG signal determines acquisition window, and after the imaging focus is actively compensated based on real-time ranging result in the acquisition window, laser speckle image sequence of heart surface is collected;Navigation image generation unit quantifies the degree of stenosis of blood vessel according to blood flow index, and generates blood flow navigation image in combination with laser speckle image sequence;Navigation image projection unit projects blood flow navigation image to the corresponding blood vessel area of heart surface.The application provides based on augmented reality navigation heart blood flow imaging system and navigation image generation method, not only realizes high-fidelity, quantitative blood flow imaging and intuitive, in situ surgical navigation integration, also significantly improves the precision and safety of coronary artery bypass grafting and other heart surgery.

An ultrasound system (110) can acquire (510) ultrasound data of a vascular structure of a region of interest of a subject from an ultrasound probe (202). The ultrasound system (110) can acquire tracking data of the ultrasound probe (202) from a tracking system (120). The ultrasound system (110) can generate (530) a three-dimensional (3D) vascular model of the vascular structure using the ultrasound data and the tracking data. The ultrasound system (110) can acquire (540) angle-compensated flow information of the vascular structure using a flow imaging technique and the 3D vascular model of the vascular structure. The ultrasound system (110) can display (550) the angle-compensated flow information of the vascular structure.

Systems and methods for determining oxygen consumption using magnetic resonance imaging (MRI) are provided. In some implementations, a method includes steps for applying a pulse sequence using an MRI system to a region of interest (ROI) in a subject, and acquiring magnetic resonance (MR) signal data from the ROI using the MRI system. The method also includes steps for reconstructing the MR signal data using a reconstruction algorithm to derive at least one motion-controlled, blood oxygenation-weighted image, and at least one blood-flow image; and analyzing the at least one motion-resolved, blood oxygenation-weighted image to determine oxygen consumption in the ROI.

The invention discloses an ultrasonic blood flow imaging method and an ultrasonic blood flow imaging system for a moving organ, which are used for removing adverse effects of motion artifacts and realizing real-time dynamic ultrasonic imaging, and remarkably improving the ultrasonic blood flow imaging quality of the moving organ by utilizing a clustering method based on an inter-frame similarity matrix. The method specifically comprises the following steps: a preprocessing module M1 is responsible for mapping acquired N frames of ultrasonic echo IQ complex signals X1 frame by frame from a complex field to a real field to construct a matrix Y1; the similarity calculation module M2 is responsible for calculating a similarity index matrix Rij (i, j = 1, 2,..., N) between the frames of images in the Y1; the clustering module M3 is responsible for performing adaptive clustering on Rij and labeling the IQ complex signal of each frame in the X1 as Zk (k = 1, 2, 3,..., K) based on a clustering result; the wall filtering module M4 is responsible for combining the quasi-static IQ * complex signals corresponding to each label into subsets X1k, and performing wall filtering on each subset X1k to obtain Wk; and the result output module M5 is used for merging all Wk and carrying out inverse process sorting according to a collection timestamp sequence to obtain a real-time high-definition ultrasonic blood flow imaging result of the moving organ.

The application relates to the technical field of optical imaging, in particular to an eye fundus blood flow imaging method and system based on cascade registration and a storage medium, which comprises the following steps: acquiring an eye fundus laser image sequence arranged according to a collection time sequence; based on the eye fundus laser image sequence, a plurality of mutually overlapped local time regions are divided according to the collection time sequence, local registration is performed on the eye fundus laser images in each local time region, and based on the eye fundus laser images after the local registration, a local structure image and a local blood flow image corresponding to the local time region are obtained; global unified registration is performed based on the local structure images, spatial transformation parameters corresponding to the local structure images are determined, and the spatial transformation parameters are synchronously applied to the corresponding local blood flow images to obtain a blood flow image sequence in a unified coordinate system; and fusion processing is performed on the blood flow image sequence in the unified coordinate system to obtain an eye fundus blood flow image. The application can improve the robustness, continuity and definition of eye fundus blood flow imaging.

The invention relates to a pulsed eddy current imaging method of a planar flexible fractal difference measurement eddy current sensor, and belongs to the technical field of nondestructive testing of conductive metal. Compared with the traditional sine excitation, the used pulse excitation can realize the detection of different depth defects of the tested block without using a plurality of different frequency excitation, the detection efficiency is high, the signal conditioning circuit is simple, and the cost is low. Under the condition that a single-frequency excitation high-performance phase-locked amplification technology is not used, the same sensitivity is achieved, and the method has the advantages that the system is simple and easy to implement. By adopting the method, the imaging quality of new features extracted by different cross-correlation algorithms can be quantitatively evaluated, and cross-correlation features and self-correlation features with good signal-to-noise ratios can be distinguished.

The application discloses an imaging position determination method and device, a terminal device and a storage medium. The method comprises the following steps: performing image segmentation processing on a first layer flow image to be identified to obtain a plurality of first particle images; adjusting the size of each of the plurality of first particle images to a preset size to obtain a second particle image corresponding to each of the plurality of first particle images; inputting each of the plurality of second particle images into a target convolutional neural network to obtain a first category corresponding to each of the plurality of second particle images; and determining the relative position relationship between the first layer flow image and a focal point according to the plurality of first categories. The application can determine the relative relationship between the current layer flow image acquisition position and the focal point position by comprehensively considering the shape and blurring degree information of the image, thereby facilitating the calculation of the subsequent focal point position.

The present application discloses an ultrasonic Doppler imaging method, comprising extracting features from an acquired raw blood flow image to obtain vascular features; determining illumination processing parameters for each vascular location based on the vascular features; adjusting the original illumination model using the illumination processing parameters to obtain an illumination model; processing the corresponding vascular locations using the illumination model to obtain reflection results; and fusing each reflection result with a pseudo-color blood flow image corresponding to the raw blood flow image to generate an ultrasonic Doppler image. The ultrasonic Doppler imaging method can effectively reduce the dependence of different blood flow feature processing on illumination model parameters, thereby improving the ultrasonic Doppler blood flow imaging effect. The present application also discloses an ultrasonic Doppler imaging device, apparatus, and computer-readable storage medium, all of which have the aforementioned beneficial effects.

The present disclosure provides a blood flow imaging method, system and storage medium, which obtains a plurality of initial ultrasonic blood flow images and a plurality of target detection groups, filters each target detection group based on a filter set to obtain a corresponding preset number of data groups, obtains a blood flow average speed value corresponding to each target detection group based on the filtered data groups, and generates an ultrasonic blood flow image based on the blood flow average speed value. The present disclosure utilizes a filter set composed of multiple filters with different cutoff frequencies to process ultrasonic echo signals, screens out target data groups corresponding to blood flow regions to generate an ultrasonic blood flow image, effectively reduces high-frequency noise caused by hardware and low-frequency clutter caused by tissue motion, makes the calculated blood flow velocity more close to the true value, and can enhance the blood flow of a certain region in a targeted manner, so as to facilitate the judgment of the degree and starting position of regurgitation.

This invention discloses a method for visualizing and detecting the internal flow field of a MEMS gas chromatograph column based on background schlieren imaging, relating to the fields of microelectromechanical systems (MEMS) and microfluidics. The method includes the following steps: S1, preparation of the MEMS micro gas chromatograph column chip; S2, establishment of the background schlieren optical link; S3, acquisition of the reference image; S4, acquisition of the flow image; S5, extraction of the displacement field; S6, inversion from displacement to refractive index / density gradient; S7, reconstruction and visualization output of flow field quantities such as velocity / pressure; S8, localization of local defects and updating of structural parameters; S9, experimental-simulation closed-loop iterative optimization. This invention applies BOS quantitative visualization technology to the internal diagnostics of MEMS-grade chromatographic columns, enabling rapid closed-loop correction and iteration of CFD models, reducing theoretical plate height, increasing the number of theoretical plates, reducing pressure drop, and increasing peak capacity. This provides a reliable experimental verification and optimization method for next-generation high-resolution, low-power, miniaturized aerospace-grade chromatographic columns.

The present application relates to the technical field of image recognition, in particular to a security check flow image adaptive judgment method and system based on artificial intelligence, wherein the security check flow image adaptive judgment method based on artificial intelligence comprises: determining a candidate object and a candidate shape-color combination; determining a shape-color combination similar performance index; determining a superimposed artifact interference direction; determining a judgment weight correction demand index based on an original model confidence, the shape-color combination similar performance index and the superimposed artifact interference direction; and correcting the judgment weight. The present application combines the shape-color combination recognition of the security check flow image with the conveyor belt flow imaging process, distinguishes the real prohibited structure, the edge offset structure and the superimposed artifact structure by analyzing the mismatch relationship between the conveyor belt running state and the line scanning sampling rhythm, and makes the intelligent judgment result be able to trace back to the real structure support or the artifact interference source under the flow imaging scene.

The embodiment of the invention provides a multi-dimensional data processing method and system for emergency data quality control analysis. The method comprises the following steps: acquiring photoacoustic blood flow imaging data and emergency treatment parameters of a patient, and generating multi-channel time-space associated data; constructing a laser pulse energy density correction module, generating an ultrasonic receiver sensitivity adjustment parameter through a dynamic coupling mechanism of the pain index grade and the capillary density distribution, and synchronously establishing a phase synchronous compensation network of the laser pulse repetition frequency and the heart rate variability; generating a real-time three-dimensional photoacoustic blood flow dynamic image, and dividing a difference region into a high-perfusion core region, a transition region and a low-perfusion marginal region based on blood flow velocity gradient mutation point spatial distribution; and generating an emergency treatment quality control score based on the dynamic correlation function, the mapping relation and the coupling coefficient. According to the technical scheme provided by the embodiment of the invention, real-time three-dimensional blood flow visualization and accurate partition diagnosis of mammary gland lesions are realized, and the pathological relevance of emergency treatment quality control scores is remarkably improved.

The present system employs optical coherence tomography (OCT) or optical coherence microscopy (OCM) systems, including ultra-high resolution Gabor-domain optical coherence microscopy (GD-OCM), into a 3D flow imaging technique. This technique models the repeated scans as Gaussian latent variables, with the common variance representing both static tissue structure and dynamic blood flow, and the anisotropic unique variance representing tissue motion in specific frames. Since the motion generated variance is independent from that of the structure or the flow, by iteratively maximizing the combined log-likelihood probability of these two variances modeled through exploratory factor analysis, the unique variance (or the tissue motion) may be largely excluded. In the common variance, the dynamic blood flow may be separated from the static tissue structure, by integrating the factors that represent the relatively low levels of correlation. Compared to a direct differentiation of OCT or OCM scans, the present flow imaging algorithm improves the visualization of capillaries with reduced motion artifacts.

The present disclosure relates to ultrasound-based strategies and techniques that are specially designed for time-resolved simultaneous cardiac tissue visualization and intracardiac flow instability mapping. First, to achieve high-resolution tissues images while also acquiring flow data, we devised an acquisition scheme which consists of two batches. The first batch is dedicated to tissue imaging, where we transmit a series of diverging waves emitted from different virtual source locations. These pulses have a single pulse-cycle to optimize axial resolution and are coherently compounded for improving lateral resolution. This paradigm generates tissue images with an improved resolution, allowing for real-time guidance at frame rates up to 50 fps. The second batch is dedicated for flow imaging where all diverging waves are transmitted from the same virtual source location. These flow pulses have a 5-cycle pulse length for improved flow signal. The length of this batch can be adjusted, but our experiments use a length of 64. The final transmission scheme alternates between the tissue batch and flow batch.

The present invention relates to the field of ultrasounds and imagining of the coronary blood flow of the heart. Patients with coronary microvascular dysfunction (CMD) have poor prognostic with significantly higher rates of cardiovascular events, including hospitalization for heart failure, sudden cardiac death, and myocardial infarction (MI). Despite the urgent clinical need, there are no non-ionizing and non-invasive techniques available in clinic to directly visualize the coronary microvasculature and assess the local coronary microvascular system. Flow imaging remains a difficult task to perform in the heart because of the fast movements of this organ. In order to overcome the limitations of actual imaging methods for the coronary blood flow, the inventors proposed an ultrasound ultrafast imaging method that automatically detect the time periods in which the myocardium velocity is low and estimate the coronary flow velocity and the tissue velocity from the same data acquisition.