54 results about "Vascular imaging" patented technology

The invention relates to the technical field of image enhancement, in particular to an angiocardiography high-precision angiography enhancement method and system. The method comprises the steps that an ECG curve of electrocardiosignals before and after contrast agent injection of a patient and a blood vessel image are obtained; determining the compressible degree of each wave band according to the change of different wave bands and the change of the heart rate in the QT interval before and after the contrast agent is injected; determining the increment duration of each wave band in combination with the standard duration, the actual duration and the compressible degree; performing standardized adjustment on the ECG time phase of each frame of blood vessel image in combination with the increment time length and the actual time length of each wave band to obtain a standard time phase; determining a mask matched with each negative film according to the standard time phases of the negative films and the masks; and carrying out image subtraction on each negative film and the matched mask, and carrying out angiography enhancement processing. The blood vessel imaging precision after digital subtraction can be improved, the blood vessel artifact phenomenon is reduced, and the blood vessel imaging precision and reliability are enhanced.

The present disclosure provides to generate ground truth data for training a machine learning (ML) model to infer pressure information (e.g., a pressure curve, a pressure ratio, or the like) for a cardiac artery from border segmentations generated from images of the cardiac artery. The ground truth data can comprise vessel and / or lumen segmentations for several cardiac arteries and associated pressure information for the cardiac arteries. The vessel and / or lumen segmentations can be generated from images from different image modalities (e.g., IVUS, angiographic, CT, etc.). Further, some of the associated pressure information can be based on measured pressure information (e.g., using a pressure sensing catheter) while other associated pressure information can be derived from the vessel and / or lumen border segmentations using numerical analysis techniques (e.g., CFD, or the like).

The invention relates to the technical field of medical instruments, in particular to a painless blood vessel puncture device with an intelligent positioning function, which comprises a base, a blood vessel imaging instrument is arranged on the base, and an auxiliary mechanism is arranged on the base; the auxiliary mechanism comprises an annular mounting frame, six stretching pieces are evenly arranged in the mounting frame in the circumferential direction, each stretching piece comprises a pull rod, a telescopic belt is arranged in the mounting frame and arranged on the pull rod of the six stretching pieces in a sleeving mode, so that the telescopic belt is hexagonal, the pull rod is connected with a separation piece, and the separation piece is connected with a pull rod. The separating piece can drive the pull rod to reciprocate in the axial direction of the mounting frame, the pull rod is connected with a pressing piece, and the pressing piece can drive the pull rod to reciprocate in the radial direction of the mounting frame; the stretching piece on the top side is connected with a liquid spraying mechanism, the liquid spraying mechanism comprises a disinfection piece and a pain relieving piece, and disinfection alcohol is contained in the disinfection piece.

The application provides a three-dimensional reconstruction and quantitative analysis consistency control method and system of multi-center CT blood vessel imaging data, an electronic device and a storage medium, and relates to the technical field of medical image processing. The method comprises the following steps: first, synchronously acquiring original projection data of multi-center CT blood vessel imaging, blood vessel center line topological data and blood vessel respiratory motion displacement data, generating a blood vessel deformation correction matrix based on the respiratory motion displacement data, and dynamically registering the blood vessel center line data by using the matrix to obtain corrected center line data; then, inputting the corrected center line data and the original projection data into a multi-modal feature fusion network for three-dimensional reconstruction to generate an initial blood vessel model; then, performing morphological parameter quantitative analysis on the initial model; finally, comparing the analysis result with a clinical standard and adjusting the model parameters to output a target blood vessel three-dimensional model. The application improves the geometric accuracy and clinical applicability of the blood vessel model reconstruction.

The invention relates to a manufacturing method of a bionic blood vessel model and the bionic blood vessel model.The manufacturing method of the bionic blood vessel model comprises the steps that a three-dimensional computer model of a blood vessel lumen is constructed according to blood vessel image data; according to a three-dimensional computer model of a blood vessel lumen, a water-soluble polyvinyl alcohol material is adopted to manufacture a water-soluble inner core through a 3D printing technology; the water-soluble inner core is subjected to operation for N times or less, wherein N is larger than or equal to 1; the outer surface of the water-soluble inner core is evenly covered with a polyvinyl alcohol solution; the water-soluble inner core covered with the polyvinyl alcohol solution is subjected to at least one time of freeze thawing treatment, so that the polyvinyl alcohol solution is solidified into polyvinyl alcohol hydrogel; after N times of operation are completed, the water-soluble inner core covered with the polyvinyl alcohol hydrogel is soaked in ultrapure water so that the water-soluble inner core can be dissolved, and therefore the bionic blood vessel model with the good shape and mechanical property is obtained.

This invention discloses a fluorescence-enhancing nanoparticle, its preparation method, and its applications, relating to the fields of organic fluorescent molecules and bioimaging technology. The nanoparticle comprises: NIR-II fluorescent molecules and an amphiphilic polymer encapsulating the NIR-II fluorescent molecules; the amphiphilic polymer has a hydrophilic segment and a rigid hydrophobic segment. The nanoparticle of this invention, based on "carrier microenvironment engineering," utilizes the rigid confinement and interfacial isolation provided by the amphiphilic polymer with the rigid hydrophobic segment for dual brightening, serving as a universal brightening platform applicable to various NIR-II fluorescent molecules. This nanoparticle can significantly improve aqueous phase quantum yield, enhance contrast and resolution in in vivo vascular imaging, improve deep tissue penetration, increase imaging sensitivity, and facilitate detection under low signal conditions. It also exhibits good stability and biocompatibility, supporting lesion imaging and intraoperative navigation applications.

This invention discloses an intelligent PICC catheter and positioning system for tumor chemotherapy, belonging to the field of biomedical engineering technology. This invention addresses the problem of inaccurate puncture due to the inherent subjectivity in puncture point selection in existing technologies. By assessing the importance of vascular imaging features and blood flow parameters, it can identify the features most influential on predicting puncture results, thereby reducing model complexity and improving model efficiency and generalization ability. Furthermore, by weighting the input data according to feature importance, the random forest model focuses more on important features, thus improving the accuracy and reliability of model predictions. Through the collaborative work of multiple modules, the positioning system is more accurate and efficient in recommending the optimal puncture point, effectively improving the puncture success rate, reducing the risk of complications, providing strong decision support for medical staff, and enhancing the patient's treatment experience and safety.

The application relates to an identification method and device, computer equipment and a storage medium. The method comprises the following steps: obtaining a blood vessel image of an eye to be examined, the blood vessel image being generated by optical coherence tomography blood vessel imaging; obtaining statistical features of a macular region in the blood vessel image; and identifying a non-perfusion region in the blood vessel image based on the statistical features. The method can effectively improve the flexibility of identifying the non-perfusion region.

A vessel imaging sequence including plurality of vessel imaging frames and a corresponding ECG signal are generated by encoding, using a first encoder, an input vessel imaging sequence to generate a plurality of vessel latent space vectors, each vessel latent space vector corresponding to an input vessel imaging frame of the input vessel imaging sequence, encoding, using a second encoder, an input ECG signal to generate a plurality of ECG latent space vectors, decoding, using a first decoder, the plurality of vessel latent space vectors and the plurality of ECG latent space vectors to generate the vessel imaging sequence and decoding, using a second decoder, the vessel latent space vector and the ECG latent space vector to generate the ECG signal.

This application provides an adaptive infrared vascular imaging enhancement method and apparatus based on image entropy feedback. It achieves precise adaptive adjustment of infrared emission power through local information entropy calculation and a proportional-integral-differential controller. An enhancement mechanism is constructed, combining multi-scale Gaussian smoothing and Hessian matrix eigenvalue analysis to establish a reliable vascular response extraction strategy. Structural analysis optimization is introduced, iteratively refining skeleton extraction and cross-point calculation to ensure continuous improvement in vascular cross-point localization. This method effectively addresses the shortcomings of traditional techniques in exposure adaptation, vascular enhancement, and topology analysis, providing technical support for infrared vascular imaging-assisted diagnosis.

This application relates to a medical image registration method, system, computer device, storage medium, and computer program product. The method includes: acquiring a first vascular feature corresponding to a preoperative medical image; acquiring an intraoperative medical image captured by a vascular imaging device and identifying a second vascular feature in the intraoperative medical image; calculating a first registration relationship between the preoperative medical image and the intraoperative medical image based on the first and second vascular features; acquiring a second registration relationship between the image coordinate system of the vascular imaging device and the world coordinate system; and generating operation navigation information based on the first and second registration relationships. This method improves accuracy through vascular registration, and the use of a vascular imaging device avoids incisions and minimizes harm to the patient.

The application belongs to the technical field of ultrasonic blood vessel imaging, and particularly relates to a peripheral blood vessel imaging method and system based on ultrasonic tomography and a storage medium. An ultrasonic tomography system is used to collect images of a to-be-measured part, and a plurality of three-dimensional cross-sectional image sequences are obtained. A pulse signal is synchronously collected. A target detection neural network is used to process the three-dimensional cross-sectional image sequences, and preliminary observation values of blood vessel positions are output. An optimal state estimation is sequentially performed on the blood vessel positions of each three-dimensional cross-sectional image based on a Kalman filtering algorithm, and optimal blood vessel position estimations of each frame are output. The preliminary observation values of the blood vessel positions are taken as observation values of the Kalman filtering, and a state transition equation of the Kalman filtering algorithm is constructed according to the blood vessel positions, blood flow velocities and the pulse signal. According to the optimized three-dimensional cross-sectional image sequences, a dynamic three-dimensional blood vessel model is reconstructed. The application realizes dynamic artifact suppression and state smoothing based on the pulse signal, and provides image clarity.

The invention provides a vascular embolism recurrence risk prediction method and device and electronic equipment. The vascular embolism recurrence risk prediction method comprises the steps that multi-modal data of a patient at each time point is acquired, the multi-modal data of each time point comprises at least two modal data of a vascular image, a medical text, biochemical test information and a physiological signal, and the multi-modal data of at least one time point comprises the vascular image; determining a first feature and a second feature according to the multi-modal data of each time point, the first feature being obtained by analyzing correlation between the modal data and reflecting a recurrence risk level of the patient at the current time point, and the second feature being obtained by analyzing a change rule of the multi-modal data along with time and reflecting a recurrence risk evolution trend of the patient; the vascular embolism recurrence risk of the patient in the future period is predicted according to the first feature and the second feature, and the prediction accuracy of the vascular embolism recurrence risk can be improved.

The present invention provides an automated system (100) and a method (300) for performing blood vessel imaging, 3D reconstruction and assisted intrusion using machine learning techniques comprising an imaging module (102) incorporating plurality of monochrome infrared stereo camera (104) with Near-Infrared Light (NIR) illumination (106); a robotic arm (108) to perform assisted intrusion with the feedback of a 3D reconstructed blood vessel; and a control unit (110) incorporating plurality of microprocessors with neural network to employ machine learning to control and automate 3D reconstruction and intrusion of blood vessel using machine learning techniques in real-time, wherein the neural network comprises of an image registration module, image library construction module, a training module, and a 3D reconstruction module.

The application relates to a blood vessel imaging method based on normalized time-varying intensity sequence similarity. The blood vessel imaging method obtains two interference spectrum signals through twice data acquisition of the same data acquisition point of a sample, sequentially carries out Fourier transform, amplitude taking, direct current removing and normalization on the two interference spectrum signals to obtain two normalized time-varying intensity sequences, carries out cross-correlation function operation on the two normalized time-varying intensity sequences to distinguish a blood vessel region and a tissue region, and further obtains a contrast image of the blood vessel region. The method can remove body motion artifacts without external additional hardware and / or software, has self-sufficiency against body motion artifacts, can reduce the complexity and cost of an OCT system, and improves the efficiency of sample data processing.

The application discloses a kind of human peripheral blood vessel photoacoustic three-dimensional imaging device and imaging method thereof, belong to blood vessel imaging field.The application provides detailed blood vessel structure and blood flow dynamic information by high resolution and functional monitoring ability of photoacoustic imaging, promote early identification and treatment effect evaluation to common pathological changes such as diabetic foot and peripheral arterial disease;Meanwhile, the application adopts mechanical system, and the detection front end of higher quality can be carried and stably operated, to obtain better photoacoustic imaging result;The application has highly stable precision scanning imaging mode, and various imaging modes are convenient for clinical application;Through the arrangement of imaging tank and its lifting structure, it is ensured that the switching of imaging mode can be applied in limited space, so as to be suitable for gantry type three-dimensional mobile device layout.The application is expected to promote the portability of equipment, reduce equipment development cost, be widely applied in clinical practice and community medical treatment, and improve disease management level.

Disclosed is a medical electronic wristband, comprising a functional member (1) and a wristband body (2). The functional member (1) comprises a housing (11) fixed on the wristband body (2), a touch screen (12) and a blood vessel imager (13) respectively arranged on a top surface and a front side of the housing (11), and a controller and a power supply separately mounted in an inner cavity of the housing (11). The touch screen (12) and the blood vessel imager (13) are separately electrically connected to the controller and are powered by the power supply. A rear side of the housing (11) is provided with an opening in communication with the inner cavity, and the opening is closed by a sealing plate (111). The controller is located in the inner cavity. The controller comprises a processing module as well as a storage module, a wireless communication module, and a GPS positioning module separately electrically connected to the processing module. The medical electronic wristband can automatically display a two-dimensional code or a barcode of a patient, and has the functions of positioning, heart rate detection, and blood vessel imaging.

The application provides a blood vessel imaging method, device, electronic equipment and storage medium. The blood vessel imaging method provided by the application comprises the following steps: acquiring a filling image and a mask image matched with the filling image. Then, for each frame of filling image, a correction control point is dynamically determined on the mask image according to the size relationship between the difference between the frame of filling image and the mask image and a first preset threshold value; then, the mask image is corrected according to the correction control point to obtain a corrected mask image corresponding to the frame of filling image. Finally, a blood vessel subtraction image is obtained according to each frame of filling image and the corrected mask image corresponding to the frame of filling image. The application can fully remove motion artifacts and improve the image quality of the blood vessel subtraction image.

The application relates to a method for determining inversion time in blood vessel imaging, a magnetic resonance imaging method and a device. The method for determining inversion time in blood vessel imaging comprises the following steps: selecting an imaging position from a blood vessel imaging area; at the imaging position, collecting at least two blood vessel images with different inversion times by using an inversion time searching technology; obtaining an inversion time corresponding to a blood vessel image with optimal blood vessel display; and determining a time point for setting a longitudinal magnetization to zero according to the inversion time corresponding to the blood vessel image with optimal blood vessel display. The magnetic resonance imaging method comprises the following steps: determining an inversion time based on the method for determining inversion time in blood vessel imaging; applying a regional selection inversion pulse at an imaging position; and applying a target imaging sequence at the imaging position after the inversion time to obtain a target magnetic resonance image. The method can optimize the inversion time, thereby obtaining optimal blood vessel display.

The application provides a blood vessel image processing method and device based on a neural network. The method comprises the following steps: obtaining a blood vessel image of an eye to be examined, dividing the blood vessel image into a plurality of blood vessel sub-images based on the input image size of a denoising model, and the blood vessel image of the eye to be examined is generated by optical coherence tomography blood vessel imaging; inputting the plurality of blood vessel sub-images into the trained denoising model, and outputting a plurality of denoised blood vessel sub-images; and obtaining a fused denoised blood vessel image based on the plurality of denoised blood vessel sub-images. In this way, a first training blood vessel image can be obtained by using a first scanning protocol with a smaller data acquisition range parameter, thereby avoiding the problem that a human eye cannot withstand long-time acquisition, so that a first training image with a higher signal-to-noise ratio can be obtained, and the prediction result of the denoising model trained by using the first training image also has a higher signal-to-noise ratio.

This invention relates to the field of simulation training, specifically a simulator and a simulator-based training method for adrenal vein blood sampling. The method includes adjusting the simulator and simulated surgical instruments to an initial preparation state; training personnel performing simulated surgical procedures in the simulator in this initial preparation state; recording the simulated surgical procedures to obtain a training personnel simulation process record; acquiring an expert simulation process record; and analyzing the training performance of the training personnel corresponding to the expert simulation process record based on the expert simulation process record. This invention can improve the efficiency of training for adrenal vein blood sampling using simulated DSA-guided vascular imaging technology.

An X-ray contrast agent (K) is described. The X-ray contrast agent (K) has an X-ray absorption, a variation of the X-ray absorption between at least two different X-ray photon energies (E(1), E(2)) being significantly different from a variation of the X-ray absorption of calcium between at least two different X-ray photon energies (E(1), E(2)). An X-ray imaging method is also described. Furthermore, an image reconstruction apparatus (50) is described. An X-ray imaging system (60) is also described.

Disclosed are methods and systems for phase-stabilized complex decorrelation (PSCD) optical coherence tomography (OCT) angiography (OCTA). In embodiments, a PSCD OCTA method includes performing phase stabilization on a complex-valued OCT data set to generate a phase-stabilized OCT dataset. The method further includes performing a complex decorrelation on the phase-stabilized OCT dataset to generate an OCTA dataset. One or more OCTA images may be generated based on the OCTA dataset. Other embodiments may be described and claimed.

The present disclosure provides to generate ground truth data for training a machine learning (ML) model to infer pressure information (e.g., a pressure curve, a pressure ratio, or the like) for a cardiac artery from border segmentations generated from images of the cardiac artery. The ground truth data can comprise vessel and / or lumen segmentations for several cardiac arteries and associated pressure information for the cardiac arteries. The vessel and / or lumen segmentations can be generated from images from different image modalities (e.g., IVUS, angiographic, CT, etc.). Further, some of the associated pressure information can be based on measured pressure information (e.g., using a pressure sensing catheter) while other associated pressure information can be derived from the vessel and / or lumen border segmentations using numerical analysis techniques (e.g., CFD, or the like).

The application provides a piezoelectric MEMS ultrasonic transducer simulating a Langevin vibrator and a preparation method thereof, which comprises, from bottom to top, a first silicon layer, a first electrode layer, a piezoelectric layer, a second electrode layer and a second silicon layer; wherein: a plurality of array units are arranged on the first silicon layer, the array units are separated by grooves, the grooves penetrate the piezoelectric layer and the second electrode layer, and the second electrode layer is divided into a plurality of second electrode layer units by the grooves; the second silicon layer comprises a plurality of stepped protruding structures, and the protruding structures are respectively located on the second electrode layer units; the protruding structure comprises coaxially arranged upper and lower second silicon layers, and the upper second silicon layer is away from the second electrode layer unit; and the area of the upper second silicon layer is smaller than that of the lower second silicon layer. 33 The piezoelectric MEMS ultrasonic transducer of the application can be used in small-size high-precision occasions such as intracardiac blood vessel imaging and fingerprint identification.

An information processing device, an information processing method, and a non-transitory computer-readable medium are disclosed. The information processing device includes a processor configured to acquire transverse tomographic images of a plurality of frames obtained by imaging a blood vessel of a patient, and calculate plaque burden in each of the frames by inputting the acquired transverse tomographic image of each of the frames to a model that has learned to calculate plaque burden in response to the transverse tomographic image inputted, and a display unit configured to display a longitudinal tomographic image based on the transverse tomographic images of the plurality of frames and a first object that is an object displayed in correlation with the longitudinal tomographic image and represents magnitude of the plaque burden at each position of the longitudinal tomographic images along an axial direction of the blood vessel.

The invention provides a super-resolution ultrasonic imaging method and system based on uncertainty density estimation, and belongs to the technical field of medical image processing and computer vision. The invention aims to solve the problems of limited spatial resolution, long imaging time, dependence on pairing data and the like in the existing ultrasonic microvascular imaging technology. According to the method, a deep learning network is designed, block consistency regularization is introduced to promote cross-regional information interaction, a discriminator-guided semantic consistency perception alignment feature is utilized to suppress a false structure, and Dirichlet uncertainty frequency domain density estimation is combined to constrain cross-domain mapping of a high information density region. According to the method, fast conversion from the energy Doppler image to the super-resolution ultrasonic positioning microscope image can be realized without data pairing, the processing time of a single image is only 13.1 milliseconds, the imaging efficiency and the authenticity of a vascular structure are remarkably improved, and the method has relatively high clinical applicability.

This application relates to a method, system, device, and medium for predicting the trend of vascular crisis in replanted fingers. The method includes: acquiring clinical pathological index data, infrared monitoring image sequences, and visual monitoring image sequences; inputting the visual monitoring image sequences into a neural network model for appearance image feature extraction to extract a feature sequence of the replanted finger's filling state and a feature sequence of the replanted finger's swelling progression; inputting the infrared monitoring image sequences into a neural network model for vascular imaging feature extraction to extract a feature sequence of blood supply patency; concatenating the blood supply patency feature sequence, the replanted finger's filling state feature sequence, and the replanted finger's swelling progression feature sequence to obtain a multi-source image monitoring feature sequence; and inputting the multi-source image monitoring feature sequence and clinical pathological index data into a vascular crisis trend prediction model to generate a vascular crisis level prediction sequence. This method can identify the filling state and swelling progression of the replanted finger, enabling dynamic trend prediction of the risk of crisis.

The invention discloses a blood vessel image recognition device and a using method thereof, and belongs to the technical field of infrared image recognition devices.The blood vessel image recognition device comprises a base, a case, a support and an infrared camera, an arm and palm containing groove is formed in the top of the base, and the case is fixed to one side wall of the base. Through the electric winding mechanism, the friction braking mechanism, the transmission mechanism and the control system which are integrated in the case, the finger limiting belt and the arm limiting belt can be automatically tightened, and the tension is monitored in real time through the chest expander. And when a preset target value is reached, automatic stopping is achieved, and the consistency and adjustability of the fixing force are achieved. Therefore, reliable fixation of the hand of a patient is ensured, movement during puncture is prevented, the vein filling effect similar to that of a manual binding rubber belt can be achieved through tightening of the arm limiting belt, and stable fixation and angiography can be completed at the same time in combination with an infrared camera.