21 results about "Elastography" patented technology

The invention relates to the field of medical image analysis, in particular to a deep learning prediction system and method based on multi-modal thyroid cancer lymph node metastasis, and the system comprises a data collection module, a preprocessing module, a nodule segmentation module, a feature extraction module, a feature fusion module, a metastasis prediction module, an interpretability analysis module and a result display module. An ultrasonic image, an elastic imaging image, an ultra-micro blood flow image and clinical index data of a patient are integrated, an improved U-Net algorithm is used for precise segmentation of a thyroid nodule region, a multi-branch deep network is used for extracting multi-modal features, a dynamic weight fusion algorithm is used for integrating the features, and the accuracy of the thyroid nodule region is improved. According to the method, the thyroid cancer lymph node metastasis state (non-metastasis, central region metastasis or lateral neck metastasis) is predicted, meanwhile, a two-dimensional interpretability framework of Grad-CAM activation diagram and SHAP value contribution degree analysis is introduced, an intuitive prediction basis is provided for doctors, and the thyroid cancer lymph node metastasis prediction accuracy is remarkably improved.

The invention relates to a lung elastography and AI-assisted pulmonary nodule benign and malignant identification system and a medium, and solves the problem of limited identification accuracy of a traditional iconography examination method. The system comprises at least one processor which is configured to realize the lung elastography and AI-assisted pulmonary nodule benign and malignant identification method when executing a computer program, and the specific steps are as follows: inputting obtained comprehensive consistency indexes, individual characteristics of patients and key information in multi-source data into a pre-trained correlation model; outputting the prediction probability that the case pulmonary nodule is malignant; based on the prediction probability and the initial confidence coefficient, adopting a preset confidence coefficient adjustment algorithm to calculate the adjusted confidence coefficient; and displaying the pulmonary nodule benign and malignant judgment result, the confidence coefficient, the multi-physical field simulation result and the comprehensive consistency index on a display terminal in a multi-modal mode. The method has the advantages that the accuracy of identifying benign and malignant pulmonary nodules is improved, and the limitation of a traditional method is made up.

The present application relates to the technical field of medical elastic imaging and material multi-scale mechanical measurement, and particularly discloses an elastic imaging method and system based on a scattering displacement gradient field, which comprises the following steps: generating a scattering displacement field by arranging an excitation device around a target material, measuring an out-of-plane displacement gradient field by using transverse shear interference imaging, selecting a single-frame instantaneous gradient field or a frequency-domain gradient field obtained by time-frequency domain Fourier transform as a target field; obtaining a global shear wave velocity distribution by adaptive sliding window interception, two-dimensional autocorrelation calculation and Rayleigh wave spatial autocorrelation theoretical model fitting, and then reconstructing viscoelastic modulus distribution by using an inversion algorithm. The present application supports single-frame scattering displacement gradient field inversion elastic imaging, can be used without high-frame-rate equipment, has strong anti-environmental vibration interference ability and high system stability, is suitable for scenes with poor isolation conditions, has low cost, high efficiency and high measurement precision, and can meet the requirements of medical clinical diagnosis and material multi-scale mechanical measurement.

The invention provides a method and device for displaying an artery plaque elastic characteristic curve by medical color ultrasound equipment, and the method comprises the steps: obtaining a plaque contour line of a target region determined based on elastography in the color ultrasound equipment, and tracking the position of the plaque contour line; dividing region blocks of the plaque contour line according to a position tracking result; performing internal filling on the plaque contour line based on a division result; pixel block division is carried out on the plaque contour line after internal filling is completed, and a pixel block division matrix is obtained; extracting elastic data of each pixel block, and analyzing the elastic data of the target area in the plaque contour line according to the area blocks and the pixel blocks to obtain elastic data features and curve features; screening out optimal elastic data and an optimal curve according to the elastic data characteristics and the curve characteristics; and displaying the optimal elasticity data and the optimal curve in a screen. By visually and quantitatively displaying the local information of the plaque, a user can visually compare the elasticity information of different local areas of the plaque.

Various methods and systems are provided for cervix elastographic analysis. In one embodiment, the method comprises acquiring an ultrasound scene comprising a plurality of frames, generating a first loss image for the plurality of frames, selecting a background and a foreground of the ultrasound scene based on the first loss image, and generating a softness ratio from the selected background and foreground.

This invention provides a transvaginal ultrasound probe equipped with a pressure assist device that enables standardized control of pressure depth and force in cervical elastography, thereby improving the objectivity and reproducibility of manual pressure operations. [Solution] The device comprises a probe body and a pressure assist device that is detachably attached to the outer circumference of its columnar handle portion 12. The pressure assist device includes a fixed base 1, a handheld support assembly, a depth adjustment mechanism, and a pressure state display mechanism. A finger rest recess is provided on the back surface of the handle portion of the handheld support assembly to guide the direction of force when gripping. The depth adjustment mechanism allows the insertion depth of the probe to be set in advance by a guide slide rod 9 and a limit ring 8. The pressure state display mechanism converts the pressurizing force into a visible displacement scale by an elastic compensation spring and a displacement transmission rod. Conventionally, manual pressurizing operations using transvaginal ultrasound probes have been problematic because they depend on the operator's subjectivity and have low reproducibility of the pressurizing direction and force.

This application provides a multimodal ultrasound intelligent identification method and precision diagnosis system for thyroid lesions. The method determines image data blocks with multimodal spatial registration and grayscale-contrast temporal alignment. Based on the grayscale ultrasound image sequence in the image data blocks, a first depth feature map of the target user's thyroid region is determined. A second depth feature map of the target user's thyroid region is determined based on the elastography map in the image data blocks. The hemodynamic spatial distribution characteristics of the parametric map in the image data blocks are captured to determine a third depth feature map of the target user's thyroid region. Cross-modal fusion is performed on the first, second, and third depth feature maps, and then the lesion segmentation mask, benign / malignant probability value, and risk classification of the target user's thyroid region are inferred and output in parallel. Using the scheme of this application, high-precision spatiotemporal alignment and cross-modal depth feature fusion of multimodal ultrasound images can be achieved to complete end-to-end intelligent identification of thyroid lesions.

An elastography method implemented by an elastography device, the method including obtaining a respiratory signal related to a respiratory activity of a subject; and acquiring a plurality of measurements of a mechanical property of a region of a body of the subject, the region being a part of a liver or a spleen of the subject, wherein each measurement among at least a subset of the plurality of measurements of the mechanical property is acquired at a same moment of a respective respiratory cycle determined from the respiratory signal.

Magnetic resonance and ultrasound methods can produce estimates of full rank-4 elasticity tensors (E-tensors) using suitable constraints. E-tensor estimates can be based on E-tensor symmetry conditions and a suitable E-tensor selected from among a set of E-tensors calculated using different symmetry constraints. Displacement fields used in E-tensor calculations can be noise reduced using compatibility conditions. With the selected E-tensor, various stains that are rotation invariant can be computed. In one example, an E-tensor for an in vivo brain is computed using the mechanical disturbance associated with cardiac pulsations. The selected E-tensor and associated stains, physiological disorders such as Alzheimer's disease and traumatic brain injury (TBI) and even neural activation may be more readily detected than with conventional methods that do not use the full E-tensor.

The application discloses a kind of based on photoacoustic viscoelasticity imaging's diabetic foot microvessel calcification evaluation system and method, the method includes: pulsed laser of laser is emitted by focusing objective lens, is irradiated on the foot surface tissue of diabetic patient and generates photoacoustic signal;Using phase-locked amplifier extraction photoacoustic signal's phase delay;Computer control motor scans foot surface tissue and saves photoacoustic signal data and photoacoustic signal's phase delay data.Photoacoustic signal is processed to extract the time width information of wave crest, the wave crest time width data of each point photoacoustic signal and phase delay data are respectively mapped to image in the form of gray value, and the image about the elasticity and viscoelasticity of diabetic foot surface tissue is reconstructed.Calcification threshold and inflammation threshold are set, and the imaging area is divided into different elastic regions using threshold segmentation method, and then the vascular calcification of diabetic foot is evaluated using viscoelasticity parameters, to detect whether there is calcification and inflammation in the microvessel of diabetic foot.

This invention discloses a method and device for anterior segment Sham elastography. This invention combines micron-level spatial resolution, high cost-effectiveness, and clinical operability. It can obtain quantitative elastic distribution of anterior segment tissues such as the cornea in vivo and in situ, providing reliable biomechanical basis for ophthalmic diagnosis and treatment scenarios such as early screening of keratoconus, refractive surgery planning, and glaucoma risk assessment. Compared with the prior art, the system structure of this invention is simplified, the cost is significantly reduced, and it has higher resolution and achieves truly non-contact measurement.

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The application relates to a high-frame-rate elastic imaging method and system. The method comprises the following steps: based on a specified frame frequency F, a target imaging area is regionally divided to form F sub-ROI areas which are sequentially arranged and meet the effective propagation of shear waves; during elastic imaging, at least one imaging frame rate expansion process is performed, wherein each time the imaging frame rate expansion process is performed, the following steps are included: two sequentially generated imaging area shear wave velocity sets are acquired, and velocity splicing processing is performed on the two acquired imaging area shear wave velocity sets to form at least F target area shear wave velocity information, based on each target area shear wave velocity information, a shear wave velocity image corresponding to the target imaging area is generated, and the generated shear wave velocity image is synchronously displayed with a B-ultrasound image. The application can effectively improve the imaging frame rate without increasing interpolation data.

The invention discloses an intestinal tract ultrasound method for evaluating ulcerative colitis disease activity, which comprises the following steps: acquiring a B-mode ultrasound image of a target colon intestinal segment of a subject, and identifying and positioning the target intestinal segment based on the B-mode image; performing ultrasonic viscoelastic imaging on the positioned target colon-intestinal segment, and synchronously acquiring and displaying a viscoelastic data graph and the B-mode image of the target colon-intestinal segment; extracting at least one viscoelasticity parameter reflecting the mechanical property of the tissue from the viscoelasticity data graph; and determining a disease activity level of the ulcerative colitis based on the at least one viscoelastic parameter.

The invention relates to the technical field of medical elastography and material multi-scale mechanical measurement, in particular to an elastography method and system based on a scattering displacement gradient field, and the method comprises the following steps: arranging an excitation device at the periphery of a target material to generate the scattering displacement field, and measuring an out-of-plane displacement gradient field by adopting lateral shear interference imaging; selecting a single-frame instantaneous gradient field or a frequency domain gradient field subjected to time-frequency domain Fourier transform as a target field; and through adaptive sliding window interception, two-dimensional autocorrelation calculation and Rayleigh wave space autocorrelation theoretical model fitting, global shear wave velocity distribution is obtained, and viscoelastic modulus distribution is reconstructed through an inversion algorithm. The method supports single-frame scattering displacement gradient field inversion elastic imaging, does not need high-frame-rate equipment, is high in environmental vibration interference resistance, is high in system stability, is suitable for scenes with poor shock isolation conditions, is low in cost, is high in efficiency, is high in measurement precision, and can meet the requirements of medical clinical diagnosis and material multi-scale mechanical measurement.

Magnetic resonance and ultrasound methods can produce estimates of full rank-4 elasticity tensors (E-tensors) using suitable constraints. E-tensor estimates can be based on E-tensor symmetry conditions and a suitable E-tensor selected from among a set of E-tensors calculated using different symmetry constraints. Displacement fields used in E-tensor calculations can be noise reduced using compatibility conditions. With the selected E-tensor, various stains that are rotation invariant can be computed. In one example, an E-tensor for an in vivo brain is computed using the mechanical disturbance associated with cardiac pulsations. The selected E-tensor and associated stains, physiological disorders such as Alzheimer's disease and traumatic brain injury (TBI) and even neural activation may be more readily detected than with conventional methods that do not use the full E-tensor.

The invention discloses a lung elastography and AI-assisted pulmonary nodule benign and malignant identification method and a storage medium, and the method comprises the steps: obtaining the individual feature data and pulmonary nodule multi-source detection data of a patient, including lung elastography data and biological digital twin multi-physical field data; preprocessing the multi-source detection data, reducing dimensions by using a principal component analysis method, and screening out a representative feature combination; inputting the representative feature combination into a pulmonary nodule benign and malignant identification model, and outputting a binary classification result and a first confidence coefficient; inputting the individual characteristic data and the representative characteristic combination into a biological digital twin model when the identification is malignant, generating simulation data, and calculating a comprehensive consistency index; inputting the individual feature data, the representative feature combination and the comprehensive consistency index into a correlation model, outputting a malignant risk degree prediction probability, and based on the probability, adjusting the first confidence coefficient to obtain a second confidence coefficient; generating a multi-modal identification report; the method has the advantage of high accuracy of identifying benign and malignant pulmonary

The present application relates to the technical field of medical imaging processing, in particular to a multi-modal image fusion method based on prostate cancer tissue morphology, comprising the following steps: obtaining microvessel photoacoustic imaging, ultrasonic elastography and magnetic resonance imaging of the same prostate site; taking the microvessel photoacoustic imaging and the ultrasonic elastography as reference images and the magnetic resonance imaging as a floating image to construct a bidirectional supervision registration network; and performing lightweight processing on the bidirectional supervision registration network through transfer learning to establish a fast registration network. The present application first obtains a high-precision registration result of the magnetic resonance, photoacoustic and ultrasonic images through a complex model structure, and then forms a small model structure through transfer learning to learn the high-precision performance of the complex model structure, so that the simple structure and the high-precision performance of the model are compatible, the requirement of the deployment environment is reduced, and the universality is improved.

An elastography method includes acquiring, at a repetition rate of at least 4 measurements per second and for a duration of at least 3 seconds, measurements of a mechanical property of a region of a body of a subject, the region being a part of a liver or a part of a spleen of the subject; obtaining a signal representative of the variations of the mechanical property with time, the signal including at least part of the measurements of the mechanical property determined; in each portion of the signal among at least one portion of the signal, select measurements, among the measurements included in the portion of the signal, lower than or equal to a threshold associated with the portion of the signal; and determining a value representative of the mechanical property, called resting value, based on the selected measurements.

This invention relates to a method for preparing for MR elastography of the liver according to the following steps: generating an image record of the subject to be examined; determining the position of the liver based on the image record; providing information regarding the target position of a vibration generator based on the position of the liver; positioning the vibration generator at the subject to be examined based on the information regarding the target position; introducing the subject to be examined with the vibration generator into the patient receiving area of ​​a magnetic resonance imaging device; detecting summary MR image data of the subject to be examined; and selecting an examination area for a cross-section covering at least one subregion of the liver based on the summary MR image data to record MRE image data.

The invention relates to the technical field of ultrasonic diagnosis, in particular to an abdominal ultrasonic multi-modal image fusion analysis system which comprises a multi-modal space alignment module, an anatomical semantic structuring module, a multi-modal feature fusion and visualization module, a multi-parameter quantitative analysis module, a qualitative evaluation matrix construction module and an intelligent report generation module. By taking the gray-scale ultrasound image sequence of the target abdominal region as a space reference, aligning the elastography and ultrasound contrast sequences to obtain a multi-modal image set; mapping an anatomical structure, tissue hardness and blood perfusion information in the image set to a standard anatomical map to generate structured data; associating and visually coding the tissue hardness distribution information and the blood perfusion dynamic information to obtain a fused image; feature parameters of the fused image are analyzed and compared with a clinical threshold value to obtain quantitative parameters, and a qualitative evaluation matrix is constructed; summarizing qualitative evaluation indexes, quantitative parameters and structured description data to generate an analysis report; the efficiency of abdominal ultrasonic diagnosis analysis can be improved.