193 results about "RESPIRATORY MOVEMENTS" patented technology

The invention relates to the technical field of medical instrument control, in particular to a lung biopsy sampling needle stabilizing method and system based on dynamic respiration compensation. The stabilizing method comprises the following steps: acquiring a respiratory movement signal of a patient in real time through a multi-source biosensor, wherein the multi-source biosensor comprises an optical fiber strain sensor array, a diaphragm myoelectricity sensor and a respiratory airflow sensor which are deployed at the chest and abdomen. According to the method, millimeter-microsecond-level accurate and stable control over the lung biopsy sampling process is achieved by establishing a cooperation mechanism of a breathing phase-displacement nonlinear mapping model and a macro-micro composite driving framework. The biological rationality of displacement prediction is improved through deep coupling of multi-mode breathing signals, and the chest wall non-uniform deformation gradient is analyzed in space based on cross topology deployment of an optical fiber strain sensor in an intercostal space area in combination with cross-scale feature fusion of myoelectricity and airflow sensing.

The invention relates to the technical field of radiotherapy, in particular to a space-time compensation method and system for radiotherapy of pancreas respiratory movement variability, and the method comprises the steps: setting an infrared reflective mark point on the body surface of a patient, and obtaining a body surface three-dimensional CT image and an infrared camera real-time image under respiratory movement; establishing a pancreas three-dimensional model, a CTV target region model and a respiratory movement model; predicting body surface mark point displacement by adopting a long-short-term memory network algorithm and generating a respiration curve; determining a pancreas three-dimensional coordinate motion state; predicting lung motion by using optical flow motion estimation, and reversely solving a pancreas motion trail; determining the opening and closing states of the blades of the multi-blade collimator; according to the method, the mapping relation between lung movement and pancreatic movement is established through reverse mapping, an improved optical flow movement estimation algorithm and an LSTM network are adopted to predict respiratory movement, and the CTV leakage volume can be remarkably reduced to 0.4 cm from 2.1 cm of a traditional gating technology.

The invention discloses a radiofrequency ablation navigation device based on multi-modal image fusion. The device comprises a respiration sensor, an image reconstruction server, an interaction terminal and a processor. The respiration sensor is worn on a target object and used for collecting respiration data of the target object. The image reconstruction server is used for receiving the multi-modal image of the target object and reconstructing the multi-modal image into a three-dimensional model; the three-dimensional model comprises an organ geometric model, nerve distribution and a blood vessel network. And the interaction terminal is connected with the image reconstruction server and is used for marking a starting point and an ending point for the three-dimensional model. The processor is connected with the respiration sensor, the image reconstruction server and the interaction terminal; and the processor generates a predicted path output according to the respiration data and the three-dimensional model marking the starting point and the ending point. The method has the advantages that respiratory movement errors are accurately compensated, the nerve mistaken injury risk is reduced, and the operation safety is improved.

The invention discloses an auxiliary renal puncture device for the nephrology department, and belongs to the technical field of renal puncture, the auxiliary renal puncture device comprises a sickbed, a plurality of supporting legs are fixedly arranged at the bottom of the sickbed, fixing plates are fixedly arranged on the two sides of the sickbed, and second sliding blocks are slidably connected to one sides of the two fixing plates; the breathing frequency and amplitude of a patient are captured in real time through an infrared breathing monitoring module, and displacement data generated by breathing of the kidney are accurately obtained in combination with motion sensing modules such as a lead screw encoder and a driving gear angle encoder. The intelligent control system drives the first stepping motor and the second stepping motor to adjust the position of the portal frame based on six-dimensional force sensor data of the force sensing module, meanwhile, the angle of the puncture needle is adjusted in real time through feedback of a mechanical arm joint encoder, and dynamic compensation of kidney respiratory movement is achieved. According to the mechanism, the puncture deviation caused by breathing can be controlled within the range of + / -0.5 mm, the puncture positioning precision is remarkably improved, and poor sample quality or operation risks caused by breathing movement are avoided.

The invention discloses a PET / MR (positron emission tomography / magnetic resonance) all-in-one machine-based dynamic attenuation correction and respiratory and cardiac dual motion correction method. The method comprises the following steps of: generating a dynamic mu graph of a respiratory cycle; mR cardiac function movie sequence scanning of the cardiac cycle; accurately segmenting the cardiac muscle; 6, performing tissue segmentation on the dynamic mu graph; clustering the PET data; pET data space-time registration is carried out; merging PET data of the same time phase; performing frame-by-frame dynamic attenuation correction; respiratory movement correction; correcting a partial volume effect; carrying out myocardial MR image space standardization on different time phases of the cardiac cycle; and carrying out spatial standardization on the myocardial PET image of different time phases in the cardiac cycle. According to the method, the mu graph of the respiration and cardiac cycles is reconstructed through time-phase sharing and is accurately registered with the PET data, so that the high-quality attenuation correction of the heart PET image is realized and the motion correction is completed at the same time.

The invention discloses a point cloud-driven thoracic cavity whole organ dynamic reconstruction and respiration monitoring method and system, and the method comprises the steps: constructing a three-dimensional geometric model corresponding to each target structure in a thoracic cavity based on the thoracic medical image data of a target object, and converting the three-dimensional geometric model into static point cloud data; driving the static point cloud data to perform dynamic deformation simulation in a respiratory cycle based on a respiratory movement rule of the target object to obtain dynamic point cloud data synchronized with a respiratory time phase; performing time-space synchronization association on the dynamic point cloud data and the electrical characteristic parameters, and constructing a digital twin thoracic cavity model; deploying a virtual sensing assembly which dynamically deforms along with the thoracic cavity in the digital twin thoracic cavity model, simulating and monitoring the dynamic breathing process of the target object, and generating a virtual physiological signal; and performing signal processing on the virtual physiological signal to obtain a dynamic reconstruction image reflecting respiratory movement. Continuous simulation of the full-breathing movement process is achieved, and the temporal-spatial resolution and diversity of a virtual database are improved.

The invention relates to the technical field of medical image information processing, discloses an ICG fluorescence image and MRCP three-dimensional model registration fusion display method and system, effectively solves the problems of deep biliary tract structure blurring and form distortion caused by liver tissue scattering effect in intraoperative fluorescence imaging, uses a preoperative model as anatomical prior, and improves the accuracy of the intraoperative fluorescence imaging. A viewpoint correlation optical path depth field is constructed through reverse ray tracing, a spatial variation point spread function is generated accordingly, physical reverse recovery of scattering halo in a fluorescence image is achieved, non-specific background noise such as vascular leakage is effectively inhibited in combination with topological gravitational constraint of a central skeleton, and the detection accuracy is improved. The real pipe diameter and the center line position of the deep bile duct are accurately recovered, non-rigid registration correction is performed on the three-dimensional model based on the recovered high-fidelity image, and projection errors caused by respiratory movement and soft tissue deformation are eliminated.

The hydrogel patch type respiratory gating magnetic resonance device comprises a respiratory gating patch, a pressure signal change receiver, a magnetic resonance main body and an image acquisition workstation, the respiratory gating patch is connected with the pressure signal change receiver; the pressure signal change receiver is connected with the magnetic resonance main body and transmits a pressure change signal to the magnetic resonance main body; the magnetic resonance main body is connected with the image acquisition work station, and the image acquisition work station processes, stores and displays acquired images. The hydrogel patch type respiratory gating magnetic resonance device is simple and feasible in structure, and is adaptive to most of magnetic resonance I (MR I) equipment at present; the device is wide in application range, can be used for patients of different age groups, and even can be used for animal MR examination; under the guidance of a trigger signal, a magnetic resonance main body performs data acquisition at a specific breathing phase so as to reduce artifacts and ambiguity caused by breathing movement, and for a patient needing an interventional operation under magnetic resonance, patch type respiratory gating is convenient for surgical operation and does not affect a surgical area.

The invention discloses an intraoperative pulmonary nodule positioning method and system based on fusion of a CT image and an endoscope video. The method comprises the following steps: firstly, constructing a three-dimensional lung model containing a pulmonary nodule position based on preoperative high-resolution CT data; generating a real-time lung surface model by using an endoscope video stream through a three-dimensional reconstruction technology during the operation; a feature point extraction and matching algorithm is adopted, and a non-rigid registration technology is combined to realize accurate registration of the preoperative model and the intraoperative dynamic model; projection display of pulmonary nodules in a real-time endoscope visual field is established through space coordinate mapping, and a dynamic compensation algorithm is developed to solve the problem of tissue deformation caused by respiratory movement and instrument operation. Meanwhile, the virtual nodule position is overlaid to an endoscope video picture through the augmented reality technology, and visual intraoperative navigation is provided for surgeons. The method effectively solves the technical bottleneck that a traditional method depends on a metal marker and cannot adapt to intraoperative tissue deformation and the like, and has clinical practical value.

A medical imaging method for detecting a movement and a magnetic resonance imaging system, wherein the method includes: receiving, through a plurality of channels, a plurality of original first time domain signals recording a movement of an object under examination; transforming, based on a plurality of respiratory frequency components as bases, the plurality of first time domain signals into a vector matrix including representations of phases; computing an eigenvector based on the vector matrix; transforming the first time domain signals into second time domain signals based on the eigenvector, and removing a maximum energy term related to a respiratory movement from the second time domain signals; and determining whether a portion of a non-respiratory body movement is detected, and determining to execute a sequence based on only a first time domain signal in which a portion of a non-respiratory body movement is not detected.

The invention provides a thoracic surgery respiratory training system and method, and the method comprises the steps: constructing a respiratory-physiological feature tensor through the time sequence change of a respiratory airflow parameter during respiratory training in combination with the fluctuation feature of blood oxygen saturation in the respiratory training process, and carrying out the space-time convolution fusion of the respiratory-physiological feature tensor and a chest respiratory movement track, obtaining a respiratory efficiency index; constructing a taboo risk vector based on the risk relationship map of the thoracic surgery postoperative complications and the electronic medical record of the target user, and generating a complication risk entropy of the target user under the current respiratory training according to the taboo risk vector in combination with the pain tolerance physiological data; and according to the respiratory efficiency index and the complication risk entropy, determining a dynamic adaptation margin of the target user to current respiratory training, and based on the dynamic adaptation margin, dynamically adjusting the training resistance of the self-adaptive resistance adjustment respiratory training device. By the adoption of the scheme, a multi-dimensional respiratory training feedback mechanism can be constructed to conduct self-adaptive adjustment on the training resistance.

The invention relates to the technical field of medical imaging, and discloses a peripheral lung cancer pleural invasion evaluation system based on ultrasonic targeted radiography, comprising: a double-frequency ultrasonic probe configured to independently work at different frequencies to realize depth imaging and high-resolution imaging of lung tissues and suitable for different types of lung lesions; the signal processing module can receive, analyze and process echo signals transmitted by the ultrasonic probe, generate images in real time and extract feature information; and the dynamic motion compensation module is used for automatically adjusting the emission time sequence and parameter setting of the ultrasonic signal based on the real-time breathing motion state of the patient. By adopting the design of the double-frequency ultrasonic probe and the core-shell structure, high-resolution imaging and depth detection of lung tissues are realized. By dynamically adjusting the thickness of the probe shell to be matched with the frequency, the system can adapt to complex tissue environments under different physiological conditions, and image definition and stability are ensured.

A respiratory motion plane alignment system and method based on ultrasound images is disclosed. The system acquires three-dimensional ultrasound images of respiratory organs at at least two different respiratory phases, calculates the motion direction of the respiratory organs based on the three-dimensional ultrasound images, controls and adjusts an ultrasound direction adjustment mechanism to align the scanning plane of the ultrasound probe with the motion direction of the respiratory organs, acquires a three-dimensional model image of the respiratory organs and multiple frames of real-time two-dimensional ultrasound images, performs registration between the multiple frames of real-time two-dimensional ultrasound images of the respiratory organs, and / or registers the three-dimensional model image and the multiple frames of real-time two-dimensional ultrasound images, acquires three-dimensional position data of a target point during respiratory motion, determines the tracking path of the ultrasound probe based on the three-dimensional position data of the target point during respiratory motion, and controls the ultrasound probe to move along the tracking path, thereby achieving long-term stable observation or tracking of target points in the respiratory organs.

The invention relates to a wearable music diaphragm pacemaker and a use method thereof, and belongs to the technical field of medical rehabilitation equipment, the wearable music diaphragm pacemaker comprises a diaphragm pacemaker host, an electrical stimulation module, a respiration monitoring module and a wearable bag, the diaphragm pacemaker host is connected with the electrical stimulation module and the respiration monitoring module through wires, the electrical stimulation module adopts an electrode patch, and the wearable bag is connected with the electrical stimulation module. The respiration monitoring module is used for applying adjustable electric pulses to phrenic nerves or diaphragm muscles, and is provided with a piezoelectric pressure sensor for collecting thoracico-abdominal respiration movement signals in real time. In the invention, compared with a traditional diaphragm pacemaker which mainly depends on electrical stimulation to passively enhance diaphragm contraction and a patient needs to actively cooperate with respiratory training, through real-time matching of rhythm and tone changes of megawatt music and electrical stimulation parameters, such as inspiratory phase tone rising and expiratory phase rhythm slowing, multi-sensory synergistic stimulation is formed; perceiving and active cooperation of the patient on the respiratory rhythm are enhanced, and therefore the rehabilitation effect can be effectively improved.

The invention belongs to the technical field of lung tissue lesion positioning, and particularly relates to a lung tissue lesion position positioning system and method based on three-dimensional reconstruction. According to the method, overall and local two-stage registration is combined, whole-lung expansion errors are corrected, local deformation is compensated, the lesion position and image alignment is achieved, the three-dimensional lesion position is displayed through the augmented reality technology, doctors are helped to visually master spatial distribution of the focus in the body of a patient, the safety and the success rate of operation or needle biopsy are improved, and the operation efficiency is improved. Based on a breathing model and an elastic registration method, the method can adapt to lung compliance differences and breathing movement conditions of different patients, is particularly suitable for severe or old patients difficult to keep stable breathing, reduces the risk of blind penetration or excessive resection through accurate positioning, and reduces tissue damage and the occurrence rate of postoperative complications.

The invention discloses a three-dimensional in-vivo radiotherapy dose monitoring method and system, and the method comprises the steps: collecting an image sequence {In} containing time dimensions at a theta t time interval through CBCT scanning equipment in a radiotherapy process; calculating target area displacement of adjacent frames of images in the image sequence {In} by using a bidirectional optical flow estimation method; state estimation and prediction are carried out on the displacement data based on an adaptive Kalman filtering algorithm, a dynamic displacement rule of the target area in the respiratory cycle is generated, and a respiratory movement prediction result is output; acquiring radiotherapy plan parameters from a radiotherapy plan system, and calculating planned dose distribution without considering respiratory movement; dynamically adjusting a ray transmission path and energy deposition according to a respiratory movement prediction result, and calculating real-time dose distribution of each respiratory time phase; mapping the dose distribution of each time phase to a reference time phase coordinate system to generate accumulated dose distribution; and comparing and verifying the accumulated dose distribution and the planned dose distribution.

The invention relates to the technical field of medical equipment, and particularly discloses a puncture positioning device for medical oncology. Adjusting grooves are formed in the inner walls of the two sides of the positioning frame, a dynamic adjusting mechanism is jointly mounted between the two adjusting grooves, supporting frames are mounted on the two sides of the bottom end of the positioning frame, a marking mechanism is mounted on the upper portion of the outer wall of the supporting frame on one side, and mounting mechanisms are mounted on the lower portions of the outer surfaces of the two supporting frames. Patient body surface mark points are captured in real time through the binocular near-infrared camera, submillimeter-level positioning precision is achieved, the actual position and target spot deviation of a puncture needle can be continuously monitored through an encoder on the six-axis mechanical arm, motion parameters of the six-axis mechanical arm are dynamically adjusted based on a PID control algorithm, accurate compensation of millisecond-level response is achieved, and the precision of the system is improved. Target point deviation caused by breathing movement or organ displacement of a patient is effectively handled, the success rate of puncture sampling is increased, and complications caused by repeated puncture are reduced.

The invention discloses an intelligent critical case early warning analysis system based on multi-source clinical data fusion, belongs to the technical field of image processing, and can more accurately carry out respiration monitoring and early warning. Comprising a respiratory movement analysis module used for generating a respiratory movement amplitude change curve according to thoracic and abdominal movement video data; the breathing machine waveform analysis module is used for generating waveform characteristic data containing abnormal time slices according to the breathing machine waveform data; the blood oxygen signal processing module is used for generating a blood oxygen change trend vector according to the blood oxygen saturation degree signal data; the multi-modal fusion module is used for generating a multi-dimensional physiological feature vector under a synchronous timestamp according to the breathing movement amplitude change curve, the waveform feature data and the blood oxygen change trend vector; the risk assessment module is used for generating a breathing compensation state score according to the multi-dimensional physiological feature vector; and the alarm triggering module is used for triggering a grading alarm signal according to the deviation degree of the breathing compensation state score and the baseline range.

The invention relates to a respiration guiding system for image examination, which is applied to the technical field of image examination and comprises a respiration monitoring module, a patient feedback module, a control processing module and a physician interaction terminal, a plurality of different target breathing waveforms are pre-stored in the doctor interaction terminal, the control processing module generates real-time breathing waveforms based on breathing waveform signals, time synchronization is conducted on the target breathing waveforms and the real-time breathing waveforms, then the patient feedback module and the doctor interaction terminal are controlled to be displayed in a parallel comparison mode, and a patient is guided to adjust breathing. According to the invention, through ''physician-system-patient'' three-element closed-loop interaction, respiratory training and pre-judgment before scanning and continuous guidance and stable maintenance during scanning are realized, so that the success rate of first scanning is improved, the number of times of repeated scanning is reduced, and the radiation dose risk and medical cost of a patient are reduced.

A wearable device (100) for monitoring cardiac function during apnoeic episode. Wearable device including ballistocardiography (BCG) sensor (102A) to measure mechanical forces generated by heart and respiratory movement; electrocardiography (ECG) sensor (102B) to measure electrical activity of heart; and processor (102C) operatively connected to BCG sensor and ECG sensor to generate BCG data from measured mechanical forces and ECG data from measured electrical activity, respectively. Processor configured to: filter respiratory signals and heart signals from BCG data; detect apnoeic episode based on low respiratory signals or absence of respiratory signals for predetermined time period in filtered BCG data; determine compensatory mechanical output of heart using at least one of filtered BCG data or ECG data for apnoeic episode, and predict risk of cardiac condition based on compensatory mechanical output during apnoeic episode. Also a system (300) and method thereof.

The invention relates to the technical field of hydrops quantitative evaluation, and discloses an ultrasound-based pleural hydrops quantitative evaluation system, which comprises an image acquisition module, a boundary division module, a trajectory analysis module, a feature judgment module, a mode classification module and a quantitative evaluation determination module, the positioning module is used for positioning an area which deforms along with breathing movement in the ultrasonic image sequence, and dividing a suspected effusion cavity boundary based on the consistency of a deformation mode; the trajectory analysis module is used for analyzing moving trajectories of the suspected effusion cavity boundary at different breathing phases and extracting regularity features and amplitude change features of the moving trajectories; the feature judgment module is used for judging the mechanical coupling state of the suspected effusion cavity and the surrounding lung tissue according to the combination of the regularity feature and the amplitude change feature; according to the method, the comprehensiveness and accuracy of quantitative evaluation of the pleural effusion are remarkably improved, and a more valuable decision basis is provided for clinical diagnosis and treatment.

To perform synchronous reconfiguration to the periodic movement of a subject without using an external device.SOLUTION: A nuclear medicine diagnosis device analyzes a respiratory movement from list mode data of scanning in which the respiratory movement and heart beats occur, divides the list mode data for every respiratory phase to create first images, analyzes the heart beats for every respiratory phase, creates second images from data obtained by dividing the list mode data for every respiratory phase and data obtained by the division for every heart beat phase, acquires at least one of a first motion vector between the respiratory phases and a second motion vector between the heart beat phases, and applies the first motion vector to the second images and adds up the images, for every group of the second images different in the respiratory phase from each other and common in the heart beat phase, to create a first single phase image corresponding to a specific phase, or applies the motion vector to the second images and adds up the images, for every group of the second images different in the heart beat phase from each other and common in the respiratory phase, to create a second single phase image corresponding to the specific phase.SELECTED DRAWING: Figure 9

The application discloses an old person free breathing coronary artery scanning image lesion analysis system and relates to the technical field of scanning image lesion analysis. In order to solve the problem that the accurate condition of a patient cannot be obtained according to a scanning image. The application adopts a diameter method, an area method and a contrast agent filling condition to judge the stenosis degree and the hemodynamic change, analyzes the lesion from the morphological and functional double angles, provides comprehensive information for clinical decision-making, identifies the R wave peak value and divides the cardiac phase, matches the respiratory signal and the projection data in time, can accurately capture the characteristics of the heart in different motion states and the respiratory stage, effectively avoids the interference of the artifacts caused by the heart beat and the respiratory motion, makes the reconstructed image clearer and more accurate, sets the CT and the injector parameters in sequence from the scanning type confirmation, each link is closely related and the target is clear, improves the work efficiency, and is convenient for quality control and process management.

The invention provides a millimeter-wave radar heart rhythm detection method based on comparative learning. The millimeter-wave radar heart rhythm detection method comprises the steps that S1, echo signals generated after millimeter-wave radar signals act on a to-be-detected object are acquired; s2, based on the obtained echo signals, reflected signals from the chest area in the three-dimensional space are extracted; s3, weakening the influence of respiratory movement based on the phase change of the reflected signal to obtain a heart mechanical activity signal; s4, creating a model, pre-training the heart mechanical activity signal based on comparative learning, and training the ability of a feature extractor in the model to extract features related to heart mechanical activity; s5, on the basis of the feature extractor obtained through training, heart rhythm feature tags are added for fine adjustment, and model training is completed through a loss function; s6, heart mechanical activity signals of the to-be-tested object are input into the trained model, and a heart rhythm classification result of the to-be-tested object is obtained.

The invention provides a breathing mode classification method and system based on a CNN-LSTM neural network, and the method comprises the steps: collecting body surface point cloud data in a non-shielding state and an arm shielding state in a human body breathing process, and extracting a breathing motion feature on the basis of extracting the breathing motion feature; the invention provides an optimization method for abnormal respiratory movement characteristics of a significant respiratory movement area, solves the interference of environmental noise and newborn clinical characteristics on respiratory signals, and comprises the following steps of: firstly, partitioning a thoracic and abdominal voxel model, and extracting the respiratory movement characteristics of the significant area based on KPCA (Kernel Principal Component Analysis); motion artifacts are removed through a Savitzky-Golay filter, body motion interference is inhibited by using a method of fusing a peak threshold method and a local variance threshold, and baseline drift is removed by using a grey wolf optimization algorithm. According to the method, a CNN-LSTM neural network is constructed to classify four breathing modes of normal, rapid, slow and pause, model parameters and evaluation indexes are determined, effective classification and recognition of the breathing modes are achieved, and the monitoring precision and clinical application value are improved.

FIELD: cardiology.SUBSTANCE: used as a component of the first stage of cardiac rehabilitation in patients with chronic heart failure (CHF), as well as an auxiliary component at all stages of cardiac rehabilitation. Warm-up exercises are performed – stretching exercises and movements in the joints of the upper body, followed by a basic set of breathing exercises lasting from 15 to 30 minutes, at least once a day, at least 5 days a week, for at least 8 weeks. At the first stage, the main set of exercises includes four exercises performed in sequence: abdominal breathing, chest breathing, breathing involving the shoulder muscles, breathing slowing. The first three exercises are performed for 5–10 breathing cycles with an interval between exercises of at least 1 minute, the fourth exercise contains 5–15 cycles, where each cycle includes an inhalation through the first nostril, followed by an exhalation and inhalation through the second nostril, then an exhalation through the first nostril . In the second and subsequent stages, the main set of exercises includes two exercises performed sequentially: an exercise for full breathing and an exercise for slowing down breathing. The full breathing exercise involves sequentially performing abdominal breathing, chest breathing, and breathing with the involvement of the shoulder muscles throughout one inhalation. The exhalation is performed in reverse order. The number of cycles of the full breathing exercise at the second stage is 15–20. The duration of each stage is at least 2 weeks, where at each subsequent stage, starting from the second one, the duration of the exercises performed in the main complex is increased by increasing the number of exercise cycles. Also the duration of inhalation and exhalation is increased when performing exercises to slow down breathing. The method improves the biomechanics of breathing: increases the depth of breathing, reduces the frequency of respiratory movements, increases the efficiency of breathing and reduces the activity of the inspiratory metaboreflex.EFFECT: exercise tolerance in patients with CHF improves.3 cl, 6 dwg, 3 ex

The application discloses a point cloud driven thoracic cavity whole organ dynamic reconstruction and respiratory monitoring method and system, and the method implementation comprises the following steps: based on the thoracic medical image data of a target object, constructing three-dimensional geometric models corresponding to each target structure in the thoracic cavity, and converting the three-dimensional geometric models into static point cloud data; based on the respiratory motion law of the target object, driving the static point cloud data to perform dynamic deformation simulation in a respiratory cycle, and obtaining dynamic point cloud data synchronized with the respiratory phase; synchronously associating the dynamic point cloud data with electrical characteristic parameters in time and space, and constructing a digital twin thoracic cavity model; deploying a virtual sensor assembly that dynamically deforms with the thoracic cavity in the digital twin thoracic cavity model, and simulating and monitoring the dynamic respiratory process of the target object, and generating a virtual physiological signal; and through signal processing on the virtual physiological signal, a dynamic reconstruction image reflecting the respiratory motion is obtained. The continuous simulation of the whole respiratory motion process is realized, and the time and space resolution and diversity of the virtual database are improved.

The present invention relates to the field of artificial intelligence technology, and discloses an intelligent quantitative assessment system for adolescent scoliosis that integrates multimodal imaging. The system includes a multimodal data management module, a cross-modal registration fusion module, a dynamic quantitative analysis module, a risk prediction module, a three-dimensional reconstruction module, a report generation module, and a system management module. By setting a multimodal registration verification mechanism, the accurate matching of bony structure and soft tissue is ensured, and the calculation error of key parameters caused by registration failure is reduced, so that the three-dimensional reconstruction accuracy is greatly improved compared with traditional single-modal assessment. By introducing a dynamic breathing compensation module, the physiological changes of the spine in the respiratory movement cycle are automatically captured during the quantification stage of spinal deformation parameters, and the measurement values ​​are corrected based on an individualized dynamic model to distinguish between pathological progression and physiological fluctuations, thereby avoiding the risk of misjudgment caused by ignoring respiratory phase changes in traditional static measurements, and improving the reliability of scoliosis progression risk assessment.

The invention discloses an ultrasonic self-adaptive scanning method and system for EIT dynamic path planning, and belongs to the technical field of medical imaging. Reconstructing an impedance distribution image in real time based on EIT and detecting an abnormal region; the coordinates of the abnormal area are mapped to an ultrasonic coordinate system, and breathing phase compensation is carried out; planning an ultrasonic beam scanning path according to clinical constraint conditions; controlling the ultrasonic beam to scan along the planned path; performing image analysis on the scanning area; and updating system parameters according to an analysis result. According to the method, abnormal coordinates detected by EIT are accurately converted into an ultrasonic beam deflection angle, clinical constraint path planning of a high-cost area of a rib shielding area and breathing phase dynamic compensation taking end expiratory as a benchmark are combined, so that the system realizes full-closed-loop control from abnormal sensing, path planning to beam execution, and the accuracy of the system is improved. The problems of scanning failure caused by rib shielding and coordinate drifting caused by respiratory movement in clinic are effectively solved, and the reliability of dynamic monitoring of the thoracic cavity is remarkably improved.

The invention provides a respiratory-gating-free free-breathing liver glycogen quantitative magnetic resonance imaging method and system, and the method comprises the steps: applying a chemical exchange saturation transfer imaging sequence to a liver region of a subject, and the imaging sequence comprises saturation pulses of a plurality of saturation frequency deviation points; a radial blade type k-space acquisition strategy is adopted to acquire magnetic resonance signal data, the radial blade type k-space acquisition strategy comprises a plurality of blades, each blade is composed of a group of parallel k-space lines, and different blades are rotationally distributed by taking the k-space center as a rotating shaft; performing image reconstruction on the acquired k space data to obtain magnetic resonance images under different saturation frequency deviations; and performing fitting analysis on the magnetic resonance image by adopting a multi-pool Lorentz model to obtain quantitative information of the liver glycogen. According to the method, the interference of respiratory movement on the CESTMRI data acquisition process can be eliminated, so that the accurate quantification of the liver glycogen in the free respiration state is realized.