11839results about "Computer-aided planning/modelling" patented technology

Aspects of the present disclosure relate to systems, devices and methods for performing a surgical step or surgical procedure with visual guidance using a head mounted display with systems, techniques and methods for improving the accuracy of an augmented reality display and / or for enhancing the 3D visualization of an augmented reality display.

A robotic surgical system includes a surgeon consol coupled to a patient consol, and the patient consol coupled to surgical instruments. A surgeon computer is coupled to or at the surgeon consol that is coupled to to one or more surgical instruments. A robotic surgery control system includes an artificial intelligence (AI) system with one or more deep learning algorithms. A feedback loop monitors and collects data from the one or more sensors. One or more cameras provide feedback to the robotic surgical system, and are configured to provide images of an anatomical object in at least a two dimensional (2D) arrangements of pixels / Deep learning algorithms of the AI system distinguish different anatomical objects from the images.

One or more data streams may be used for controlling multi-system interaction. For example, a data stream may be received, and a surgical option associated with a surgical instrument may be selected based on the data stream. A control signal associated with the surgical instrument may be generated based on the selected surgical option. A surgical device may receive an external data stream from a source external to the surgical system. The device may derive, based at least on the external data stream, decision contextual information. The device may select a surgical option associated with a surgical instrument based on the decision context information. The device may generate a visual indication of the decision context information associated with selecting the surgical option. The device may generate a control signal associated with the surgical instrument based on the selected surgical option.

Systems, methods, and instrumentalities are disclosed for displaying a magnitude and location of a resulting tissue tension from an applied force to an instrument and a resulting tissue reaction. A surgical stapling device for monitoring and adapting to tissue tension during a surgical stapling procedure may measure strain on at least one component of the surgical stapling device resultant from one or more of an opposed force applied by a user and a force resisted by tissue associated with the tissue tension. The device may determine a location of the tissue tension based on historical surgical data, the opposed force, and the resisted force. The device may highlight the location of the tissue tension to aid in real-time surgical decision-making.

A method performed by a surgical robotic system. The method determines a surgical procedure that is to be performed using a robotic arm. The method determines, for the robotic arm, a planned trajectory based on the surgical procedure, where the planned trajectory is from a current pose of the robotic arm to a predefined procedure pose that is within a threshold distance from a trocar that is coupled to a patient. The method drives the robotic arm along the planned trajectory from the current pose to the predefined procedure pose.

A medical system includes an elongate instrument, a tracking system, and one or more processors. The tracking system is disposed along at least a portion of the elongate instrument. The one or more processors are coupled to the tracking system and are configured to: generate a plurality of linked bounded-surface elements corresponding to a set of connected passageways of a patient anatomy; receive shape information from the tracking system, the shape information indicating a shape of at least a portion of the elongate instrument when the portion is disposed in the set of connected passageways; register the shape information to the plurality of linked bounded-surface elements; and based on the registering, display a composite image including an instrument image of the elongate instrument displayed within a model of the set of connected passageways.

The disclosed embodiments relate to systems and methods for a surgical tool or a surgical robotic system. A tool driver is coupled to a distal end of a robotic arm and includes a roll drive disk driven by a rotary motor. One or more processors are configured to detect an attachment of a surgical tool to the tool driver. The surgical tool includes a roll tool disk to be engaged with the roll drive disk of the tool driver, actuate of the roll drive disk through the rotary motor, determine that a measured torque of the rotary motor exceeds a preset torque threshold for a preset period of time since the actuation, and report a successful engagement between the roll drive disk and the roll tool disk.

A system comprises a processor and a memory having computer readable instructions stored thereon, which, when executed by the processor, cause the system to display an image of a surgical environment. The image includes an information icon corresponding to an instrument in the surgical environment. The instructions further cause the system to display an image of a body part of a user. The image of the body part is used to interact with the information icon. The instructions further cause the system to receive a gesture of the body part, via a gesture-based input device registering movement of the body part, to cause the image of the body part to interact with the information icon. The instructions further cause the system to display an information menu in the image of the surgical environment based on the interaction between the image of the body part and the information icon.

A computer-implemented method for designing a patient-specific orthopedic implant can include creating a user account associated with a patient. A patient-specific orthopedic implant can be designed based on patient data and imaging data. A healthcare provider can provide feedback for a design of the patient-specific orthopedic implant, treatment protocol, or other aspects of treatment. The patient can provide data and feedback.

The invention discloses a surgical robot resection navigation method based on multi-modal image registration. The method comprises the following steps: acquiring a preoperative multi-modal medical image of a patient and reconstructing a three-dimensional model containing a focus and a dangerous structure; acquiring an intraoperative real-time image; extracting cross-modal invariant features from the pre-operative and intra-operative images by using a first deep learning network, and establishing an initial corresponding relation; predicting an initial non-rigid deformation field by using a second deep learning network, based on the pre-operative / intra-operative image and the initial corresponding relation and in combination with physical model constraints; tracking a surgical tool in real time, and updating a non-rigid deformation field in real time by adopting an incremental calculation strategy; applying the updated deformation field to the preoperative three-dimensional model to generate a deformed model; and mapping the tool position to the deformed model, and generating a navigation instruction. According to the method, soft tissue deformation can be accurately compensated, multi-modal image information is effectively fused, navigation information is dynamically updated in real time, and the precision and safety of robot surgery are remarkably improved.

The invention belongs to the technical field of medical robots, and particularly relates to a mammary gland puncture surgical robot navigation system and device based on multi-modal image fusion. The multi-mode image data are registered and fused, high-precision three-dimensional reconstruction of the mammary gland tissue is achieved, more visual and accurate surgical navigation information is provided for doctors, the position of the puncture needle is tracked in real time, space registration is conducted on the puncture needle and the image data, and therefore the precision and safety of the surgery are improved, and the operation efficiency is improved. Meanwhile, puncture force feedback information of a puncture needle in the needle moving process is collected in real time, the implementation effectiveness of a puncture navigation path is evaluated, when it is found that the puncture path has risks, dynamic adjustment is conducted immediately, a new puncture path bypassing an obstacle area and reaching a focus is planned again, and the risk of the puncture path is avoided. And if the safe path cannot be obtained, the system automatically stops needle insertion and gives an acousto-optic early warning prompt, so that the surgical risk caused by manual misoperation in the traditional surgery is avoided.

The present invention provides systems, methods, and devices for electroporation-based therapies (EBTs). Embodiments provide patient-specific treatment protocols derived by the numerical modeling of 3D reconstructions of target tissue from images taken of the tissue, and optionally accounting for one or more of physical constraints or dynamic tissue properties. The present invention further relates to systems, methods, and devices for delivering bipolar electric pulses for irreversible electroporation exhibiting reduced or no damage to tissue typically associated with an EBT-induced excessive charge delivered to the tissue.

A robotic surgical system includes a surgeon consol coupled to a patient console and coupled to one or more surgical instruments. The surgeon consol is used by a surgeon to perform a surgical procedure. A surgeon computer is coupled to or at the surgeon console. The surgeon consol is coupled to the one or more surgical instruments. A surgical robot is coupled to a robotic surgery control system and a feedback loop. The robotic surgery control system includes or is coupled to an artificial intelligence (AI) system. The feedback loop receives data from one or more sensors at the robotic surgical system. The data is analyzed by the robotic surgery control system, and in response operation of the robotic surgical system is adjusted as needed. The surgical control system or the AI system uses intraoperative data describing a surgical procedure being performed. The feedback loop receives data from one or more sensors of the robotic surgical system regarding performance of at least a portion of the robotic surgical system. The data is analyzed by the robotic surgical control system. In response to analysis, operation of the robotic surgical system is adjusted as needed. The robotic surgical control system or AI system extracts one or more programmed steps used by the surgeon for positioning at least one of the surgical instruments during the surgical procedure.

A robotic surgical system. a surgeon console operatively coupled to a patient console and one or more surgical instruments. A surgeon computer is coupled to or integrated with the surgeon console, the surgeon computer further operatively connected to the one or more surgical instruments; A surgical robot is coupled to a robotic surgery control system and a feedback loop. The robotic surgery control system includes or is coupled to an artificial intelligence (AI) system. A feedback loop is further configured to receive performance-related data from the one or more sensors, the data analyzed by the robotic surgery control system or the AI system to dynamically adjust the robotic system's operation as needed. A data extraction module retrieves, from the robotic surgery control system or the AI system. one or more programmed steps executed by the surgeon for positioning at least one of the surgical instruments during the surgical procedure.

There are provided methods and systems for training and using machine learning (ML) models to determine suitability of a given patient for an endovascular aortic repair (EVAR) intervention and to monitor the given patient after the EVAR intervention. The pre-EVAR ML models are trained on training datasets comprising strain maps having been generated based on a multiphase image stack of the aorta of each respective patient during a cardiac cycle, measures of aortic weakness in the aorta of each respective patient, geometric features of the aorta of the respective patient, and outcomes of the EVAR intervention on the respective patient. The post-EVAR ML models are trained on pre-EVAR strain maps, post-EVAR strain maps having been generated after the EVAR intervention, and a respective outcome of the EVAR intervention.

The invention relates to an image processing method and a puncture guiding system. The method comprises the following steps: acquiring a medical image sequence image and an ultrasonic sequence image of a target object; performing registration based on the ultrasonic sequence image and the medical image sequence image to obtain a registration transformation matrix and a three-dimensional image after registration fusion; displaying a cross section image in the registered and fused three-dimensional image in a first display area, and projecting a puncture point on the puncture plate on a mapping point of the cross section image and an imaging area of a sagittal plane; responding to rotation operation of the ultrasonic probe, and updating imaging areas of the cross section image, the mapping points and the sagittal plane in the first display area in real time according to the rotation operation; when any target mapping point is located in the imaging area of the sagittal plane in the cross section image, the relative position of the target mapping point located in the imaging area of the sagittal plane in the sagittal plane image is displayed in the second display area. Therefore, the same target mapping point can be displayed in the cross section image and the sagittal plane image at the same time.

The invention provides an intelligent choledochoscope-assisted bile duct calculus minimally invasive calculus removal method and system, and relates to the technical field of minimally invasive calculus removal, and the method comprises the steps: collecting a video image in a bile duct through a choledochoscope, extracting bile duct calculus feature information through a deep learning target detection network, and carrying out the enhancement processing of the image to obtain bile duct cavity wall features; constructing a three-dimensional bile duct blood vessel tree model with focus marks; calculating a risk coefficient based on bile duct calculus characteristics, inputting the three-dimensional model, an anatomy knowledge base and expert experience data into a deep reinforcement learning network, and generating an optimal calculus taking path; the system establishes a real-time three-dimensional navigation map, and real-time path correction is realized through dynamic registration; a visual servo and force feedback control method is adopted, the choledochoscope robot is controlled to move to the target position along the corrected path, the grabbing parameters of the end effector are adjusted according to the morphological characteristics of the calculus, and accurate calculus taking is achieved.

The invention relates to a puncture path planning system and equipment adopting the puncture path planning system, which directly solve the difficulty of peripheral artery puncture and laterally solve the defects of some deep vein catheterization and vasostomy, and the puncture path planning system comprises at least one memory in which a computer program is stored, the at least one processor is configured to implement the puncture path planning method when executing a computer program, and the method comprises the following specific steps: generating a path leading to a target position from different starting points and angles of a blood vessel by adopting a preset geometric algorithm based on a preset safety margin constraint, blood vessel feature constraint information and surrounding tissue constraint information; the generated puncture needle inserting path is integrated into a blood vessel 3D reconstruction model to be displayed in different colors or line styles. The method has the advantages that the blood vessel model is accurately constructed, the puncture path is safely generated, and catheterization of the peripheral artery indwelling needle is more efficient.

Systems and methods for facilitating registration and validation of registration and / or transformation in connection with image-guided surgery or medical procedures are disclosed. The systems and methods may be used in connection with devices or systems including augmented reality near-eye displays.

A system to provide endovascular support for patients. The system includes a processor configured to receive, from a medical imaging device, a pre-treatment vessel roadmap and medical images acquired in response to an endovascular therapy performed on a patient, and obtain endovascular treatment parameters, including image-based endovascular treatment parameters based on features of the medical images. Such endovascular treatment parameters include a geometry and location of an endovascular therapy device within a vessel of the patient. The processor is further configured to predict tissue characteristics of a first lesion based on the endovascular treatment parameters and generate a map of the first lesion based on the pre-treatment vessel roadmap and the predicted tissue characteristics of the first lesion.

There is described a computer-implemented method for designing a stent, comprising: providing for display a first image of a 3D model of at least a portion of a body part comprising an aneurysm; receiving a position for each one of a plurality of reference points chosen along the body part; inserting in the first image a visual marker at the position of each reference point, thereby obtaining a second image; providing the second image for display; for each reference point, calculating a respective diameter; calculating at least one length using the positions of the reference points; and outputting the respective diameter and at least one length.

The invention relates to the technical field of medical instruments, and discloses a laparoscope and digestive endoscope combined positioning measurement system and method.The method comprises the steps of positioning mark initialization, image feature analysis, instrument path planning, dynamic positioning calibration, operation integrity evaluation and the like. Spatial matching is realized by setting multiple types of positioning marks and utilizing optical reflection signals, noise reduction and feature extraction are performed on endoscope imaging data to generate a measurement area boundary, an operation path is planned in combination with anatomical path information, the tail end position of an instrument is calibrated in real time, and operation integrity is evaluated. The system comprises a positioning module, an analysis module, a correction module and an integration module which are respectively used for realizing the functions of positioning mark setting, image processing and path generation, offset correction and operation evaluation. According to the system, the operation positioning precision and the operation safety are improved, intellectualization and precision of minimally invasive surgery are achieved, and the system is suitable for minimally invasive treatment of digestive system diseases.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as financial science and technology and medical health, and discloses a strategy generation method and device based on hierarchical reinforcement learning, equipment and a medium. And processing environment state information to generate a sub-target and a specific action, generating a strategy reward signal in combination with state change, carrying out joint training and updating on the dynamic causal graph and the hierarchical reinforcement learning model based on the strategy reward signal, and generating an optimized action strategy. The state evolution relation is modeled by constructing the dynamic causal graph, so that the reinforcement learning can obtain causal understanding of the state change trend, decomposition and optimization of sub-targets and actions are realized in combination with a layered reinforcement learning architecture, the response precision and generalization ability of the action strategy in a complex environment are improved, and the method is suitable for application and popularization. Therefore, the task completion stability and the convergence efficiency of strategy training are improved.

Systems and methods are disclosed for blood flow simulation. For example, a method may include performing a plurality of blood flow simulations using a first model of vascular blood flow, each of the plurality of blood flow simulations simulating blood flow in a vasculature of a patient or a geometry based on the vasculature of the patient; based on results of the plurality of blood flow simulations, generating a response surface mapping one or more first parameters of the first model to one or more second parameters of a reduced order model of vascular blood; determining values for the one or more parameters of the reduced order model mapped, by the response surface, from parameter values representing a modified state of the vasculature; and performing simulation using the reduced order model parameterized by the determined values, to determine a blood flow characteristic of the modified state of the vasculature.

A system and method for blood flow simulation is disclosed. For example, the method may include performing a plurality of blood flow simulations using a first model of vascular blood flow, each of the plurality of blood flow simulations simulating blood flow within a patient's vasculature or a geometry based on the patient's vasculature; generating a response surface based on results of the plurality of blood flow simulations that maps one or more first parameters of the first model to one or more second parameters of a reduced-order model of vascular blood; determining values ​​for one or more parameters of the reduced-order model mapped from parameter values ​​representing a modified state of the vasculature by the response surface; and performing a simulation using the reduced-order model parameterized by the determined values ​​to determine blood flow characteristics of the modified state of the vasculature.

A method for auxiliarily planning a fracture reduction path based on an augmented reality technology includes: obtaining fracture image data for a fracture area of a patient, the fracture image data including computer tomography (CT) data and X-ray data; reconstructing a three-dimensional model of a fracture part based on the fracture image data; matching and calibrating the three-dimensional model of the fracture part based on the fracture area of the patient in an actual scene; inputting a calibrated three-dimensional model of the fracture part and a corresponding fracture type and fracture surgery requirement into a fracture reduction path planning model to determine at least one corresponding optimized fracture reduction path, where the fracture reduction path planning model includes a cascaded reinforcement learning (RL) module and a multi-physics field simulation optimization module; and rendering each fracture reduction path, and determining a target fracture reduction path according to a detected interactive instruction.

The invention relates to the field of medicine, and discloses a thyroid nodule surgical operation planning and navigation system based on artificial intelligence, which comprises a multi-modal medical image acquisition module, an image preprocessing and enhancing module, an intelligent anatomical structure analysis module, an operation planning decision module and an intraoperative real-time navigation module, the multi-modal medical image acquisition module is used for integrating data of various image equipment such as ultrasonic equipment, CT equipment and MRI equipment, and space-time consistency of multi-modal images is ensured. According to the thyroid nodule surgical operation planning and navigation system based on artificial intelligence, the real-time calculation problem is solved, the system delay is reduced, which is crucial to real-time navigation in an operation, the real-time performance and the operation efficiency are improved, the operation time is shortened, and complications are reduced; by integrating the advantages of different images, the system can provide more comprehensive dissection views, help doctors to more accurately position nodules and important structures and avoid injury to nerves and blood vessels, so that the accuracy is improved, and the surgical risk is further reduced.

The invention discloses an AI-based neurosurgery auxiliary robot visual positioning system, and relates to the field of visual positioning, which comprises the steps of deploying and initializing structured light scanning equipment and near-infrared imaging equipment, carrying out multi-modal image acquisition on a surgical area, and carrying out standardization processing, space-time alignment and fusion on the acquired image. A multi-modal visual acquisition and preprocessing module, a three-dimensional tissue model construction and registration module, a visual-anatomical feature recognition and extraction module, an AI auxiliary positioning and path optimization module, an intraoperative dynamic perception and feedback control module and a target position confirmation and instruction output module are constructed. According to the method, high-precision identification and dynamic modeling of a brain tissue structure are realized, real-time identification, path planning and position correction can be carried out on a key anatomical structure in an operation process, the precision, the intelligent level and the intra-operation response capability of neurosurgery operation are remarkably improved, the operation risk is effectively reduced, and the positioning reliability and the automatic control efficiency are improved.

The invention relates to the technical field of assessment and early warning systems, and particularly discloses a rectal cancer operation risk assessment and early warning system based on multi-modal data fusion, which comprises a multi-modal data acquisition module, a data preprocessing module, a cross-modal fusion module, a dynamic risk assessment module, an intelligent early warning module and a system self-checking module. By integrating multi-modal data and dynamically allocating weights, real-time risk updating in the whole operation period is achieved, the comprehensiveness, timeliness and precision of risk assessment are comprehensively improved by combining the grading early warning function, the autonomous detection calibration function and the risk tracing and countermeasure matching function, long-term reliable operation of the system is guaranteed, powerful support is provided for clinical decision making, and the risk assessment method is suitable for clinical decision making. The surgical risk and the complication occurrence rate are effectively reduced.

Embodiments include methods of identifying a personalized cardiovascular device based on patient-specific geometrical information, the method comprising acquiring an anatomical model of at least part of the patient's vascular system; performing, using a processor, one or more of geometrical analysis, computational fluid dynamics analysis, and structural mechanics analysis on the anatomical model; and identifying, using the processor, a personalized cardiovascular device for the patient, based on results of one or more of the geometrical analysis, computational fluid dynamics analysis, and structural mechanics analysis of anatomical model.