AI-Powered Robotic Surgery

Tracking bones and surgical instruments in robot-assisted surgery without line-of-sight requirements. The system uses alternative tracking methods like inertial sensors or ultrasound imaging connected to the objects, along with robot arm position data, to continuously track and output the position and orientation of the objects in the surgical frame of reference. This allows tracking bones with limited exposure or hidden areas by registering them with the robot arm and leveraging the robot's position sensors instead of relying solely on direct line-of-sight sensors.

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Determining the configuration of a tool inside a catheter using a neural network trained on images of the tool being inserted into the catheter. The network analyzes live images of the tool as it's being advanced into the catheter to determine the tool's orientation and location inside the catheter. This allows accurate tracking of the tool's position and orientation inside the catheter, even when visibility is limited. The neural network is trained by feeding it images of the tool being inserted into the catheter with known orientations, so it learns to recognize the tool's appearance in different configurations.

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Selecting the best anchor UE for sidelink positioning in wireless communications by providing comprehensive anchor UE selection criteria. A candidate anchor UE can signal its position accuracy, type, source, age, validity, and assistance data validity to other UEs. This allows sidelink-capable UEs to choose the most suitable anchor for positioning based on factors like reliability, longevity, and accuracy.

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Endoscope control system that improves manipulation of the distal end of the scope during procedures by using machine learning to determine appropriate movements based on the endoscopic image. The system acquires an endoscopic image, determines operation details like bending angles and motion paths using trained machine learning models, and then controls the scope movement based on the learned details. This allows the system to properly navigate through complex anatomy by leveraging historical images and labels to learn optimal movements.

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Robotic surgery system that uses AI and machine learning to improve surgical planning and robotic control. The system analyzes data from past surgeries to generate feedback for surgeons and the robots. It can predict changes in organ function based on surgical plans and suggest adjustments. It uses imaging to identify vasculature within the organ and estimates long-term blood flow to determine function loss. The AI-generated scores can help optimize treatment trajectories to avoid unnecessary organ damage.

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Enhancing surgical workflows using computer-assisted surgery with improved tracking techniques. The methods involve attaching flexible fiber optic shape sensing (FOSS) devices to anatomical structures or surgical instruments in a surgical environment. Reflectivity data from the FOSS devices is used to track their locations. This allows accurate tracking of anatomy and instruments inside patients, without line-of-sight or EM interference. The FOSS devices can also detect flexibility changes in instruments. This data is used to automatically control instrument behavior and prevent collisions.

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Ultrasonic surgical instrument with a movable ultrasonic transducer assembly for inserting the ultrasonic blade into a patient. The transducer assembly is attached to a carrier that can slide along the instrument's longitudinal axis. This allows the transducer to move between a proximal position near the handle and a distal position near the blade tip. The carrier is guided along rails and driven by a screw. The distal movement extends the ultrasonic blade for insertion into the patient. The robotic system can have this instrument mounted on a robotic arm for precise positioning during surgery.

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Automated planning of bone correction using external fixation devices by generating virtual models and optimization algorithms. The method involves creating virtual models of deformed bones using images and autonomously overlaying graphical templates with landmarks. These templates are used to generate virtual fixation rings and rings can be graphically manipulated to optimize the fixation frame configuration for bone correction. The automated planning simplifies and expedites finding the optimal fixation frame setup for complex bone deformities compared to manual configuration.

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Accurately determining the position of an anatomic part of a patient's body during robot-assisted surgery to account for patient movement and compensate for IMU drift. The system uses an IMU attached to the patient's anatomy to track its position. It resets the IMU's drift periodically by detecting points in time when the patient's respiration and heartbeat are minimally moving. This provides repeatable, stationary points for resetting the IMU's reference.

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Adapting a biomechanical model of an anatomical body part to match a patient's current status during a medical intervention. The method involves determining the current step of the intervention, then acquiring data like region-of-interest, imaging, and instrument guidance to adapt the biomechanical model. This allows updating the model during the intervention based on real-time changes in the patient's anatomy.

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Automated and robotic surgical procedures using AI to transcribe, analyze, and present patient data during surgery. The system collects data from medical professionals, sensors, and imaging devices. It analyzes the data using AI models and presents the findings in a conversational interface to the surgeon. The surgeon can provide additional data which is further analyzed. This allows real-time analysis and decision making during surgery. The AI can also generate surgical plans, simulate procedures, and optimize outcomes. The goal is to prevent errors, improve outcomes, and reduce recovery time using AI-assisted surgery.

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Robotic surgical system for precise placement and guidance of tools during surgery, particularly spinal surgery. The system uses a portable robotic arm with a force-controlled end effector that holds surgical tools. The robotic arm allows intuitive, manual positioning of the tool for accurate trajectories without pre-op planning. The end effector can switch between force control (impedance) and holding modes. It calculates trajectories from images and real-time position. The robotic cart stabilizes during surgery. The system enables precise, repeatable tool placement and guidance for spinal procedures like drilling.

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Robotic system for precise instrument positioning during minimally invasive surgeries without requiring external tracking devices. The system uses real-time instrument tracking to align the robotic arm with the planned trajectory. It calculates the error between the tracked instrument position and the target, then iteratively moves the arm to close the gap. This avoids the need for external markers or registration steps since the robot aligns based on the instrument's own feedback.

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Robotic surgical system that can be fully inserted into a patient's body for minimally invasive procedures without the need for external ports. The robotic device consists of segmented arms with motors and operational components that can be assembled inside the body. It's controlled externally via a support structure that extends through an incision. This allows the robot to be completely inside the body for procedures like biopsy, dissection, and retraction without external access. The support structure provides power and communication to the robot. The system can also have sealing ports to create a closed environment inside the body.

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Robotic surgical system for spinal, neuro, and orthopedic surgeries that improves precision, reduces radiation exposure, and allows easy sterilization. The system has a robotic arm with a force/torque controlled end-effector to hold a surgical tool. A tracking detector detects tool/patient position. A processor maintains the tool on a pre-planned trajectory using real-time positions. The robotic arm automatically adjusts tool position as the vertebra moves to keep the trajectory. This allows stable, guided instrument placement without requiring manual coordination with 2D images.

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Navigation of surgical robots to prevent collisions with patient anatomy during movements. The method involves defining 3D volumes around critical anatomical elements based on registration data. The robot arm is then controlled to avoid passing through these volumes during movements. This prevents unintentional collisions with patient anatomy.

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Robotic laser surgery system that uses computer-modulated laser intensity to precisely and accurately remove tissues during surgical procedures. The system involves a surgical robot with a laser attached. Before surgery, a pre-operative plan is generated based on patient and procedure data. The plan includes initial laser settings. During surgery, imaging and sensors continuously monitor the area. The computer determines real-time adjustments based on the monitoring. The laser automatically adjusts during surgery to ensure accurate and precise removal of tissues.

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Automatically adjusting camera views in a surgical system to capture specific locations of interest during procedures. The system analyzes surgical session data to identify events and determine associated locations. It then directs the camera to automatically adjust its view to capture those locations without manual intervention. This allows quick visualization of critical areas during procedures without requiring the user to move the camera.

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Robotic catheter system for accurate and efficient targeting of hard-to-reach locations in the body like peripheral lung nodules. The system uses a robotic catheter with segments that can bend individually. A tracking device monitors the catheter tip position. The system allows tilting and offsetting the tip using separate bending operations. It estimates sampling locations based on tip position and target. A display shows the expected locations history as the tip moves. This helps avoid repeated attempts to align the tip.

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Robotic system to accurately reduce ankle fractures by assisting surgeons during the procedure. The system uses a separate actuatable section and a passive arm that attach to the tibia and fibula respectively. A controller limits the forces and torque during reduction based on predefined max values. The system helps reduce ankle fractures by accurately aligning the distal tibiofibular joint using robotic assistance. This improves reduction accuracy compared to manual methods and reduces radiation exposure compared to fluoroscopy.

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