Intelligent mobile device applied in medical imaging systems for automatic placement of mr coils

Abstract

Disclosed in the present invention is an intelligent mobile device applied in medical imaging systems for automatic placement of MR coils. The intelligent mobile device comprises: an MR coil placement table; an MR coil gripping device, which comprises a gripper, a vertical lifting operation module, a horizontal telescopic operation module and a horizontal angle module, wherein the gripper is separately connected to the vertical lifting operation module, the horizontal telescopic operation module and the horizontal angle module, and the vertical lifting operation module, the horizontal telescopic operation module and the horizontal angle module are each provided with an electric motor customized by using a completely non-magnetic material, so as to use and control the gripping device to grip a corresponding MR coil to lift vertically and move horizontally and accurately place the corresponding MR coil at a preset position; and a controller, which controls the completion of moving an MR coil from an adapted storage space position to a pre-placement position, including an initial position, of a medical imaging system, and removing the MR coil from the medical imaging system and placing same at the corresponding adapted storage space position.

Description

Intelligent mobile device for automatic placement of MR coils in medical imaging systems Technical Field

[0001] The present invention relates to auxiliary equipment for medical equipment, in particular to an intelligent mobile device for automatically placing MR coils in a medical imaging system. Background Art

[0002] Typically, a physician orders an MR exam for a patient, which is then performed by a technician. The technician is responsible for operating, positioning, acquiring, and transmitting the medical images. These images are stored in a metadata format that provides context for manual or automated analysis. This metadata can include information about the image's orientation, the anatomical region being imaged, and / or conditions important for proper analysis.

[0003] In MR imaging, the coupling between the subject and the coil significantly impacts the signal-to-noise ratio. The coil plays a crucial role in image data acquisition and subsequent MR image reconstruction. Magnetic resonance imaging signals are very weak, only at the microvolt level. Different coils are used for different parts of the human body. There are approximately 20 types of MR coils commonly used clinically. Proper positioning is interrelated with factors such as contrast, spatial resolution, and scan time. Accurate coil placement can significantly improve MR image quality. However, for many years, medical staff have relied on manual placement of these bulky coils.

[0004] For a long time, medical staff have been manually placing different coils for different examination sites. This is heavy, bulky, and requires lifting over the patient's body, which is labor-intensive and can easily lead to medical disputes if the coils accidentally touch the patient. The present invention is a solution to these long-standing problems. Technical Solutions

[0005] The present invention provides an intelligent mobile device for automatically placing MR coils in a medical imaging system, so as to solve the existing technical problem that different coils for different examination parts are placed manually by medical personnel.

[0006] Intelligent mobile devices for automatic placement of MR coils in medical imaging systems, including:

[0007] MR coil placement table: includes multiple storage spaces, each space is used to place objects with coils of different shapes and specifications for scanning different parts of the human body;

[0008] The MR coil gripping device includes a gripper, a vertical lift module, a horizontal telescopic module, and a horizontal angle module. The gripper is connected to the vertical lift module, the horizontal telescopic module, and the horizontal angle module, respectively. The vertical lift module, the horizontal telescopic module, and the horizontal angle module are each equipped with a custom motor made of completely non-magnetic material to control the gripping device to grasp the vertical lift and horizontal movement of the corresponding MR coil and accurately place it in a preset position.

[0009] The controller includes a configuration file and an execution unit. The configuration file includes at least a position configuration file and a path motion configuration file. The position configuration file includes the initial positions for placing different coil objects on the medical imaging system and the storage space positions for placing different coil objects on the MR coil placement table. The path motion configuration file includes at least pre-stored motion information of different MR coils from the adapted storage space positions to the initial positions of the medical imaging system and motion information of different MR coils from the adapted medical imaging system grasping positions to the adapted storage space positions. The execution unit receives instructions to complete the movement of the MR coils from the adapted storage space positions to the pre-placement positions of the medical imaging system including the initial positions, and the removal of the MR coils from the medical imaging system and their placement in the corresponding adapted storage space positions. Beneficial effects

[0010] The key advantage of the automated placement and real-time movement device is that it reduces workload for medical staff, improves efficiency, and is cost-effective. It also avoids medical disputes caused by manual placement and contact with patients, making it highly practical for widespread adoption. The entire system utilizes open-source hardware and software, boasting a simple structure, easy software modification, reliable functionality, ease of use, and high speed. The device is expected to be highly praised in MRI rooms for its cost-effectiveness and is expected to be widely adopted in hospitals for its intelligent operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] FIG1 is a schematic diagram of an example magnetic resonance imaging system;

[0012] FIG2 is an exploded view of an implementation of an MR coil placement table;

[0013] FIG3 is an implementation diagram of a robotic arm;

[0014] FIG4 is a schematic diagram of a smart mobile device for automatically placing MR coils in a medical imaging system. Modes for Carrying Out the Invention

[0015] In the examples shown, specific reference is made to magnetic resonance imaging systems. It will be appreciated that the following figures are also generally used to discuss medical imaging systems, such as PET systems, SPECT systems, CT systems, and X-ray systems. Thus, references to magnetic resonance imaging systems can also be understood as descriptions of medical imaging systems. References to pulse sequence commands can also be understood as descriptions of medical imaging system commands. Medical image data can also be references to magnetic resonance data or be understood as descriptions of medical image data. References to magnetic resonance imaging protocols can also be understood as descriptions of medical imaging protocols.

[0016] Figure 1 illustrates an example of a magnetic resonance imaging system. The magnetic resonance imaging system includes a magnet 102. Magnet 102 can, for example, be a superconducting magnet. Alternatively, magnet 102 can be a resistive magnet. It is also possible to use different types of magnets; for example, split cylindrical magnets and so-called open magnets can also be used. A split cylindrical magnet is similar to a standard cylindrical magnet, except that the cryostat has been split into two sections to allow access to the magnet's isoplane, enabling the magnet to be used, for example, in conjunction with charged particle beam therapy. An open magnet has two magnet sections, one above the other, with a space large enough to accommodate the subject. The arrangement of the two sections is similar to that of Helmholtz coils. Open magnets are popular because the subject is less confined. Inside the cylindrical magnet's cryostat is a collection of superconducting coils. Within the bore 106 of the cylindrical magnet 102 lies an imaging zone 108, where the magnetic field is sufficiently strong and uniform to perform magnetic resonance imaging. A region of interest 109 within the imaging zone 108 is shown. An object 118 is shown supported by an object support 120 such that at least a portion of the object 118 is within the imaging zone 108 and the region of interest 109. Also within the bore 106 of the magnet is a collection of magnetic field gradient coils 110 for acquiring primary magnetic resonance data to spatially encode magnetic spins within the imaging zone 108 of the magnet 102. The magnetic field gradient coils 110 are connected to a magnetic field gradient coil power supply 112. The magnetic field gradient coils 110 are intended to be representative. Typically, the magnetic field gradient coils 110 comprise a collection of three discrete coils for spatially encoding in three orthogonal spatial directions. The magnetic field gradient power supply supplies current to the magnetic field gradient coils. The current supplied to the magnetic field gradient coils 110 is controlled over time and can be ramped or pulsed.

[0017] Adjacent to the imaging zone 108 is a radio frequency coil 114, which also receives radio transmissions from spins within the imaging zone 108. In some examples, the radio frequency coil can also be configured to manipulate the orientation of magnetic spins within the imaging zone 108. The radio frequency antenna may include multiple coil elements. An radio frequency antenna may also be referred to as a channel or antenna. The radio frequency coil 114 is connected to a radio frequency receiver or transceiver 116. The radio frequency coil 114 and radio frequency transceiver 116 can optionally be replaced by separate transmit and receive coils, or separate transmitters and receivers. It should be understood that the radio frequency coil 114 and radio frequency transceiver 116 are representative. The radio frequency coil 114 can also represent a dedicated transmit antenna and a dedicated receive antenna. Similarly, the transceiver 116 can also represent a separate transmitter and receiver. The radio frequency coil 114 can also have multiple transmit / receive elements, and the radio frequency transceiver 116 can have multiple transmit / receive channels. For example, if a parallel imaging technique such as SENSE is implemented, the radio frequency coil 114 can have multiple coil elements.

[0018] The transceiver 116, gradient controller 112, current source 124, and magnet power supply 104 are shown as being connected to a controller 126. Different regions of interest 109 generally require different coils to be placed in different examination locations.

[0019] The present invention provides an intelligent mobile device for automatically placing an MR coil in a medical imaging system, comprising:

[0020] Please refer to Figure 2, which shows an exploded view of one implementation of an MR coil table. The table includes multiple storage spaces, each for placing coils of varying shapes and sizes for different body parts. Considering the varying sizes of coils, an open-type configuration can be used, as shown in Figure 2.

[0021] The MR coil grasping device includes a gripper, a vertical lifting operation module, a horizontal telescopic operation module and a horizontal angle module. The gripper is connected to the vertical lifting operation module, the horizontal telescopic operation module and the horizontal angle module respectively. The vertical lifting operation module, the horizontal telescopic operation module and the horizontal angle module are respectively equipped with motors customized with completely non-magnetic materials to control the vertical lifting and horizontal movement of the corresponding MR coil by the gripper device and to place it precisely in a preset position. Please refer to Figure 3. The MR coil grasping device includes a clamper, a vertical lifting operation module, a horizontal telescopic operation module and a horizontal angle module. It further includes a clamping device including a guide rail 14, at least two clamp adjustment hydraulic cylinders 20 and at least two groups of clamp assemblies 10. Each of the clamp adjustment hydraulic cylinders 20 is powered by the corresponding clamp assembly 10. The clamp assembly 10 is slidably connected to the guide rail 14. The clamp assembly is used to clamp the MR coil. The clamp hydraulic system is powered by the clamp adjustment hydraulic cylinder 20 and is used to drive the clamp assembly 10 to slide on the guide rail 14. A walking device 19 is connected to the clamp device to drive the clamp device to move.

[0022] The controller includes a configuration file and an execution unit. The configuration file includes at least a position configuration file and a path motion configuration file. The position configuration file includes the initial positions for placing different coil objects on the medical imaging system and the storage space positions for placing different coil objects on the MR coil placement table. The path motion configuration file includes at least pre-stored motion information of different MR coils from the adapted storage space positions to the initial positions of the medical imaging system and motion information of different MR coils from the adapted medical imaging system grasping positions to the adapted storage space positions. The execution unit receives instructions to complete the movement of the MR coils from the adapted storage space positions to the pre-placement positions of the medical imaging system including the initial positions, and the removal of the MR coils from the medical imaging system and their placement in the corresponding adapted storage space positions.

[0023] When the MR coil is placed at a moving position on the medical imaging system,

[0024] multiple collectors are arranged on the gripper;

[0025] [Corrected 01.07.2024 according to Rule 26] The execution unit further includes: initial configuration When the coil object is placed in the initial state, start the collector to collect the current position information of the pre-detection part (x i ,y i ), taking the initial position x(k), y(k) as the reference position, calculate the pre-detection position data Z collected by each collector i (K), i = 1, 2...i is the number of the collector; each collector calculates the Z of the collector at different time points.i (K), the position data value Z calculated at different time points i (K) can only be used if the deviation value is less than a certain threshold, otherwise it is considered that the pre-detection part is moving or the collector is moving, and the calculated Z i (K) needs to be recalculated at the next moment;

[0026] [Corrected 01.07.2024 in accordance with Article 26]

[0027] The least square method is used to calculate the current precise position information of the pre-detection part by combining these data, and then the execution unit is controlled to move the MR coil accurately to the specified position.

[0028] A walking mechanism is arranged below the MR coil placing table or the MR coil grabbing device.

[0029] In order to automatically control the placement of the MR coil, optimize the running route and avoid unnecessary touches, in various embodiments of the present application, when the position of the MR coil is a moving position on the medical imaging system,

[0030] A plurality of collectors are arranged on the gripper, wherein the collectors include at least one sensor device;

[0031] The execution unit further includes: obtaining the motion trajectory of the execution unit based on the dynamic window algorithm prediction, evaluating the motion trajectory and selecting the optimal trajectory for operation, specifically including;

[0032] Obtaining the current speed, motion characteristics, target endpoint, and obstacles of the gripper, wherein the motion characteristics include acceleration, minimum speed, and maximum speed;

[0033] At any time t, the gripper forms multiple sets of motion trajectories in the two-dimensional space of the current velocity (v, ω) to form an initial velocity search space;

[0034] Sampling the speed in the speed search space under the constraints of the motion characteristics, the target endpoint, and obstacles and generating speed samples, and further narrowing the speed search space based on the speed samples to determine a final speed search space that the gripper can reach;

[0035] Determine the motion trajectory of the gripper based on the acquired speed samples, and determine the next operating point on the motion trajectory;

[0036] An evaluation function is used to score each motion trajectory, and the optimal speed sample is taken and sent to the execution unit for execution. The speed range that the execution unit can reach is determined based on the current speed and motion characteristics of the execution unit. Since the ultimate goal of the motion is to reach the target point, when it reaches the vicinity of the target point, it is necessary to reduce the speed of the execution unit, that is, to further limit the speed range of the execution unit to ensure that the execution unit can reach the target point smoothly. Finally, based on the number of samples given manually, a number of discrete speed samples are obtained within the limited speed range, including linear velocity v and angular velocity ω. Determining the motion trajectory based on the speed sample is simple operational knowledge. The main thing to pay attention to is whether the sample is generated by the simulation time or the simulation cycle. The simulation time refers to a period of simulation time set manually, which defaults to 1 second, and the simulation cycle refers to the actual control cycle of the algorithm, which defaults to 0.1 second.

[0037] The full name of the DWA algorithm is dynamic window approach. Its algorithm process is mainly divided into two main processes: simulating the motion trajectory of the execution unit and evaluating the trajectory to select the optimal trajectory. The dynamic window expresses that the number of simulated motion trajectories is limited, mainly because the execution unit can only reach a certain speed within a short control cycle.

[0038] In various embodiments of the present application, the final speed search space Vr includes at least the intersection of a first speed set Vs under a first constraint, a second speed set Vd under a second constraint, and a third speed set Va under a third constraint, that is, Vr=Vs∩Vd∩Va, wherein the first speed set includes the speed search space under the maximum speed and minimum speed boundary limits of the gripper itself, the second speed set includes the speed search space under the speed limit during the start and stop action of uniform acceleration / deceleration motion, and the third speed set includes the speed search space under the speed limit required for the gripper to avoid obstacles. The kinematic constraints and environmental constraints of the above-mentioned execution unit can reduce the sampling speed to a more precise area, automatically control the placement of the MR coil, optimize the running route to avoid unnecessary touches, and improve running efficiency.

[0039] In order to automatically control MR coil placement and predict and avoid unnecessary collisions in advance, in various embodiments of the present application, determining the motion trajectory of the gripper based on the acquired velocity samples and determining the next reference point on the motion trajectory includes:

[0040] After determining the final velocity search space Vs, sample uniformly in the space according to the preset sampling interval;

[0041] In this velocity search space, the resolutions are set for the linear velocity and angular velocity respectively, and the sampling resolutions are represented by Ew and Ev respectively. The number of sampling velocity groups is determined as follows:

[0042] n=[(V high −V low ​) / Ev​]⋅[(W high −W low ​) / Ew​];

[0043] When sampling a set of (v, w) in the final velocity search space Vs, the motion trajectory of the gripper is predicted and updated based on the kinematic model. The trajectory prediction calculation formula is as follows:

[0044] Xk=X k-1 +v*cos(θ k-1 )Δt;

[0045] Yk=Y k-1 +v*sin(θ k-1 )Δt;

[0046] θ k =θ k-1 +wΔt;

[0047] Among them, V high ​、V low ​、W high ​、W low are the upper and lower limits of the speed search space; (X, Y, θ) represents the position of the gripper, k represents the sampling time, and Δt represents the sampling interval.

[0048] In order to automatically control MR coil placement, predict and avoid unnecessary collisions in advance, and improve the accuracy of the coil prediction model, in various embodiments of the present application, the use of an evaluation function to score each motion trajectory and taking the optimal velocity sample to send to the execution unit for execution includes:

[0049] Mapping the contour of the gripper to the global coordinate system through each motion trajectory;

[0050] Analyze the cost values ​​on the contour edge and select the maximum cost value as the obstacle cost, so as to determine whether the gripper will collide with the obstacle;

[0051] If the contour is a polygon, obtain the coordinates of a point on the contour and the coordinates of adjacent contour points, determine the maximum cost value of the current contour point and the adjacent contour points, calculate the maximum cost value of all edges of the polygon, and thus determine whether there is a collision with an obstacle.

[0052] In another embodiment, in order to improve the process of automatically placing the coil and avoid unnecessary touches, avoid damage to the device, and improve the accuracy of the route prediction model, a target cost function is also included. First, the local target point is determined based on the boundary of the global path and the local cost map, and then a grid map is generated based on the local target point. The value at each grid represents the distance from the current grid to the target point. For the obstacle grid, the distance to the target point is directly set to infinity. Finally, based on the position of the grid at the end point of the trajectory, the distance from the position to the target point is directly obtained in the map through the index as the cost from the target point. Therefore, the main task of the target cost function is to generate a grid map. Alternatively, a path cost function, the implementation principle of this cost function is similar to that of the target cost function, except that the function uses all points on the local path as the starting point to expand outward to construct a grid map, and the average value of the sum of the distance values ​​of all points on the simulation trajectory is used as the cost value of the trajectory.

[0053] In various embodiments of the present application, the MR coil is a phased array coil, including multiple coil units, and the coil units are used independently or in combination; multiple coil units form a coil group, and multiple coil groups share a receiving channel for MRI parallel acquisition imaging. Regardless of the domain based correction, the following steps need to be performed when MRI performs parallel acquisition imaging: (1) Pre-scanning, before all sequences, or before each sequence, obtain sensitivity information data of each small coil unit. (2) Sequence scanning, each small coil unit obtains uncorrected image data with folding artifacts. (3) The data is processed by the corresponding algorithm, and the correction and synthesis are performed to obtain a complete image without folding artifacts. The phased array coil can be simply understood as a large coil of uniform volume composed of multiple small surface coils / units. The combination of multiple units of coils can better fit the scanning area to obtain images with higher signal-to-noise ratio and resolution, and can also obtain a larger range of scanning images.

[0054] In various embodiments of the present application, the internal arrays of the coil units are arranged in parallel in the head and foot, front and back, and left and right directions. During 3D imaging, the coil units are capable of simultaneously performing accelerated scanning in any two directions, with significantly different sensitivities. During parallel acquisition, the acceleration direction supports any of the head and foot, left and right, and front and back directions. In another embodiment, the internal arrays of the coil units are arranged in a non-parallel relationship in the head and foot directions, with the same sensitivity distribution. During parallel acquisition, the acceleration direction supports both left and right and front and back acceleration. Best Mode for Carrying Out the Invention

[0055] The basic principle of handling and placement is to utilize a single-chip microcontroller (MCU) with multiple sensors, a MCU, and an actuator motor to detect the surrounding environment. Intelligent processing algorithms are then used to comprehensively assess various situations. The upper computer's actuator unit then notifies the coils with different functions at different locations on the coil holder. Multiple sensors accurately determine the placement of the coils. The operational process includes three types of sensors: ultrasonic sensors, human motion sensors, and vertical and horizontal motion sensors. The intelligent processing algorithm is implemented through a combination of the upper and lower computers and is integrated into the STM32 chip. The actuator unit utilizes four DC motors and two stepper motors. It can accurately navigate the MRI room, grasp the MRI coil, and precisely position it at the patient's examination site.

[0056] The automatic placement mobile device primarily consists of an ultrasonic sensor array, a position calculation module, an environmental detection module, a single-chip microcomputer module, a battery power supply module, a drive control module, and a DC motor / stepper motor module. The ultrasonic sensor array utilizes multiple sets of ultrasonic sensors to achieve 360-degree ultrasonic ranging. The position calculation module utilizes infrared photoelectric sensors, inductive sensors, and laser ranging sensors to form an embedded human position measurement system. The single-chip microcomputer module is responsible for determining, processing, and integrating all information. The drive component isolates and amplifies the control and actuator components. The battery power supply module uses a high-energy lithium battery as its power source, converting it into power for other modules. A DC motor drives the operation, while a stepper motor performs vertical and horizontal movement to accurately grasp the MR coil. The single-chip microcomputer issues commands to grasp different coils based on information from the host computer regarding different scanning locations. After grasping, the mobile component continues to operate, transporting the MR coil to the precise scanning location.

[0057] Our invention primarily utilizes intelligent control: based on single-chip microcomputer sensor technology, it integrates a controller, memory, timer, monitor, host and slave terminal monitoring, and data processing systems. The mobile device performs specified actions according to programmed operating instructions. The single-chip microcomputer offers the advantages of compact size, low energy consumption, and reliability. Multiple control modes can be incorporated to ensure the mobile device accurately and automatically positions the MR coil. This achieves artificial intelligence-based single-chip microcomputer control and management, replacing traditional manual service models. Our device seamlessly connects to the hospital's information system through MR system patient information from the physician workstation. Independent DC motors and stepper motors drive the vertical lift assembly and horizontal movement assembly, respectively. The independently controlled mechanical connection effectively reduces mechanical noise, minimizes failure rates, and offers a more compact structure, reducing motor power and size. Honeywell angle sensors, comprised of position sensors, are installed at corresponding locations on the device. They collect various data, convert them into digital signals, and enable real-time control.

[0058] Main module components

[0059] 1. Ultrasonic sensor

[0060] The ultrasonic sensor array includes multiple groups of ultrasonic sensors to achieve 360-degree ultrasonic ranging. Since the detection angle of a single ultrasonic sensor is small, a method of multiple sensors working in parallel is adopted to increase the detection and obstacle avoidance capabilities. The device uses three different types of ultrasonic sensors from Honeywell in the United States: 946-MV-2D-2C0-175E, with a beam angle of 50. The sensor measurement range is 200-2000mm; 943-F4Y-2D-ID0-180E, with a beam angle of 80. The sensor measurement range is 200-2000mm.

[0061] The 941-C2V-2E-IC0 has a beam angle of 100°. The sensor has a measurement range of 200-1500mm. The 50° and 80° sensors can output both voltage and current signals, while the 10° sensor only outputs an analog voltage signal. This requires an A / D conversion circuit for control. Considering the beam angle effect of ultrasonic sensors, which emit a beam of ultrasound that represents a surface rather than a single point, multiple sampling points are designed in the equipment room to control obstacle avoidance and achieve accurate operation control. The combined ultrasonic sensor provides high detection accuracy, with detection ranges of 1cm to 800cm and 1cm to 1000cm (10 meters). The detection frequency can reach 500Hz, meaning 500 detections per second. This enables precise transmission of turn signal commands.

[0062] 2. Infrared sensor

[0063] The infrared sensor system forms a measurement system that can detect the position, direction, speed, and spatial distance of the MR coil. The specific chip selection is as follows.

[0064] This infrared sensor offers excellent sensitivity, temperature stability, low noise, simplified application programming, and excellent remote control capabilities. High and low-level outputs, comprised of an OC gate, enable operational control. An internal low-pass filter provides a fast-mode flip-flop interface for both transmit and receive. It can be accessed via SPI (3-wire or 4-wire) or I2C digital interfaces. This infrared photoelectric sensor, model DZ-31, utilizes standard technology manufactured by Omron Corporation of Japan, offering high sensitivity, linearity, and high precision.

[0065] 3TL-Q5 inductive sensor

[0066] When the control system starts running the stepper motor according to the programmed program and reaches the designated position, the drive stops. The inventive design uses a TL-Q5M inductive sensor for operational safety control. A 15mm x 20mm rectangular iron sheet is installed between the measured positions. When the OMRON TL-Q5M inductive sensor's internal sensor receives this information, it issues a stop command, outputting a high level to the DKC-1A drive controller to stop the stepper motor. This creates a dual safety feature. The stepper motor's inherent operational detection is sensitive and reliable, ensuring it operates within the designed distance. Combined with the inductive sensor's control, operation is more stable and safer. The TL-Q5M inductive sensor features a non-detachable, integrated design with three color-coded cables for easy identification. The device also incorporates comprehensive protection features, ensuring that even accidental wiring errors prevent the sensor from burning out. It offers excellent value for money, fast signal conversion, stable performance, and a wide voltage range.

[0067] 4 single chip microcomputer modules

[0068] The STM32 microcontroller circuit uses the STM32F103RB as the central control chip. In this hardware control circuit design, an external 8MHz crystal is used as the microcontroller system's clock input source. The clock is multiplied to 72MHz by an internal PLL (phase-locked loop) and used as the microcontroller system's clock. Serial Wire Debug (SWD) mode is used for debugging and downloading programs. For human-computer interaction, two buttons and an LED are included to control the patient examination area of ​​the MRI system and indicate the MR coil's position. Furthermore, the minimum STM32 microcontroller system operates on a 3.3V power supply. This ARM processor offers high clock speed, rich interfaces, and low power consumption, meeting system design requirements. The STM32L series is based on the ultra-low-power ARM Cortex-M4 processor core and utilizes two unique STMicroelectronics energy-saving technologies: a dedicated 130nm low-leakage manufacturing process and an optimized energy-saving architecture, delivering industry-leading energy-efficiency performance. The products share a majority of pins, software, and peripherals, ensuring excellent compatibility and providing developers with maximum design flexibility.

[0069] 5MR coil vertical grab handle

[0070] The mechanical control of the MR coil gripper utilizes DC stepper motors and brushless DC motors. Three stepper motors are installed, responsible for vertical lift, horizontal extension, and horizontal angular control. These stepper motors can be customized using completely non-magnetic materials. The entire system features five motors. Two DC motors are used for operation. Ultrasonic sensors detect obstacles ahead to ensure accurate operation of the DC motors. The stepper motors are responsible for vertical lift, horizontal movement, and precise placement of the MR coil. The gripper is designed in a claw-like shape, capable of vertically gripping a weight greater than 1.5 times the maximum weight of the coil.

[0071] 6I2C bus control simplifies hardware configuration

[0072] The design utilizes the I2C bus to enhance the stability of the entire circuit. The I2C bus utilizes a two-wire inter-chip serial transmission bus. All nodes on the bus, including the main components of the automatic placement mobile device (microcontroller, and various interface modules), are connected to the SDA and SCL pins on the same line, achieving perfect half-duplex synchronous data transmission. This facilitates the construction of multi-machine systems and peripheral device expansion systems. The I2C bus uses a hardware-based device address setting method, completely eliminating the need for chip select line addressing through software addressing, thus enabling simple and flexible hardware system expansion. Data transmission on the I2C bus follows a prescribed data transmission format. Data is sent from the sensor to the microcontroller for processing, calculation, and control. The master controller initiates data transmission, sends a start signal, addressing information, and issues a stop signal at the end of the transmission. The slave device then responds as needed. The use of I2C significantly optimizes the bus structure, achieving stable transmission and control on the I2C bus. Implementing program control using the I2C bus effectively simplifies the hardware circuit structure of the automatic placement mobile device.

[0073] 7. Lithium iron phosphate battery as the main power source for automatic placement mobile device

[0074] Because the system operates in the dynamic environment of mobile grasping, the design utilizes a large-capacity lithium iron phosphate (LiFePO4) battery as the primary power source, with LiFePO4 as the positive electrode material. This lithium-ion battery offers a long lifespan (over 2,000 cycles with a standard charge rate (5-hour charge rate)), a high performance-price ratio, and long-term constant current discharge. Using a dedicated charger, the battery can be fully charged in just 40 minutes. Operating over a wide temperature and humidity range (-20°C to +75°C), LiFePO4 batteries exhibit no memory loss and can be used at any time, regardless of battery state. They are environmentally friendly, pollution-free, and highly stable. The LiFePO4 battery used in the mobile disinfection device is 24V, 20Ah, and measures 195x150x100. It is mounted on the bottom of the device. A switching power supply module also generates multiple DC voltages to provide stable DC voltages for the microcontroller sensors and operating components. The device requires multiple stable voltages to power the circuits. The linear regulation of traditional linear regulated power supplies results in significant heat loss during operation, resulting in an efficiency of only 30% to 50%, with nearly half of the electrical energy being wasted as heat. New switching power supplies operate in either a fully on or fully off state. Therefore, during operation, either a high current flows through the low-on voltage switching transistors or no current flows through them. This results in extremely low power consumption. In actual testing, the average efficiency of switching regulated power supplies can reach 70% to 90%. To improve operational stability, the LM2576 series switching power supply module was selected. It features a 3A current output, a step-down switching integrated voltage regulator circuit, and includes a fixed-frequency oscillator (52kHz) and a reference voltage regulator (1.23V). The LM2576 module requires minimal external components to create a highly efficient voltage regulator circuit. The patented power control module utilizes the LM2576 series, ensuring a stable, simple, and reliable control circuit.

[0075] 8 Application of non-magnetic materials

[0076] To ensure proper operation in a strong magnetic environment, the device must be designed with non-magnetic materials to facilitate interconnection and securement between modules. The sensor layout is determined by the sensor's characteristics and the size of the housing. The KS103 module needs to detect obstacles 180 degrees ahead and should be placed at the very front of the PCB. The pyroelectric PE module also needs to detect forward movement and should be placed below the corresponding KS103 module. The specific placement of the other modules depends on their structural dimensions. Furthermore, to ensure stable power supply for each module, a TI filter network is used for power supply filtering.

[0077] 9SCA61T angle sensor

[0078] The SCA61T angle sensor is a premium product from VTI of Finland. It consists of a high-quality silicon capacitive sensor element and interface electronics, assembled in an application-specific package. The silicon capacitive inclination sensor element is made of single-crystal silicon and glass. This design ensures reliability, excellent accuracy, and superior stability over time and temperature. The SCA61T angle sensor can withstand accelerations exceeding 40,000 g. The SCA61T is a 3D MEMS-based, single-axis inclination sensor that provides level measurement instrument-grade performance. The SCA61T sensor's sensing element must remain parallel to the measurement platform during measurement, and the sensor's two axes must be perpendicular to each other. The core of the SCA61T angle sensor is the symmetrical capacitive block of the micromachined accelerometer element. It consists of three silicon wafers separated by a thin glass membrane. The central silicon wafer is a cantilevered, multi-ray structure, with a large mass placed on top. The capacitance and spring constant are optimized independently, enabling the SCA61T to achieve excellent measurement results in the low-g range. Sometimes, gravity and acceleration acting on the silicon wafer can cause the oscillation of a single-crystal silicon electron beam to bend. This deviation can be measured as a change in the distance between two metal film electrodes in a capacitor. Micromechanical chips make it relatively easy to detect relatively large capacitances and capacitance changes. The SCA61T sensor outputs angle data. The control signal is generated by a microcontroller based on real-time data from the machine room's location and environment. Data is written on the rising edge of the microcontroller's clock signal, and read on the falling edge. Combined with vertical and horizontal sensors, it automatically positions the MR coil.

[0079] 10Automatic placement mobile device control firmware design

[0080] a: Programming plan

[0081] The system requires a combination of hardware and software to function properly. Its design consists of three functional modules. First, data collected by the infrared photoelectric sensor, infrared induction sensor, and ultrasonic sensor is transmitted to the microcontroller via I2C. The data is then processed within the STM32 microcontroller. Finally, an alarm algorithm is integrated into the program, combining data from various sensors to simulate different unexpected user situations and generate different alarm modes. The design of the microcontroller software can be divided into three main steps: system initialization, hardware testing, and data processing and judgment. System initialization is the beginning of the program and an essential part. It ensures that all sensors are functioning properly. Hardware testing ensures that every component is functioning properly, significantly reducing debugging time. Data processing and judgment algorithms are the core of the entire program. The diverse data from different sensors requires comprehensive judgment to minimize errors.

[0082] B: Multi-channel sensor design

[0083] The infrared sensor debugging method uploads position status data to the microcontroller and then monitors it in real time within the debugging program. After the system is powered on, each sensor begins operating. The infrared photoelectric sensor module uploads position and distance data, while the ultrasonic sensor module uploads energy sensing information about the forward area. All this information is uploaded to the STM32 microcontroller. The STM32 microcontroller reads the data and sends it to the actuator. The host computer's RS232 serial port reader program reads, calculates, and displays the data uploaded by the microcontroller.

[0084] in conclusion

[0085] This patented automatic MR coil placement and movement system utilizes information fusion from multiple sensors and is highly practical. Its main advantages are: (1) It is highly intelligent, as it uses multiple sensors to collect information about the surrounding environment and coil position, and can accurately identify the position of the human body through sensors, enabling precise placement. The algorithm is flexible, as it can accurately position different parts of the MRI examination to achieve better clinical examination results.

[0086] The present invention is highly intelligent and flexible.

[0087] The key advantage of the automatic placement and real-time movement device is that it reduces workload for medical staff, improves efficiency, and is cost-effective, making it highly practical for widespread adoption. The entire system utilizes open-source hardware and software, resulting in a simple structure, easy software modification, reliable functionality, ease of use, and high speed. The device is expected to be highly praised in MRI rooms for its cost-effectiveness and is expected to be widely adopted in hospitals for its intelligent operation.

[0088] Based on the same concept, some embodiments of the present application also provide an electronic device. This electronic device includes a memory and a processor, wherein the memory is used to store a processing program, and the processor executes the processing program according to instructions. When the processor executes the processing program, the rehabilitation care method for paralyzed patients described in the aforementioned embodiments is implemented. The electronic device used in this embodiment can be an execution unit.

[0089] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. An intelligent mobile device for automatically arranging MR coils in a medical imaging system, characterized in that, Comprising: MR Coil Placement Table: Comprising multiple storage spaces, each space for placing coil objects of different shapes and specifications for scanning different parts of the human body; MR Coil Gripping Device, comprising a gripper, a vertical lifting operation module, a horizontal telescopic operation module, and a horizontal angle module. The gripper is respectively connected to the vertical lifting operation module, the horizontal telescopic operation module, and the horizontal angle module. The vertical lifting operation module, the horizontal telescopic operation module, and the horizontal angle module are respectively equipped with motors customized with completely non-magnetic materials to control the vertical lifting and horizontal movement of the gripper to grip the corresponding MR coil and accurately place it at a preset position; Controller, comprising a configuration file and an execution unit. The configuration file at least includes a position configuration file and a path motion configuration file. The position configuration file includes the initial positions adapted for different coil objects on the medical imaging system and the storage space positions adapted for different coil objects on the MR coil placement table. The path motion configuration file at least includes pre-stored motion information of different MR coils from the adapted storage space positions to the initial positions of the medical imaging system, and motion information of different MR coils from the adapted gripping positions on the medical imaging system to the adapted storage space positions. The execution unit receives instructions to complete the pre-placement position of the MR coil from the adapted storage space position to the medical imaging system including the initial position, and the placement of the MR coil from the medical imaging system to the corresponding adapted storage space position.

2. [Corrected according to Rule 26 on 01.07.2024] The intelligent mobile device for automatically placing an MR coil in a medical imaging system according to claim 1, characterized in that, When the position where the MR coil is placed is a moving position on the medical imaging system, A plurality of collectors are provided on the gripper; The execution unit further includes: initially configured to start the collector when the coil object is placed in the initial state, respectively collect the current position information of the pre-detection part, use the initial positions x(k) and y(k) as the reference positions, and calculate the position data Z of the pre-detection part collected by each collector i (K), where i = 1, 2... and i is the number of the collector; calculate the Z of this collector at different time points for each collector i (K), and the deviation value of the position data value Z i (K) calculated at different time points can be used only when it is less than a certain threshold, otherwise it is considered that the pre-detection part is moving or the collector is moving, and the calculated Z i (K) needs to be recalculated at the next moment; Combining these data, the current precise position information of the pre-detection part is calculated by the least squares method, and then the execution unit is controlled to accurately move the MR coil to the specified position.

3. The intelligent mobile device for automatically arranging the MR coil in the medical imaging system according to claim 1, characterized in that, A walking mechanism is provided below the MR coil placement table or the MR coil gripping device.

4. The intelligent mobile device for automatically placing an MR coil in a medical imaging system according to claim 1, wherein MR Coil Gripping Device, comprising a gripper, a vertical lifting operation module, a horizontal telescopic operation module, and a horizontal angle module, further comprising a clamp device including a guide rail, at least two clamp adjustment hydraulic cylinders, and at least two groups of clamp assemblies. Each of the clamp adjustment hydraulic cylinders is power-connected to the corresponding clamp assembly. The clamp assembly is slidably connected to the guide rail. The clamp assembly is used for clamping the MR coil, and a clamp hydraulic system. The clamp hydraulic system is power-connected to the clamp adjustment hydraulic cylinders to drive the clamp assembly to slide on the guide rail; Walking Device, the walking device is connected to the clamp device to drive the clamp device to move.

5. The intelligent mobile device for automatically placing the MR coil in the medical imaging system according to claim 1, wherein When the position where the MR coil is placed is a moving position on the medical imaging system, A plurality of collectors are provided on the gripper, and the collectors at least include one sensor device; The execution unit further includes: predicting and obtaining the motion trajectory of the execution unit based on the dynamic window algorithm, and evaluating and selecting the optimal trajectory for operation, specifically including; Obtaining the current speed, motion characteristics, target end point, and obstacles of the gripper. The motion characteristics include acceleration, minimum speed, and maximum speed; At any moment t, the gripper forms multiple sets of motion trajectories in the two-dimensional space of the current speed (v, ω) to constitute an initial speed search space; Perform speed sampling on the speed search space under the constraints related to motion characteristics, target end point and obstacles to generate speed samples, and further narrow the speed search space according to the speed samples to determine the final speed search space that the gripper can reach; Determine the motion trajectory of the gripper according to the obtained speed samples, and determine the next running point on the motion trajectory; Use the evaluation function to score each motion trajectory, and send the optimal speed sample to the execution unit for execution.

6. The intelligent mobile device for automatically placing an MR coil in a medical imaging system according to claim 5, wherein The final speed search space Vr at least includes the intersection of the first speed set Vs under the first constraint condition, the second speed set Vd under the second constraint condition and the third speed set Va under the third constraint condition, that is, Vr = Vs ∩ Vd ∩ Va. Among them, the first speed set includes the speed search space under the maximum speed and minimum speed boundary limits of the gripper itself, the second speed set includes the speed search space under the speed limits during the start and stop actions of uniform acceleration / deceleration motion, and the third speed set includes the speed search space under the speed limits required for the gripper to avoid obstacles.

7. The intelligent mobile device for automatically placing an MR coil in a medical imaging system according to claim 5, wherein The determining the motion trajectory of the gripper according to the obtained speed samples and determining the next reference point on the motion trajectory includes: After determining the final speed search space Vs, uniformly sample in this space at a preset sampling interval; In this speed search space, set the resolution for the linear velocity and angular velocity respectively, and use Ew and Ev to represent the sampling resolutions respectively. Then the number of sampling speed groups is determined as follows: n = [(V high ​ - V low ​) / Ev​] ⋅ [(W high ​ - W low ​) / Ew​]; When sampling a group of (v, w) in the final speed search space Vs, predict and update the motion trajectory of the gripper based on the kinematic model. The trajectory prediction calculation formula is as follows: Xk = X k-1 + v * cos(θ k-1 ) Δt; Yk = Y k-1 + v * sin(θ k-1 ) Δt; θ k = θ k-1 + wΔt; Among them, V high ​, V low ​, W high ​, W low are the upper and lower limits of the speed search space; (X, Y, θ) represents the pose of the gripper, k represents the sampling moment, and Δt represents the sampling interval.

8. The intelligent mobile device for automatically placing an MR coil in a medical imaging system according to claim 5, wherein, The using the evaluation function to score each motion trajectory and sending the optimal speed sample to the execution unit for execution includes: Map the contour of the gripper to the global coordinate system through each motion trajectory; Analyze the cost values on the contour edge, select the maximum cost value as the obstacle cost, so as to determine whether the gripper will hit an obstacle; If the contour is a polygon, obtain the coordinates of a point on the contour and the coordinates of the adjacent contour points, determine the maximum cost value formed by the current contour point and the adjacent contour points, and calculate the maximum cost values of all sides of the polygon, so as to determine whether it collides with an obstacle.

9. The intelligent mobile device for automatically placing an MR coil in a medical imaging system according to claim 1, wherein The MR coil is a phased array coil, including multiple coil units, and the coil units are used independently or in combination; multiple coil units form a coil group, and multiple coil groups share a receiving channel for MRI parallel acquisition imaging.

10. The intelligent mobile device for automatically placing an MR coil in a medical imaging system according to claim 9, characterized in that, The internal array of the coil unit is arranged in a parallel relationship in the head-foot, front-back and left-right directions, and the coil unit can perform accelerated scanning simultaneously in any two directions during 3D imaging.

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