Imaging method, device and equipment of interventional instrument

Abstract

The invention provides an imaging method, device and equipment of an interventional instrument. The imaging method comprises the following steps: acquiring a movement track and a current position of the interventional instrument in an interventional environment; according to the motion trail and the current position, a local scanning visual field area of the imaging equipment is determined, and the local scanning visual field area at least comprises an expected advancing path of the interventional instrument; and imaging the interventional instrument according to the local scanning view area to obtain a local image of the interventional instrument. The radiation quantity in the imaging process of the interventional instrument is reduced, and the imaging accuracy is improved.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to an imaging method, apparatus and device for interventional instruments. Background Technology

[0002] With the miniaturization and intelligent development of interventional devices such as guidewires, and the expansion of indications for endovascular treatment, digital subtraction angiography (DSA) systems have become a core tool for surgical navigation.

[0003] During fluoroscopic imaging in DSA interventional surgery, X-ray machines can be used to acquire images of the guidewire, thereby determining its position within the blood vessel. During this image acquisition process, a large amount of surrounding human tissue is repeatedly irradiated with X-rays. For example, tissues such as brain tissue and limbs, which are not affected by respiration or heartbeat, primarily serve as references for the guidewire's relative position within the scanning field of view, but are subjected to unnecessary radiation during the procedure. Therefore, how to image the guidewire with lower radiation levels is a technical problem that this application aims to solve. Summary of the Invention

[0004] This application provides an imaging method, apparatus, and device for interventional devices to reduce radiation exposure and improve imaging accuracy during the imaging process.

[0005] In a first aspect, an imaging method for interventional devices is provided, comprising: acquiring the motion trajectory and current position of the interventional device in an interventional environment; determining a local scanning field of view of an imaging device based on the motion trajectory and current position, wherein the local scanning field of view includes at least the expected travel path of the interventional device; and imaging the interventional device based on the local scanning field of view to obtain a local image of the interventional device.

[0006] In a second aspect, an imaging device for interventional devices is provided, comprising: a data acquisition module for acquiring the motion trajectory and current position of the interventional device in an interventional environment; a field of view prediction module for determining a local scanning field of view area of ​​the imaging device based on the motion trajectory and current position, wherein the local scanning field of view area includes at least the expected travel path of the interventional device; and a device imaging module for imaging the interventional device based on the local scanning field of view area to obtain a local image of the interventional device.

[0007] Thirdly, an electronic device is provided, comprising: a processor and a memory for storing a computer program, the processor for calling and running the computer program stored in the memory, and performing the methods as described in the first aspect or its various implementations.

[0008] Fourthly, a computer-readable storage medium is provided for storing a computer program that causes a computer to perform the methods described in the first aspect or its various implementations.

[0009] Fifthly, a computer program product is provided, including computer program instructions that cause a computer to perform the methods as described in the first aspect or its various implementations.

[0010] Sixthly, a computer program is provided that causes a computer to perform the methods described in the first aspect or its various implementations.

[0011] The technical solution provided in this application allows an electronic device to acquire the motion trajectory and current position of an interventional device in the interventional environment. Then, based on the motion trajectory and current position, a local scanning field of view (FSV) of the imaging device can be determined, where the FSV includes at least the expected path of the interventional device. Finally, the interventional device can be imaged based on the FSV to obtain a local image of the interventional device. In this process, the electronic device determines the motion trend, i.e., the expected path, of the interventional device through its position and motion trajectory. It images only the minimum necessary area containing the expected path, i.e., the FSV, thus reducing the radiation irradiation range of the imaging device from a fixed, large FSV in related technologies (e.g., typically covering a large amount of non-interventional tissue) to a smaller FSV that dynamically changes with the movement of the interventional device. This reduces the ineffective radiation dose to non-interventional tissues in the interventional environment, such as brain tissue and limbs, while ensuring surgical navigation accuracy. This achieves precise and automated guidewire imaging under low-radiation conditions, reducing radiation exposure during interventional device imaging and improving imaging accuracy. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 An application scenario diagram provided for an embodiment of this application; Figure 2 A flowchart illustrating an imaging method for an interventional device provided in an embodiment of this application; Figure 3 A schematic diagram of an imaging method for an interventional device provided in an embodiment of this application; Figure 4AA schematic diagram of another imaging method for an interventional device provided in an embodiment of this application; Figure 4B A schematic diagram of another imaging method for an interventional device provided in an embodiment of this application; Figure 4C A schematic diagram of another imaging method for an interventional device provided in an embodiment of this application; Figure 4D A schematic diagram of another imaging method for an interventional device provided in an embodiment of this application; Figure 5 A schematic diagram of an imaging device for an interventional instrument provided in an embodiment of this application; Figure 6 This is a schematic block diagram of the electronic device provided in the embodiments of this application. Detailed Implementation

[0014] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0015] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0016] It should be understood that the technical solution of this application can be applied to the following scenarios, but is not limited to: In one embodiment, the technical solution of this application can be applied to the field of imaging and tracking of interventional devices. The interventional device can be a medical interventional device, such as a guidewire or catheter, but is not limited to these. Tracking the interventional device can include determining its movement trajectory and current position.

[0017] In one embodiment, Figure 1 An application scenario diagram provided for an embodiment of this application, such as... Figure 1As shown, this application scenario may include terminal device 110 and server 120. Terminal device 110 and server 120 establish a connection through a wired network or a wireless network.

[0018] For example, terminal device 110 may be a desktop computer, laptop computer, tablet computer, mobile phone, or imaging device with intelligent display function, etc. The imaging device may be a device for performing subtraction angiography, but is not limited thereto. Server 120 may be a server, server cluster, or cloud service, but is not limited thereto.

[0019] For example, server 120 can acquire the movement trajectory and current position of the interventional device in the interventional environment, and determine the local scanning field of view of the imaging device accordingly. The local scanning field of view includes at least the expected path of the interventional device. Then, it can control the imaging device to image the interventional device according to the local scanning field of view to obtain a local image of the interventional device. Finally, the local image can be sent to terminal device 110 for display. Alternatively, terminal device 110 is an imaging device with intelligent display function. Server 120 can send the local scanning field of view to terminal device 120, and terminal device 120 can image the interventional device according to the local scanning field of view to obtain and display a local image of the interventional device.

[0020] also, Figure 1 An example of a terminal device and a server is given, but in practice, other numbers of terminal devices and servers may be included, and this application does not limit this.

[0021] In another embodiment, the technical solution of this application may also be executed by an electronic device including the aforementioned terminal device 110 and server 120, which may further include an imaging device or establish a communication connection with the imaging device; or, the technical solution of this application may be executed by only the aforementioned terminal device 110 or server 120, and this application does not limit this.

[0022] For example, the technical solution of this application can be executed by an intelligent imaging device, which can acquire the motion trajectory and current position of the interventional device in the interventional environment, and determine the local scanning field of view of the imaging device accordingly. The local scanning field of view includes at least the expected travel path of the interventional device. Then, the interventional device can be imaged according to the local scanning field of view to obtain and display a local image of the interventional device.

[0023] After introducing the application scenarios of the embodiments of this application, the technical solution of this application will be described in detail below: Figure 2 A flowchart illustrating an imaging method for an interventional device provided in this application embodiment is shown below. Figure 2 As shown, the method may include steps S210-S230: S210: Obtain the movement trajectory and current position of the interventional device in the interventional environment.

[0024] Specifically, the interventional device can be a medical interventional device, such as a guidewire or catheter, but is not limited to these. Furthermore, there can be one or more of the aforementioned interventional devices, and this application does not impose any limitations on this. The following sections will describe embodiments using a guidewire as an example.

[0025] The intervention environment can be blood vessels, bones, but is not limited to these.

[0026] Specifically, the movement trajectory of the interventional device in the interventional environment includes at least one of the following: the historical movement trajectory of the interventional device, and the preset movement trajectory of the interventional device in the interventional environment. The movement trajectory can specifically be the movement trajectory of the moving tip of the interventional device.

[0027] The historical trajectory can be a path formed by all the actual locations the interventional device has traveled in the interventional environment from the start of the surgery to the current moment. For example, the position of the interventional device in the interventional environment at each historical moment can be obtained using a method similar to obtaining the current position in S210, and the historical trajectory can be determined based on the position at each historical moment. Alternatively, the historical trajectory can also be determined using local images in S230 at historical moments or global images in subsequent embodiments.

[0028] The preset motion trajectory can be a path set for the interventional device before or during surgery, and can be at least one of the following: a preset motion trajectory before the current moment, or a preset motion trajectory after the current moment.

[0029] Specifically, S210 includes the following steps: acquiring the current frame imaging image and previous multiple frame imaging images of the intervention environment; determining the current position based on the image difference between the current frame imaging image and at least one adjacent frame imaging image; and determining the motion trajectory based on the image difference between the current frame imaging image and previous multiple frame imaging images.

[0030] Among them, at least one of the current frame imaging image and the imaging image adjacent to the current frame imaging image includes an interventional device; at least one of the current frame imaging image and the previous multiple frames imaging image includes an interventional device.

[0031] For example, the at least one imaging image adjacent to the current frame imaging image can be the previous frame or multiple frames imaging images, but is not limited thereto.

[0032] For example, multiple difference pixel regions can be determined first based on the differences between each pair of adjacent imaging images in the current frame and the previous multiple frames. These difference pixel regions are the pixel regions where the interventional device is located in the corresponding imaging image. Then, the motion trajectory is determined based on these multiple difference pixel regions. For example, the motion trajectory can be obtained by connecting the multiple difference pixel regions.

[0033] For example, the imaging device can be configured to acquire the current frame image and the previous frame image using a first ray parameter (the corresponding imaging area corresponds to the global scanning field of view of the imaging device, which can be the largest scanning field of view of the imaging device). In the subsequent imaging process of S230, the interventional device can be imaged using a second ray parameter (the corresponding imaging area corresponds to the local scanning field of view determined in S220, i.e., a local scanning field of view), obtaining a local image. The radiation dose corresponding to the first ray parameter is lower than the radiation dose corresponding to the second ray parameter. In this way, guidewire tracking with a lower radiation dose can be achieved.

[0034] For example, the beam parameters may include, but are not limited to, at least one of the following: the position, thickness, type, tube current, and tube voltage of the filter element in the beaming device. Subsequent embodiments describe the beaming device and the filter element.

[0035] For example, the acquisition of the current frame image and the previous multiple frames of images, and the imaging in S230 can be performed separately by multiple imaging devices. Alternatively, the acquisition of the current frame image and the previous multiple frames of images, and the imaging in S230 can be performed separately by different imaging devices of the same imaging device.

[0036] The imaging equipment can be an imaging device used for interventional surgery. For example, the imaging equipment can be a DSA system containing at least one imaging device: a C-arm X-ray machine. The imaging equipment can be a single-plane device (e.g., a DSA system containing a C-arm X-ray image overlay machine) or a dual-plane imaging device containing two single-plane devices (e.g., a DSA system containing a two-arm X-ray machine). This application does not impose any limitations on this.

[0037] For example, the current position can be determined based on the pixel differences between the current frame image and adjacent images. For instance, pixel values ​​can be subtracted. The pixel value is the numerical representation of the pixel, describing its color and brightness information. For example, if the image is grayscale, the pixel value ranges from 0 to 255. If the image is color, the pixel value can be the channel value of the red, green, and blue channels, each ranging from 0 to 255. This application does not limit the format of the image or the specific content of the pixel values.

[0038] It is understandable that the movement of interventional devices has the characteristics of spatiotemporal continuity (e.g., the position of the same guidewire changes smoothly without sudden jumps) and feature stability (e.g., the morphology, grayscale distribution, and other features of the same guidewire are relatively consistent), while the interventional environment (e.g., blood vessels, bones) is static. Therefore, after calculating the differences between the images, the pixel value of the corresponding pixel in the interventional environment is equal to or close to zero. The moving interventional device will produce a relatively obvious difference in pixel value between its two positions before and after the movement. Therefore, the current position of the interventional device can be determined.

[0039] Specifically, the current position and trajectory of the interventional device are identified based on the gradient of pixels in the differential pixel region.

[0040] The gradient of a pixel can characterize the maximum rate of change of the pixel value in space and its direction of change. The gradient of a pixel can include gradient direction and gradient magnitude. Taking a guidewire as an example, the gradient magnitude of pixels at the edge of the guidewire is generally higher than that of pixels in other tissues; for a straight guidewire, the gradient directions of its two edges are approximately opposite, both pointing perpendicular to the guidewire axis; for a curved guidewire, its gradient direction changes smoothly with the guidewire contour.

[0041] Understandably, in the spatial dimension, interventional devices, such as guidewires, generally appear as high-contrast, slender structures in imaging images (specifically, regions of difference in pixels). Therefore, their edges exhibit significant changes in pixel values, resulting in a characteristic response with significant gradient amplitude and orderly gradient direction distribution. In the temporal dimension, the movement of interventional devices is smooth, and the materials of the devices are stable. Therefore, in imaging images (specifically, regions of difference in pixels) across consecutive frames, the gradient characteristics (including corresponding gradient amplitude and gradient direction features) of the same interventional device have high temporal correlation. They do not undergo abrupt changes due to small displacements between frames. This is different from the gradient abrupt changes caused by background artifacts and contrast agent flow. Therefore, by calculating the gradient of pixels in a pixel region, interventional devices in the pixel region can be identified relatively accurately.

[0042] Furthermore, identifying interventional devices in the difference pixel region can reduce the computational load of interventional device identification and improve the efficiency of interventional device identification.

[0043] For example, before calculating the gradient of pixels in a pixel region, the difference pixel region can be preprocessed to suppress image noise, enhance the signal-to-noise ratio, and avoid gradient direction disorder and false edges caused by noise, thereby ensuring the stability and accuracy of subsequent gradient calculation.

[0044] For example, the image quality of the differing pixel regions can be used to preprocess them. Specifically, the image quality can be evaluated first to determine the noise level and contrast of the differing pixel regions. If the noise is high, the differing pixel regions can be filtered; if the contrast is low, a portion of the differing pixel regions (e.g., the approximate area involved by the interventional device) can be enhanced for contrast.

[0045] For example, Gaussian blur algorithms can be used to suppress noise in regions of difference in pixels.

[0046] For example, the gradient of the interventional device can be approximated by the projection or partial derivative of the gradient in the horizontal (x-axis) and vertical (y-axis) directions using gradient operators such as the Sobel operator. Then, the gradient magnitude and gradient direction can be calculated based on Gx and Gy.

[0047] For example, identifying the current position and trajectory of an interventional device based on the gradient of a pixel can be achieved in any of the following ways, but is not limited to: Method 1: For any frame of imaging image corresponding to the target difference pixel region, determine the neighboring pixels in the neighboring regions of each target pixel in the target difference pixel region; determine the neighborhood gradient direction according to the gradient direction of the neighboring pixels; calculate the directional difference between the neighborhood gradient direction and the gradient direction of the target pixel; determine the target pixels whose corresponding directional difference is less than the directional difference threshold as candidate pixels; identify the current position of the interventional device based on the candidate pixels.

[0048] Candidate pixels refer to the pixels corresponding to the edge points of interventional instruments that satisfy the gradient direction continuity.

[0049] For example, the adjacent region can be a local region centered on the target pixel in the target difference pixel region. The number of adjacent pixels in the adjacent region can be 2, 4, or 8. For example, the adjacent pixels can be 8 pixels adjacent to the target pixel. This application does not limit this.

[0050] For example, the neighborhood gradient direction can be the vector sum of the gradient directions of adjacent pixels, that is, the average direction of the gradient directions of adjacent pixels. Alternatively, the direction corresponding to the peak value in the histogram of the gradient directions of adjacent pixels can be used as the neighborhood gradient direction; this application does not impose any restrictions on this.

[0051] For example, the directional difference between the gradient direction of the neighborhood pixel and the gradient direction of the target pixel refers to the angular difference between the two gradient directions. The directional difference threshold can be a preset angular difference threshold, such as 10°.

[0052] For example, morphological closing operations can be performed on candidate pixels to obtain interventional devices. Specifically, morphological dilation can be performed on candidate pixels first to connect closely spaced pixels and bridge gaps between them; then morphological erosion can be performed on the candidate pixels to restore the complete contour of the interventional device and eliminate isolated noise points. Next, connected component analysis can be performed on the processed image to extract all candidate contours; based on the geometric features of the interventional device (e.g., slender structure, curvature), the candidate contours are filtered, and those that meet the geometric features are identified as the interventional device.

[0053] In the above embodiments, the spatial consistency feature of interventional devices within a single frame image can be utilized, namely, the gradient direction of the interventional device edge is smoothly and continuously distributed along the contour tangent. By calculating the gradient direction difference between the target pixel and the pixels in its adjacent region, pixels with a direction difference less than a threshold can be selected to identify the interventional device, thereby achieving both accuracy and efficiency in identifying interventional devices.

[0054] Method 2: For any frame of imaging image corresponding to the target difference pixel region, determine the template gradient features of the pixels corresponding to the interventional device in the first historical difference pixel region. The first historical difference pixel region is the difference pixel region under any historical frame of imaging image corresponding to the target difference pixel region. Based on the gradient of the pixels in the target difference pixel region, determine the candidate gradient features of each candidate region in the target difference pixel region. Calculate the similarity between the candidate gradient features and the template gradient features. Based on the target candidate region with the highest similarity, obtain the interventional device, and determine the motion trajectory based on multiple target candidate regions.

[0055] For example, the first historical difference pixel region can be the difference pixel region in the previous frame of the imaging image corresponding to the target difference pixel region.

[0056] For example, template gradient features can be features determined based on the gradient magnitude and gradient direction of the corresponding pixel points of the interventional device in the first historical difference pixel region. For example, they can include gradient magnitude distribution features and gradient direction trend features, and can include at least one of the following: gradient direction histogram, gradient magnitude statistics such as the mean, variance, maximum value, median value, and minimum value of the gradient magnitude of the corresponding pixel points.

[0057] Candidate gradient features are similar to template gradient features, and will not be elaborated upon in this application.

[0058] For example, the similarity between candidate gradient features and template gradient features can be calculated using cosine similarity. Specifically, it can be calculated using the following formula (1): Formula (1) Where Ai and Bi are the i-th elements in the template gradient feature and the candidate gradient feature, respectively, and n is a positive integer.

[0059] Alternatively, interventional devices can be obtained from target candidate regions whose similarity is greater than a similarity threshold (e.g., 0.8; the similarity threshold can be determined or adjusted based on the image quality of the imaging image).

[0060] For example, the region corresponding to the center of the target candidate region or the region corresponding to the circumscribed rectangle can be identified as the interventional device.

[0061] In addition, the historical gradient features of the corresponding pixels of the interventional device in the second historical difference pixel region can be determined. The second historical difference pixel region is the difference pixel region under the imaging images of a preset number of historical frames corresponding to the target difference pixel region. The feature difference between the target candidate gradient features and the historical gradient features of the target candidate region can be calculated. In response to the feature difference being greater than the feature difference threshold, the interventional device is re-identified.

[0062] Historical gradient features are similar to template gradient features, and will not be elaborated upon in this application.

[0063] For example, the feature differences between the target candidate gradient features and historical gradient features can be determined by calculating the differences in gradient magnitude distribution and gradient direction similarity in the gradient features.

[0064] The feature difference threshold can be a pre-set threshold or can include multiple thresholds, such as a difference threshold for gradient magnitude distribution, like 30%, or a similarity difference threshold for gradient direction, but is not limited to these.

[0065] If the feature difference is greater than the feature difference threshold, it can be determined that the target candidate region belongs to the incorrect determination result caused by gradient mutation, for example, it may be caused by trajectory deviation or mismatch due to artifact occlusion.

[0066] For example, the aforementioned re-identification of interventional devices could involve modifying or redefining the target candidate region, and then obtaining the interventional device based on the modified or redefined target candidate region. For instance, the target candidate region could be redefined according to method one (in this case, the target candidate region is the region corresponding to the candidate pixel).

[0067] Specifically, the current position of the interventional device can be determined by performing image processing (e.g., recognition, feature point matching, etc.) on the current frame imaging image and / or imaging images adjacent to the current frame imaging image through at least one of the preset machine learning model, feature matching, and template matching.

[0068] Specifically, the local image in S230 corresponding to the historical moment can also be obtained, namely the historical local image. Based on the historical local image, the current position of the interventional device can be determined according to any method in the above embodiments (e.g., image difference between two adjacent frames, machine learning model, feature matching, and template matching).

[0069] Specifically, the aforementioned current position can be the two-dimensional or three-dimensional spatial coordinates corresponding to the interventional device in the current frame imaging image, the imaging image adjacent to the current frame imaging image, or a historical local image.

[0070] The coordinate system corresponding to the current frame image, the adjacent image, or the historical local image can be a two-dimensional coordinate system. The origin of the coordinate system can be a vertex of the image, such as the upper left or lower left corner. The units for the horizontal and vertical coordinates can be pixels in the image. One pixel corresponds to one coordinate point, and one coordinate point represents the row and column of the corresponding pixel in the image.

[0071] Two-dimensional coordinates in the two-dimensional coordinate system can be transformed into three-dimensional coordinates in the three-dimensional coordinate system using methods such as linear transformation (translation, rotation, scaling, affine transformation, etc. between corresponding points in the two-dimensional and three-dimensional coordinate systems), nonlinear transformation, device-space transformation, and feature matching transformation. This three-dimensional coordinate system can be a device-space coordinate system with the imaging device as a reference. The origin of the device-space coordinate system can be the center point of the C-arm (i.e., the mechanical center point around which the C-arm rotates, and the position of this mechanical center point in space is fixed), but it is not limited to this. The X, Y, and Z axes of the device-space coordinate system can correspond to the front-back, left-right, and up-down directions of the imaging device.

[0072] Correspondingly, the trajectory of the aforementioned interventional device in the interventional environment can also be the curve equation or coordinate set corresponding to the two-dimensional coordinates or three-dimensional spatial coordinates of the current position in the coordinate system.

[0073] In the above embodiments, the movement trajectory and current position of the interventional device in the interventional environment can be determined in a relatively accurate, rapid and low-radiation manner, providing reliable data for determining the radiation irradiation range, i.e., the local scanning field of view area, in subsequent embodiments.

[0074] S220: Based on the motion trajectory and current position, determine the local scanning field of view of the imaging device, which includes at least the expected travel path of the interventional device.

[0075] The local scanning field of view can refer to the area where the imaging object (e.g., a patient) is exposed to actual imaging rays (e.g., X-rays, but not limited to these). The area corresponding to the local scanning field of view can be smaller than the area corresponding to the global scanning field of view of the imaging device.

[0076] Specifically, the local scanning field of view may include the moving tip of the interventional device and the interventional environment of the moving tip. The shape of the local scanning field of view may be regular or irregular; for example, it may be a rectangular or circular field of view along the direction of travel of the interventional device. This application does not impose any limitations on this.

[0077] Specifically, the expected path of the interventional device can be predicted based on the movement trajectory and current position, and then the local scanning field of view can be determined based on the expected path of the interventional device.

[0078] For example, deep learning can be used to predict the expected path of an interventional device based on its motion trajectory and current position. For instance, the positional and temporal differences between adjacent points in the motion trajectory can be calculated using a finite difference method to obtain the device's velocity and acceleration. This velocity, acceleration, and current position are then input into a pre-trained deep learning model to obtain the device's positional distribution over a future time period, i.e., its expected path. The deep learning model can be a Transformer or a temporal convolutional network, but is not limited to these.

[0079] For example, a geometric region can be generated centered on each location point in the expected travel path, and the area formed by each geometric region can be defined as the local scanning field of view. For instance, the local scanning field of view can be obtained by performing a region union on all geometric regions. Alternatively, any preset specific geometric region can be defined as the local scanning field of view, and the specific geometric region can cover each location point in the expected travel path.

[0080] The orientation of the local scanning field of view can be consistent with the path direction of the expected travel path.

[0081] Specifically, field of view determination parameters can also be obtained, which include at least one of the following: morphological features of the intervention environment, preset scanning field of view range, and preset scanning field of view expansion parameters; based on the field of view determination parameters, motion trajectory, and current position, the local scanning field of view area is determined.

[0082] For example, the morphological features of the intervention environment can be features corresponding to the two-dimensional or three-dimensional geometry of the intervention environment. For example, they can be determined based on at least one of the following, but not limited to: the path, curvature, position and angle of the bifurcation or confluence points of the geometric centerline of the intervention environment, and the inner diameter of the cross section perpendicular to the geometric centerline.

[0083] The preset scanning field of view can be the maximum scanning field of view supported by the imaging device. For example, it can be the global scanning field of view of the imaging device, or it can be a set maximum scanning field of view.

[0084] Preset scanning field of view (SFR) parameters refer to parameters that adjust the expected travel path (e.g., selecting the corresponding geometric region, adding or removing position points along the expected travel path) or parameters that adjust the determined initial local scanning field of view. For example, the SFR parameter can be a time value parameter, used to limit the length of future time corresponding to the expected travel path; it can be a distance or quantity parameter, used to display the path distance or number of position points corresponding to the expected travel path; or it can be a field of view size parameter (e.g., the final local scanning field of view width is 5 mm, the final local scanning field of view length is 10 mm; the width expansion ratio is 10%, the length expansion ratio is 10%), used to expand / reduce the size of the initial local scanning field of view. This ensures that the interventional instrument tip is not lost due to an excessively small field of view, while avoiding dose waste caused by blindly expanding the field of view.

[0085] For example, this process is similar to the embodiments described above. For instance, field-of-view determination parameters can be input into the deep learning model, enabling the model to determine the expected path of travel based on these parameters. Specifically, morphological features of the interventional environment can be input into the input layer or intermediate feature layer of the deep learning model, allowing the model to consider these features when predicting the expected path of travel, thereby outputting an expected path that better reflects the actual surgical situation. Scanning field-of-view expansion parameters and a preset scanning field-of-view range are input as conditional vectors into the input layer or intermediate feature layer, instructing the model to generate an expected path that meets the corresponding conditions.

[0086] Alternatively, parameters can be determined based on the field of view to adjust the initial local scanning field of view area, which is determined based on the motion trajectory and the current position, to obtain the final local scanning field of view area. Specifically, the initial local scanning field of view area can be adjusted first using scanning field of view expansion parameters and a preset scanning field of view range. Then, the adjusted initial local scanning field of view area can be cropped based on the morphological characteristics of the intervention environment to obtain the final local scanning field of view area. For example, the adjusted initial local scanning field of view area can be cropped based on the cross-section of the intervention environment at the location corresponding to the expected path of travel in the morphological features, ensuring that the final local scanning field of view area is confined within the cross-section.

[0087] It should be noted that determining the local scanning field of view of the imaging device as described above includes at least one of the following: determining the orientation, size, and shape of the local scanning field of view.

[0088] In the above embodiments, the X-ray irradiation range, i.e., the local scanning field of view, during the S230 imaging process can be automatically determined based on the motion trajectory and current position, thereby reducing the technical defects of inaccuracy and untimely determination of the local scanning field of view. Moreover, the determined local scanning field of view is restricted to the corresponding constraints of the intervention environment and imaging equipment by the field of view determination parameters, ensuring that the imaging result, i.e., the local image, can fit the intervention environment and that the local scanning field of view does not exceed the range supported by the imaging equipment, and also reserving a buffer space for prediction errors.

[0089] For example, a three-dimensional anatomical model corresponding to the interventional environment can be obtained; the current position of the imaging device can be mapped into the three-dimensional anatomical model to determine the anatomical structure at the current position and the local extension direction of the structure; based on the local extension direction, the orientation of the central axis of the local scanning field of view can be adjusted, and the shape and size parameters of the local scanning field of view can be adapted to the cross-sectional shape and size of the anatomical structure.

[0090] S230: Imaging the interventional device based on the local scanning field of view to obtain a local image of the interventional device. The imaging area corresponding to the local image is consistent with the local scanning field of view.

[0091] Specifically, S230 can be achieved through the following steps: Adjusting the beamforming device of the imaging equipment according to the scanning field of view, the beamforming device is used to control the distribution of the corresponding imaging rays (e.g., the energy distribution of the imaging rays, the position, shape, and size distribution of the radiation area corresponding to the imaging rays); imaging the interventional instrument based on the adjusted beamforming device to obtain a local image. Specifically, the radiation area corresponding to the rays transmitted by the adjusted beamforming device can be made consistent with the local scanning field of view.

[0092] For example, the beam-beaming device includes a filter element for filtering the corresponding imaging rays; the beam-beaming device for adjusting the imaging device described above may include adjusting at least one of the following: the position, thickness, and type (e.g., one material corresponds to one type) of the filter element.

[0093] For example, the beam-beaming device can be a beam beamer (e.g., a rectangular beam beamer, a circular variable aperture beam beamer), and the filter element can be a filter or a grid of filters in the beam beamer, but is not limited thereto. The beam-beaming device may include at least one filter element, and the position, thickness, and type of each of the at least one filter element are different. The filter element can be a lead plate, or its material can be aluminum, copper, or an alloy, but is not limited thereto. The filter element can be a wedge-shaped filter, for example, thin at one end and thick at the other end, or with a gradual change in thickness from one side to the other. This application does not limit the material, type, thickness, number, etc. of the beam-beaming device and the filter element.

[0094] In the above embodiments, the beamforming device, specifically the filter element of the beamforming device, can be adjusted according to the local scanning field of view to perform local imaging of the interventional instrument and a small amount of surrounding tissue according to the local scanning field of view. Because the radiation flux received per unit area by the detector (FPD) of the imaging device is more concentrated in a smaller local scanning field of view, a lower radiation dose (mAs) can be used to complete imaging while achieving the same signal-to-noise ratio (SNR). Alternatively, at the same radiation dose, a clearer image with less noise can be obtained compared to a larger scanning field of view. Moreover, since most detector manufacturers perform more precise calibration on the central area of ​​the detector, the resolution of the central area is usually higher and the geometric distortion is smaller than that of the surrounding area. Therefore, while ensuring the accuracy of surgical navigation, it is possible to reduce the ineffective radiation dose to non-interventional tissues in the interventional environment, such as brain tissue and limbs, achieving precise and automated imaging of the interventional instrument under low-radiation conditions. This reduces the radiation dose during the interventional instrument imaging process and improves imaging accuracy.

[0095] In one embodiment, to address the operator's insufficient spatial perception caused by the limited field of view (FOV) of local images, a global image of the interventional device can be acquired. The global image and the local image are then fused to obtain a fused global image of the interventional device. The global image includes the interventional environment corresponding to the current location, the scanning field of view corresponding to the local image is smaller than that corresponding to the global image, and the local and global images overlap.

[0096] Specifically, a feature point matching algorithm can be used to fuse global and local images to obtain a globally fused image. For example, feature point matching can be performed on feature points of interventional devices or vascular branches in local and global images, aligning and fusing the global and local images to obtain a globally fused image of the interventional device. For instance, the global view of the interventional device can include the real-time position of the guidewire tip and a large area of ​​blood vessels and surrounding tissues.

[0097] This method allows for the fusion of global and local images based on pixel-level weight allocation. Since local images have a narrower scanning field of view and higher resolution, a higher fusion weight can be assigned to the local images in overlapping areas, while only the global image can be retained in non-overlapping areas.

[0098] In one embodiment, the method may further include the following steps: detecting that the interventional device has moved to a preset boundary range or that a local scanning field of view has reached a preset boundary range, and imaging the interventional environment according to the global scanning field of view of the imaging device (for example, the current scanning field of view can be adjusted to the global scanning field of view) to obtain a global image of the subsequent interventional device. For example, the interventional environment can be imaged based on the aforementioned first ray parameters to obtain a global image. The preset boundary range may be a preset boundary range of the global scanning field of view, or a preset boundary range of the previous global / local or previous global image; this application does not impose any limitations on this.

[0099] Alternatively, the global image could be acquired before surgery, or it could be the current frame image or the previous frame image in S210, or it could be the previous global fusion image or the previous global image. This application does not limit the scope of the image.

[0100] Specifically, the imaging quality of a local image is greater than that of the global image. This enables high-resolution imaging of a local area of ​​interest with a relatively low radiation dose.

[0101] For example, at least one of the resolution, frame rate, pulse width, and radiation dose of a local image can be set to be greater than at least one of the resolution, frame rate, pulse width, and radiation dose of the global image.

[0102] For example, the resolution of local and global images can be adjusted by switching the exposure focus, such as using a 200µm focus to capture the global image and a 100µm focus to capture the local image.

[0103] In one embodiment, a local field of view identifier can be used to identify a local scanning field of view region and / or a global field of view identifier can be used to identify a global scanning field of view region.

[0104] The field of view marker (e.g., a local field of view marker or a global field of view marker) can be a geometric pattern with the same shape and size as the corresponding scanned field of view area (e.g., a local scanned field of view area or a global scanned field of view area). For example, the field of view marker can be a dashed frame, specifically a circular or square dashed frame. This application does not limit the size, shape, color, etc. of the field of view marker.

[0105] For example, field of view identifiers can be displayed in local images, global images, or globally fused images at any given time.

[0106] For example, such as Figure 3 As shown, assuming the interventional environment contains one guidewire, imaging images at times 1, 2, ..., n (at least one of the n imaging images contains the guidewire) can be acquired by the image acquisition unit of the electronic device, where n is a positive integer. Then, the image fusion unit of the electronic device fuses each local image with its corresponding global image to obtain the following result: Figure 3 The diagram shows multiple globally fused images: Global Fusion Image 1, Global Fusion Image 2, ..., Global Fusion Image n. Each globally fused image may include dashed and solid bounding boxes. Dashed boxes are used to identify historical local scan fields of view in historical local images, while solid boxes are used to identify local scan fields of view in the current local image.

[0107] For example, such as Figures 4A-4D As shown, the electronic device can display at least one of local images, global images, and globally fused images through a visualization interface. In addition, relevant information such as patient information, examination information, scanning protocol information, and device status information can be displayed on the far left of the visualization interface.

[0108] For example, such as Figure 4A As shown, the global fused image can be displayed in the middle of the visualization interface, while the dynamic programming FOV, i.e., the local image, is displayed on the far right. The local image here can be the current local image.

[0109] Specifically, a local field of view identifier corresponding to the local scanning field of view can be displayed at the corresponding position in the global image and / or the global fused image; the global image includes the intervention environment corresponding to the current position, the scanning field of view corresponding to the local image is smaller than the scanning field of view corresponding to the global image, and the local image and the global image overlap; the global fused image is the image after fusing the local image and the global image.

[0110] like Figure 4BAs shown, when a local scanning field of view (or the position reached by the interventional device) reaches or approaches the edge of the global field of view, the local scanning field of view can be adjusted to the global field of view and imaged to obtain a global image. This global image can be fused with subsequent local images to obtain a global fused image. Furthermore, the local FOV (corresponding to the local scanning field of view in the local image) and the global FOV (corresponding to the global scanning field of view in the global image) can be identified using boxes of different sizes, colors, or shapes, i.e., field of view markers. Alternatively, the box corresponding to the local FOV can be switched to the box corresponding to the global FOV.

[0111] That is, when the interventional device is detected to have moved to a preset boundary range or the local scanning field of view has reached a preset boundary range, the corresponding global field of view marker for subsequent global imaging scans is displayed in the global image and / or the global fused image.

[0112] like Figure 4C As shown, the last acquired global image can be directly displayed in the middle of the visualization interface, without showing the fused global image in the middle. The right side of the visualization interface can display real-time local images, or it can display the current global image or the fused global image.

[0113] Alternatively, the global image (referring to the current global image) can be stitched together with the subsequent global images corresponding to subsequent global imaging scans, or the global fused image can be stitched together with subsequent global images to obtain a global navigation image. This global navigation image can then be displayed, specifically on the far right of the visualization interface, such as... Figure 4C As shown in the rightmost image. Similarly, local view markers can be displayed on the global navigation image.

[0114] like Figure 4D As shown, the visualization interface can display both lower-resolution global fused images and higher-resolution local images. The lower right side of the visualization interface displays a real-time local image of the interventional device within the local image.

[0115] In the above embodiments, by fusing global and local images, a complete and coherent global fused image can be provided, which can solve the problem of insufficient spatial perception or spatial disorientation of the surgeon caused by small field of view imaging, and ensure the spatial perception and smooth operation of the surgery.

[0116] In other words, a global image with view identifiers, a global fused image, and a global navigation image can be defined as a dynamic navigation image. The view identifiers on a dynamic navigation image change with the position of the local view. The dynamic navigation image and the global image or global fused image without view identifiers can appear to be in different areas, for example, displayed in split-screen mode, or displayed in different areas within the same screen.

[0117] In one embodiment, image overlap of interventional devices in a local image can also be detected, and the imaging adjustment angle and the device motion information corresponding to the imaging adjustment angle can be calculated. Based on the device motion information, the imaging device can be controlled to move (for example, a control command can be generated based on the device motion information, and the imaging device can be controlled to move through the control command), so that the imaging angle of the imaging device is the imaging adjustment angle, so as to acquire a local image of the interventional device under the imaging adjustment angle; wherein, there is no image overlap of interventional devices in the local image corresponding to the imaging adjustment angle.

[0118] The aforementioned image overlap can be caused by the curling of a single interventional device, or by the movement of an interventional device to a tortuous part of the blood vessel path at the current angle, or by the image overlap of multiple interventional devices under the same imaging view.

[0119] For example, one could analyze connected regions, identify whether an “X” shape exists in the image, or detect whether there is overlap using three-dimensional spatial coordinates, but is not limited to these methods.

[0120] For example, the interventional environment and interventional device can be reconstructed in three dimensions based on the multi-frame imaging images in S210 above, the three-dimensional spatial coordinates of the interventional environment and interventional device can be determined, the imaging angle for the interventional device under the condition of no image overlap can be calculated based on the three-dimensional spatial coordinates, the imaging angle can be determined as the imaging adjustment angle, and the device motion information can be determined based on the imaging adjustment angle and the current angle for the interventional device.

[0121] For example, the movement of the imaging device can be controlled by adjusting the rotation angle of the C-arm, adjusting the displacement of the detector, etc.

[0122] In addition, the device's operating information can be displayed, for example, through the display unit of the imaging device. It can also prompt the available imaging adjustment angles. Then, in response to the user's confirmation of adopting the above imaging adjustment angle, the frame and image chain of the imaging device can be controlled to automatically move to the position corresponding to the imaging adjustment angle, thereby enabling the user to quickly switch angles for acquisition and avoid the overlap of interventional instruments in the imaging image.

[0123] In one embodiment, a hardware identifier can be attached to the interventional device to enable physical hardware tracking, which can reduce the dependence on image resolution and achieve more stable imaging field linkage and interventional device tracking.

[0124] Specifically, a physical marker that can be detected by X-rays or external sensors can be added to the tip or other parts of the interventional device. For example, the physical marker can be a high-density metal element that can appear as a high-contrast bright spot under X-rays.

[0125] The technical solution of this application enables a fully automated process of tracking interventional instruments, determining the scanning field of view, local imaging, and image fusion of local and global images, thereby reducing radiation dose and improving the efficiency and accuracy of surgical procedures as well as the precision of imaging navigation.

[0126] It should be noted that all technical solutions in this application can be combined in any way to form optional embodiments of this application. To avoid repetition, these will not be elaborated upon.

[0127] Figure 5 This application provides a schematic diagram of an imaging device for an interventional instrument. (See attached diagram.) Figure 5 As shown, the device 500 includes: a data acquisition module 510 for acquiring the motion trajectory and current position of the interventional device in the interventional environment; a field of view prediction module 520 for determining the local scanning field of view area of ​​the imaging device based on the motion trajectory and current position, wherein the local scanning field of view area includes at least the expected travel path of the interventional device; and a device imaging module 530 for imaging the interventional device based on the local scanning field of view area to obtain a local image of the interventional device.

[0128] For example, the instrument imaging module 530 is specifically used to: adjust the beam beam device of the imaging device according to the scanning field of view, the beam beam device being used to control the distribution of the corresponding imaging rays; and image the interventional instrument according to the adjusted beam beam device to obtain a local image.

[0129] For example, the beam-beaming device includes a filter element for filtering the corresponding imaging rays; the instrument imaging module 530 is specifically used to: adjust at least one of the position, thickness, and type of the filter element.

[0130] For example, the data acquisition module 510 is specifically used to: acquire the current frame imaging image and the previous multiple frame imaging images of the intervention environment; determine the current position based on the image difference between the current frame imaging image and at least one adjacent frame imaging image; and determine the motion trajectory based on the image difference between the current frame imaging image and the previous multiple frame imaging images.

[0131] For example, the field of view prediction module 520 is specifically used to obtain field of view determination parameters, which include at least one of the following: morphological features of the intervention environment, a preset scanning field of view range, and a preset scanning field of view extension parameter; and to determine the scanning field of view area based on the field of view determination parameters, the motion trajectory, and the current position.

[0132] For example, the global determination module 540 is used to: acquire a global image of the interventional device, the global image including the interventional environment corresponding to the current position, the scanning field of view corresponding to the local image being smaller than the scanning field of view corresponding to the global image, and the local image and the global image overlapping; and perform image fusion of the global image and the local image to obtain a global fused image of the interventional device.

[0133] For example, the global determination module 540 is specifically used to: detect when the interventional device moves to a preset boundary range or the scanning field of view reaches a preset boundary range, and image the interventional environment according to the global scanning field of view of the imaging device to obtain a global image of the interventional device.

[0134] For example, the global determination module 540 is specifically used to: fuse the global image and the local image through a feature point matching algorithm to obtain a global view.

[0135] For example, the imaging quality of a local image is greater than that of the global image.

[0136] For example, the interface display module 550 is used to: display a local field of view identifier corresponding to the local scanning field of view at a corresponding position in the global image and / or the global fused image; wherein, the global image includes the intervention environment corresponding to the current position, the scanning field of view corresponding to the local image is smaller than the scanning field of view corresponding to the global image, and the local image and the global image overlap, and the global fused image is the image after the local image and the global image are fused.

[0137] For example, the interface display module 550 is specifically used to: detect when the interventional device moves to a preset boundary range or the local scanning field of view reaches a preset boundary range, and display the global field of view identifier corresponding to the subsequent global imaging scan in the global image and / or global fusion image.

[0138] For example, the interface display module 550 is specifically used to: stitch together the global image and the subsequent global image corresponding to the subsequent global imaging scan, or to stitch together the global fused image and the subsequent global image to obtain a global navigation image; and to display local field of view markers on the global navigation image.

[0139] For example, the device control module 560 is used to: detect image overlap of interventional devices in a local image, calculate the imaging adjustment angle and the device motion information corresponding to the imaging adjustment angle; control the imaging device to move according to the device motion information, so that the imaging angle of the imaging device is the imaging adjustment angle, so as to acquire a local image of the interventional device under the imaging adjustment angle; wherein, there is no image overlap of interventional devices in the local image corresponding to the imaging adjustment angle.

[0140] It should be understood that the device embodiments and method embodiments can correspond to each other, and similar descriptions can be referred to the method embodiments. To avoid repetition, further details will not be provided here. Specifically, Figure 5 The apparatus 500 shown can execute the above method embodiments, and the foregoing and other operations and / or functions of each module in the apparatus 500 are respectively for implementing the corresponding processes in the above method. For the sake of brevity, they will not be described in detail here.

[0141] The apparatus 500 of this application embodiment has been described above from the perspective of functional modules in conjunction with the accompanying drawings. It should be understood that this functional module can be implemented in hardware, in software instructions, or in a combination of hardware and software modules. Specifically, the steps of the method embodiments in this application can be completed by integrated logic circuits in the processor's hardware and / or by software instructions. The steps of the method disclosed in this application embodiment can be directly embodied as being executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. Optionally, the software module can reside in a mature storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps in the above method embodiments.

[0142] Figure 6 This is a schematic block diagram of the electronic device provided in an embodiment of this application. Figure 6 As shown, the electronic device 600 may include: The system includes a memory 610 and a processor 620. The memory 610 stores computer programs and transfers the program code to the processor 620. In other words, the processor 620 can retrieve and run the computer programs from the memory 610 to implement the methods described in the embodiments of this application.

[0143] For example, the processor 620 can be used to execute the above-described method embodiments according to instructions in the computer program.

[0144] In some embodiments of this application, the processor 620 may include, but is not limited to: General-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0145] In some embodiments of this application, the memory 610 includes, but is not limited to: Volatile memory and / or non-volatile memory. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), and Direct Rambus RAM (DR RAM).

[0146] In some embodiments of this application, the computer program may be divided into one or more modules, which are stored in the memory 610 and executed by the processor 620 to perform the method provided in this application. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the electronic device.

[0147] like Figure 6 As shown, the electronic device may also include: Transceiver 630, which can be connected to processor 620 or memory 610.

[0148] The processor 620 can control the transceiver 630 to communicate with other devices; specifically, it can send information or data to other devices or receive information or data sent by other devices. The transceiver 630 may include a transmitter and a receiver. The transceiver 630 may further include antennas, and the number of antennas may be one or more.

[0149] It should be understood that the various components in the electronic device are connected through a bus system, which includes a data bus, a power bus, a control bus, and a status signal bus.

[0150] This application also provides a computer storage medium storing a computer program thereon, which, when executed by a computer, enables the computer to perform the methods of the above-described method embodiments. Alternatively, embodiments of this application also provide a computer program product containing instructions that, when executed by a computer, cause the computer to perform the methods of the above-described method embodiments.

[0151] When implemented using software, it can be implemented entirely or partially as a computer program product. This computer program product includes one or more computer instructions. When these computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., digital video disc (DVD)), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0152] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0153] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0154] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. For example, the functional modules in the various embodiments of this application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0155] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An imaging method for an interventional device, characterized in that, include: Acquire the movement trajectory and current position of interventional instruments in the interventional environment; Based on the motion trajectory and the current position, a local scanning field of view of the imaging device is determined, wherein the local scanning field of view includes at least the expected travel path of the interventional device; The interventional device is imaged based on the local scanning field of view to obtain a local image of the interventional device.

2. The method according to claim 1, characterized in that, The acquisition of the movement trajectory and current position of the interventional device in the interventional environment includes: Acquire the current frame imaging image and previous multiple frame imaging images of the intervention environment; The current position is determined based on the image difference between the current frame image and at least one adjacent frame image. The motion trajectory is determined based on the image differences between the current frame and the previous multiple frames.

3. The method according to claim 1, characterized in that, Determining the local scanning field of view of the imaging device based on the motion trajectory and the current position includes: Obtain field of view determination parameters, which include at least one of the following: morphological features of the intervention environment, preset scanning field of view range, and preset scanning field of view expansion parameters; The local scanning field of view is determined based on the field of view parameters, the motion trajectory, and the current position.

4. The method according to any one of claims 1-3, characterized in that, The method further includes: A global image of the interventional device is acquired. The global image includes the interventional environment corresponding to the current position. The scanning field of view corresponding to the local image is smaller than the scanning field of view corresponding to the global image, and the local image overlaps with the global image. The global image and the local image are fused to obtain a global fused image of the interventional device.

5. The method according to claim 4, characterized in that, The method further includes: When the interventional device is detected to have moved to a preset boundary range or the local scanning field of view reaches the preset boundary range, the interventional environment is imaged according to the global scanning field of view of the imaging device to obtain a global image of the interventional device.

6. The method according to any one of claims 1-3, characterized in that, The method further includes: Display the local field of view identifier corresponding to the local scanned field of view region at the corresponding position in the global image and / or the global fused image; The global image includes the intervention environment corresponding to the current position, the scanning field of view corresponding to the local image is smaller than the scanning field of view corresponding to the global image, and the local image overlaps with the global image. The global fused image is the image after fusing the local image and the global image.

7. The method according to claim 6, characterized in that, The method further includes: If the interventional device is detected to have moved to a preset boundary range or the local scanning field of view has reached the preset boundary range, the global field of view identifier corresponding to the subsequent global imaging scan is displayed in the global image and / or the global fused image.

8. The method according to claim 7, characterized in that, The method further includes: The global image and the subsequent global image corresponding to the subsequent global imaging scan are stitched together, or the global fused image and the subsequent global image are stitched together to obtain a global navigation image; The local view marker is displayed on the global navigation image.

9. The method according to any one of claims 1-3, characterized in that, The method further includes: If image overlap of the interventional device is detected in the local image, the imaging adjustment angle and the device motion information corresponding to the imaging adjustment angle are calculated. Based on the device motion information, the imaging device is controlled to move so that the imaging angle of the imaging device is the imaging adjustment angle, so as to acquire a local image of the interventional device under the imaging adjustment angle. Wherein, the interventional device does not have image overlap in the local image corresponding to the imaging adjustment perspective.

10. An imaging device for an interventional instrument, characterized in that, include: The data acquisition module is used to acquire the movement trajectory and current position of interventional instruments in the interventional environment; The field of view prediction module is used to determine the local scanning field of view of the imaging device based on the motion trajectory and the current position. The local scanning field of view includes at least the expected travel path of the interventional device. The instrument imaging module is used to image the interventional device based on the local scanning field of view to obtain a local image of the interventional device.

11. An electronic device, characterized in that, include: A processor and a memory, the memory being used to store a computer program, the processor being used to invoke and run the computer program stored in the memory to perform the method of any one of claims 1-9.

12. A computer program product containing instructions, characterized in that, When the computer program product is run on an electronic device, the electronic device performs the method of any one of claims 1-9.

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