Image acquisition method, apparatus, medical device, and computer program product

Abstract

This application relates to the field of medical technology and provides an image acquisition method, apparatus, medical device, and computer program product, including: determining the acquisition protocol required when using the medical device; obtaining the human body surface coordinates of the scanned object based on the acquisition protocol; acquiring the reference coordinates of the area to be acquired in the scanned object; fusing the human body surface coordinates and the reference coordinates to obtain the target coordinates of the area to be acquired; controlling the image acquisition module to move to the target coordinates and acquiring the target image of the area to be acquired. This application, based on the human body surface coordinates obtained by the acquisition protocol and the reference coordinates of the area to be acquired, and by fusing these two sets of coordinates, can accurately locate the actual position of the area to be acquired within the scanned object's body. This eliminates the need for manual intervention in positioning and continuous fluoroscopy, thereby avoiding excessive radiation exposure to the scanned object.

Description

Technical Field

[0001] This application belongs to the field of medical technology, and in particular relates to an image acquisition method, device, medical equipment, and computer program product. Background Technology

[0002] Digital subtraction angiography (DSA) is a computer-assisted imaging method for angiography. During image acquisition using a DSA system, the system needs to locate specific parts of the body being scanned (e.g., a patient). Current technology uses continuous fluoroscopy during gantry movement to achieve precise organ localization. This method of continuous fluoroscopy not only relies on the physician's clinical experience but also exposes the scanned individual to significant radiation exposure. Summary of the Invention

[0003] This application provides an image acquisition method, device, medical equipment, and computer program product to solve the problems that the positioning method of continuous fluoroscopy in DSA system requires reliance on the doctor's clinical experience and that the scanned object has to endure a lot of radiation damage.

[0004] In a first aspect, embodiments of this application provide an image acquisition method, including:

[0005] Determine the data collection protocol required when using medical devices;

[0006] Based on the acquisition protocol, the coordinates of the human body surface of the scanned object are obtained;

[0007] Obtain the reference coordinates of the area to be collected in the scanned object;

[0008] The coordinates of the human body surface and the reference coordinates are fused to obtain the target coordinates of the area to be collected.

[0009] The image acquisition module is controlled to move to the target coordinates and acquire the target image of the area to be acquired.

[0010] This application provides an image acquisition method that involves determining the acquisition protocol required when using medical equipment; obtaining the human body surface coordinates of the scanned object based on the acquisition protocol; acquiring the reference coordinates of the area to be acquired in the scanned object; fusing the human body surface coordinates and the reference coordinates to obtain the target coordinates of the area to be acquired; controlling the image acquisition module to move to the target coordinates and acquiring the target image of the area to be acquired. Determining the acquisition protocol in this application signifies a comprehensive consideration of factors such as the patient's condition, the purpose of the examination, and the equipment's performance, laying the foundation for subsequent operations. Based on the human body surface coordinates and the reference coordinates of the area to be acquired obtained from the acquisition protocol, and by fusing these two sets of coordinates, the actual position of the area to be acquired within the scanned object can be accurately located. This eliminates the need for manual intervention in positioning and continuous fluoroscopy, thereby avoiding excessive radiation exposure to the scanned object. Simultaneously, the clearly defined acquisition protocol and target coordinates allow the image acquisition module to quickly move to the designated position to begin acquisition, significantly shortening preparation time and improving image acquisition efficiency compared to repeated positioning attempts.

[0011] In one possible implementation of the first aspect, obtaining the human body surface coordinates of the scanned object based on the acquisition protocol includes:

[0012] Determine the size range of the scanned object;

[0013] Select preset body surface coordinates corresponding to the body size range from the data collection protocol, and use the preset body surface coordinates as the human body surface coordinates.

[0014] In the above embodiments, the positions and shapes of body parts differ for scanned objects of different body shapes during image acquisition. By determining the body shape range and selecting the corresponding preset body surface coordinates, the image acquisition module can be more accurately aligned with the target area. Furthermore, it eliminates the need to spend a significant amount of time precisely measuring and adjusting the body surface coordinates of each scanned object during the acquisition process, greatly shortening the preparation time before acquisition and improving acquisition efficiency.

[0015] In one embodiment of the first aspect, obtaining the human body surface coordinates of the scanned object based on the acquisition protocol includes:

[0016] Acquire a first historical sequence image of the scanned object under the acquisition protocol; the first historical sequence image corresponds to the acquisition area.

[0017] Based on the first historical sequence images, the coordinates of the human body surface are determined.

[0018] In the above embodiments, the first historical image sequence records the previous conditions of the scanned object in the area to be acquired under the same acquisition protocol, containing rich anatomical structural information. Determining the body surface coordinates based on these images allows for reference to past actual image presentations, enabling more accurate location of relevant parts. Furthermore, using historical image sequences to determine body surface coordinates eliminates the need for complex re-localization operations during each acquisition, saving localization time and accelerating the acquisition process.

[0019] In one embodiment of the first aspect, obtaining the human body surface coordinates of the scanned object based on the acquisition protocol includes:

[0020] Under the aforementioned acquisition protocol, the scanning object is photographed using a camera module to obtain the coordinates of the human body surface.

[0021] In the above embodiments, the camera module can directly capture images of the surface of the scanned object and present them as images, allowing for a direct observation of information such as the location of various parts of the scanned object's body and feature points. Compared to other abstract positioning methods, this intuitive visual information makes it easier to accurately determine the body surface coordinates.

[0022] In one embodiment of the first aspect, obtaining the reference coordinates of the region to be collected in the scanned object includes:

[0023] Acquire the second historical sequence image of the scanned object under the acquisition protocol;

[0024] The reference coordinates are determined based on the second historical sequence image.

[0025] In the above embodiments, the second historical sequence images contain past information of the scanned object under the same acquisition protocol. This data reflects the true situation of a specific area of ​​the scanned object. Determining reference coordinates based on these images allows reference to previously accurately recorded position, shape, and other information, avoiding errors that may occur due to a single judgment or measurement. This enables a more accurate determination of reference coordinates that match the scanned object.

[0026] In one embodiment of the first aspect, the step of fusing the human body surface coordinates and the reference coordinates to obtain the target coordinates of the area to be collected includes:

[0027] The reference coordinates are superimposed on the human body surface coordinates to obtain the target coordinates.

[0028] In the above embodiments, the human body surface coordinates provide positional information based on the appearance of the human body, while the reference coordinates may contain more specific information about the area to be acquired, such as the location of lesions and key anatomical structures. Superimposing the two can integrate information from these two different sources, making the target coordinates more accurately reflect the actual location of the area to be acquired within the human body, thereby improving the efficiency of subsequent image acquisition.

[0029] In one embodiment of the first aspect, acquiring the target image of the area to be acquired includes:

[0030] Acquire an initial image of the area to be acquired;

[0031] If the confidence level of the initial image is greater than or equal to a set threshold, then the initial image is determined as the target image;

[0032] If the confidence level is less than the set threshold, the motion offset is determined based on the difference between the confidence level and the set threshold; and the image acquisition module is controlled to move by the motion offset to acquire the image and obtain the target image.

[0033] In the above implementation, an initial image is evaluated by setting a confidence threshold. If the confidence level is greater than or equal to the threshold, it is directly identified as the target image, ensuring that the quality of the used image meets a certain standard. If the confidence level is less than the threshold, the motion offset is determined based on the difference between the confidence level and the threshold, and adjustments are made during acquisition. This is an intelligent optimization method. Compared to blindly repeating acquisitions, this targeted adjustment can acquire high-quality images more quickly, reducing the blindness and randomness of adjustments and further improving acquisition efficiency.

[0034] Secondly, embodiments of this application provide an image acquisition device, including:

[0035] The protocol determination unit is used to determine the protocol to be collected when using medical devices.

[0036] The first coordinate determination unit is used to obtain the human body surface coordinates of the scanned object based on the acquisition protocol.

[0037] The first acquisition unit is used to acquire the reference coordinates of the area to be acquired in the scanned object; the reference coordinates are used to describe the reference position of the area to be acquired on the human body.

[0038] The processing unit is used to fuse the coordinates of the human body surface and the reference coordinates to obtain the target coordinates of the area to be collected;

[0039] The control unit is used to control the image acquisition module to move to the target coordinates and acquire the target image of the area to be acquired.

[0040] In one embodiment of the second aspect, the first coordinate determining unit specifically includes:

[0041] A range determination unit is used to determine the body size range of the scanned object;

[0042] The selection unit is used to select preset body surface coordinates corresponding to the body size range from the protocol to be collected, and to use the preset body surface coordinates as the human body surface coordinates.

[0043] In one embodiment of the second aspect, the first coordinate determining unit specifically includes:

[0044] The second acquisition unit is used to acquire a first historical sequence image of the scanned object under the acquisition protocol; the first historical sequence image corresponds to the acquisition area.

[0045] The second coordinate determination unit is used to determine the coordinates of the human body surface based on the first historical sequence image.

[0046] In one embodiment of the second aspect, the first coordinate determining unit specifically includes:

[0047] The imaging unit is used to capture images of the scanned object through a camera module under the acquisition protocol to obtain the coordinates of the human body surface.

[0048] In one embodiment of the second aspect, the first acquisition unit specifically includes:

[0049] The third acquisition unit is used to acquire the second historical sequence image of the scanned object under the acquisition protocol;

[0050] The third coordinate determination unit is used to determine the reference coordinates based on the second historical sequence image.

[0051] In one embodiment of the second aspect, the processing unit specifically includes:

[0052] The overlay unit is used to overlay the reference coordinates onto the human body surface coordinates to obtain the target coordinates.

[0053] In one embodiment of the second aspect, the control unit specifically includes:

[0054] The first acquisition unit is used to acquire an initial image of the area to be acquired;

[0055] An image determination unit is configured to determine the initial image as the target image if the confidence level of the initial image is greater than or equal to a set threshold.

[0056] The second acquisition unit is used to determine the motion offset based on the difference between the confidence level and the set threshold if the confidence level is less than the set threshold; and to control the image acquisition module to move by the motion offset and then acquire the image to obtain the target image.

[0057] Thirdly, embodiments of this application provide a medical device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the image acquisition method as described in any one of the first aspects above.

[0058] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the image acquisition method as described in any one of the first aspects above.

[0059] Fifthly, embodiments of this application provide a computer program product that, when run on a medical device, enables the medical device to perform the image acquisition method described in any one of the first aspects. Attached Figure Description

[0060] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the 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.

[0061] Figure 1 This is a flowchart illustrating the implementation of an image acquisition method provided in an embodiment of this application;

[0062] Figure 2 This is a flowchart illustrating the implementation of an image acquisition method provided in another embodiment of this application;

[0063] Figure 3 This is a flowchart illustrating the implementation of an image acquisition method provided in another embodiment of this application;

[0064] Figure 4 This is a schematic diagram of the structure of an image acquisition device provided in an embodiment of this application;

[0065] Figure 5 This is a schematic diagram of the structure of a medical device provided in one embodiment of this application. Detailed Implementation

[0066] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0067] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0068] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0069] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0070] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0071] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0072] In practical applications, digital subtraction angiography (DSA) is a computer-assisted imaging method for angiography. During image acquisition using a DSA system, the system needs to locate specific parts of the body being scanned (e.g., a patient). Current technology achieves precise organ localization by performing continuous fluoroscopy during gantry movement. This method of localization via continuous fluoroscopy not only relies on the physician's clinical experience but also exposes the scanned individual to significant radiation exposure.

[0073] Based on this, this application proposes an image acquisition method that can accurately locate the actual position of the area to be acquired within the human body of the scanned object. This method eliminates the need for manual positioning and continuous fluoroscopy, thereby avoiding excessive radiation damage to the scanned object.

[0074] Please see Figure 1 , Figure 1 This is a flowchart illustrating the implementation of an image acquisition method according to an embodiment of this application. In this embodiment, the subject of the image acquisition method is a medical device. The medical device can be a DSA system, or a medical device equipped with a DSA system.

[0075] like Figure 1 As shown, an image acquisition method provided in one embodiment of this application may include steps S101 to S105, which are described in detail below:

[0076] In S101, the protocol to be collected when using medical devices is determined.

[0077] It should be noted that during a DSA examination, the acquisition protocol refers to a set of pre-defined parameters and rules for image acquisition. It is like a detailed operating manual that guides the medical equipment on how to acquire image data to ensure high-quality vascular images.

[0078] In one implementation of this application, the medical device can directly determine the historical acquisition protocol used when the scanned object was examined by the medical device at the end of the historical time period as the acquisition protocol to be acquired at this time. The historical time period can be determined according to actual needs and is not limited here. The scanned object specifically refers to the person who needs to be examined by the medical device. For example, the scanned object can be a patient.

[0079] In another implementation of this application, the operator can input the protocol to be collected through the front-end interface of the medical device, and thus the medical device can receive the protocol. The operator can be a medical professional.

[0080] In S102, the coordinates of the human body surface of the object being scanned are obtained based on the acquisition protocol.

[0081] In this embodiment, the medical device can acquire the human body surface coordinates of the scanned object under the acquisition protocol. The human body surface coordinates are used to describe a set of three-dimensional coordinates composed of the three-dimensional coordinates of organs and tissues with certain characteristics on the surface of the scanned object.

[0082] In one embodiment of this application, the medical device can specifically be implemented via, as shown in the example below. Figure 2 Steps S201 to S202, which determine the coordinates of the human body surface, are described in detail below:

[0083] In S201, the body size range of the scanned object is determined.

[0084] In this embodiment, the medical device can capture a full-body image of the scanned object through a camera module connected in communication with it. The medical device can then compare this full-body image with a pre-stored standard full-body image to determine the magnitude of the difference between the two images.

[0085] The medical equipment can then determine the body size range of the scanned object based on the size of the aforementioned differences.

[0086] It should be noted that the medical device has multiple preset body size ranges pre-stored, including but not limited to: a first range, a second range, a third range, and a fourth range. Among them, the preset body size range corresponding to the standard full-body image is the second range.

[0087] Therefore, medical devices can determine the body size range of the scanned object by using the aforementioned differences and the aforementioned multiple preset body size ranges.

[0088] In one implementation of this embodiment, the medical device can also determine the height of the scanned object through a human body scanning module that is communicatively connected to it.

[0089] In this embodiment, the medical device pre-stores the correspondence between different height ranges and different body size ranges.

[0090] Therefore, medical devices can determine the height range of the scanned subject based on their height. Then, by considering the height range and the correspondence between different height ranges and different body type ranges, the medical device can determine the body type range of the scanned subject.

[0091] In S202, preset body surface coordinates corresponding to the body size range are selected from the protocol to be collected, and the preset body surface coordinates are used as the human body surface coordinates.

[0092] In this embodiment, the acquisition protocol is pre-set with preset body surface coordinates corresponding to different body size ranges. Therefore, the medical device can select the preset body surface coordinates corresponding to the body size range of the scanned object from the acquisition protocol and use the corresponding preset body surface coordinates as the body surface coordinates of the scanned object.

[0093] Using the above method, the position and shape of body parts differ when scanning subjects of different body shapes are image acquired. By determining the body shape range and selecting the corresponding preset body surface coordinates, the image acquisition module can be more accurately aligned with the target area. Furthermore, it eliminates the need to spend a significant amount of time precisely measuring and adjusting the body surface coordinates of each scanned subject during the acquisition process, greatly shortening preparation time and improving acquisition efficiency.

[0094] In another embodiment of this application, the medical device can also determine the coordinates of the human body surface in the following manner, as detailed below:

[0095] Acquire a first historical sequence image of the scanned object under the acquisition protocol; the first historical sequence image corresponds to the acquisition area.

[0096] Based on the first historical sequence images, the coordinates of the human body surface are determined.

[0097] In this embodiment, the medical device can acquire a first historical sequence of images of the scanned object under the acquisition protocol. The first historical sequence of images corresponds to the area to be acquired.

[0098] It should be noted that the first historical sequence images refer to a series of images obtained by continuous and dynamic X-ray image acquisition of a specific anatomical site.

[0099] In practical applications, the acquired image sequence typically uses an image coordinate system, with a corner or center of the image as the origin, establishing horizontal and vertical coordinate axes. Within this coordinate system, the relative coordinates of the region of interest or specific anatomical landmarks can be determined based on the position and morphology of the anatomical structures in the acquired image sequence. Subsequently, these image sequences are fused with other medical imaging modalities (such as CT and MRI). Using specific image registration algorithms, the correspondences of the same anatomical structures in different modalities can be determined within the fused image, thereby further refining the relative coordinates of human tissues in different image spaces.

[0100] In practical applications, image registration refers to the process of geometrically aligning two or more images of the same scene acquired at different times, from different perspectives, or by different sensors.

[0101] It should be noted that the image registration algorithms mentioned above can be existing image registration algorithms, such as feature-based registration algorithms (e.g., Scale Invariant Feature Transform SIFT, Accelerated Robust Feature Transform SURF, etc.), region-based registration algorithms (e.g., cross-correlation algorithms, normalized cross-correlation algorithms, and mutual information algorithms, etc.), and transformation model-based registration algorithms (e.g., rigid body transformation registration, affine transformation registration, and nonlinear transformation registration, etc.). The specific implementation processes of the above-mentioned registration algorithms will not be elaborated here.

[0102] Based on this, medical devices can fuse the first historical sequence images with other medical imaging modalities to obtain a fused image. Then, the medical devices can process the fused image using a specific image registration algorithm to obtain the coordinates of the human body surface.

[0103] In this way, the first historical image sequence records the previous conditions of the scanned object in the area to be acquired under the same acquisition protocol, containing rich anatomical structural information. Determining the body surface coordinates based on these images allows for reference to past actual image presentations, leading to more accurate location of relevant parts. Furthermore, using historical image sequences to determine body surface coordinates eliminates the need for complex re-localization operations during each acquisition, saving localization time and accelerating the acquisition process.

[0104] In another embodiment of this application, the medical device can also capture images of the entire body of the scanned object through a camera module under the acquisition protocol, thereby obtaining the real-time coordinates of the human body surface of the scanned object.

[0105] In this embodiment, the camera module can directly capture images of the surface of the scanned object and present them as images. This allows for a direct observation of the various parts of the scanned object's body, the location of feature points, and other information. Compared to other abstract positioning methods, this intuitive visual information makes it easier to accurately determine the body surface coordinates.

[0106] In S103, the reference coordinates of the area to be collected in the scanned object are obtained; the reference coordinates are used to describe the reference position of the area to be collected on the human body.

[0107] It is understood that the reference coordinates of the area to be acquired in the scanned object can be the coordinates of the region of interest or specific anatomical landmarks of the scanned object in the reference sequence images when the operator scans the object using medical equipment. In other words, the coordinates of the region of interest or specific anatomical landmarks of the scanned object in the reference sequence images are the reference coordinates of the area to be acquired in the scanned object in this application, and the region of interest or specific anatomical landmarks of the scanned object are the area to be acquired in the scanned object in this application. The reference sequence images refer to a series of standard images obtained by continuously and dynamically acquiring X-ray images of the region of interest or specific anatomical landmarks of the scanned object.

[0108] In practical applications, the above-mentioned image sequence usually has an image coordinate system, with a corner point or center of the image as the origin, and horizontal and vertical coordinate axes are established.

[0109] In this embodiment of the application, in order to determine which part of the body the medical device needs to examine, the medical device can obtain the reference coordinates of the area to be collected within the scanned object. Specifically, the area to be collected refers to the part of the body within the scanned object that needs to be examined, and the reference coordinates are used to describe the reference position of the area to be collected on the human body.

[0110] In one embodiment of this application, the medical device may obtain reference coordinates according to the following steps, detailed below:

[0111] Acquire the second historical sequence image of the scanned object under the acquisition protocol;

[0112] The reference coordinates are determined based on the second historical sequence image.

[0113] In this embodiment, the medical device can acquire a second historical sequence image of the scanned object under the acquisition protocol. The second historical sequence image corresponds to a historical acquisition area within the scanned object.

[0114] It should be noted that the second historical sequence images refer to a series of images obtained by continuous and dynamic X-ray image acquisition of a specific anatomical site.

[0115] Based on this, the medical device can directly identify the historical acquisition area corresponding to the second historical sequence image as the area to be acquired. Then, the medical device can use the three-dimensional coordinates of this historical acquisition area as the reference coordinates for the area to be acquired.

[0116] In this way, the second historical image sequence contains past information about the scanned object under the same acquisition protocol, reflecting the true condition of a specific area of ​​the scanned object. Determining reference coordinates based on these images allows for reference to previously accurately recorded position, shape, and other information, avoiding errors that may arise from a single judgment or measurement. This enables a more precise determination of the reference coordinates that match the scanned object.

[0117] In another embodiment of this application, the acquisition protocol is configured with the acquisition area corresponding to the scanned object. Therefore, the medical device can directly determine the acquisition area of ​​the scanned object from the acquisition protocol.

[0118] In S104, the coordinates of the human body surface and the reference coordinates are fused to obtain the target coordinates of the area to be collected.

[0119] In this embodiment of the application, in order to clarify the specific location of the area to be acquired in the scanned object so as to facilitate subsequent image acquisition, the medical device can perform fusion processing on the human body surface coordinates and reference coordinates to determine the specific location of the area to be acquired in the human body surface coordinates of the scanned object, thereby obtaining the target coordinates of the area to be acquired.

[0120] In one implementation of this application, the medical device can perform fusion processing of human body surface coordinates and reference coordinates by: the medical device can spatially register the human body surface coordinates with the reference coordinates; correspondingly, the target coordinates of the area to be collected can be obtained by: generating a target coordinate system.

[0121] In one embodiment of this application, the medical device can superimpose the aforementioned reference coordinates onto the body surface coordinates of the scanned object to determine the location range of the area to be collected within the body of the scanned object, thereby obtaining the target coordinates.

[0122] In S105, the image acquisition module is controlled to move to the target coordinates and acquire the target image of the area to be acquired.

[0123] In this embodiment of the application, after obtaining the target coordinates of the area to be acquired, the medical device can control the image acquisition module to move to the target coordinates of the area to be acquired through a motion control component connected in communication with it. After that, after detecting that the image acquisition module has moved to the target coordinates, the medical device can control the image acquisition module to acquire images of the range corresponding to the target coordinates, thereby obtaining the target image of the area to be acquired.

[0124] In one implementation of this application embodiment, in conjunction with S104, the medical device can perform fusion processing on the human body surface coordinates and reference coordinates by: spatially registering the human body surface coordinates with the reference coordinates; correspondingly, obtaining the target coordinates of the area to be acquired can be achieved by: generating a target coordinate system. Therefore, the medical device can control the image acquisition module to move to the target coordinates and acquire the target image of the area to be acquired by: driving the image acquisition module to move along the target coordinate system, and performing low-dose pulse fluoroscopy to acquire the target image after reaching the position corresponding to the target coordinates. The image acquisition module can be the C-arm of a DSA device, and the target image can be an angiography image.

[0125] In one embodiment of this application, the medical device can specifically be implemented via, as shown in the example below. Figure 3 The target image is obtained through steps S301 to S303, as shown below:

[0126] In S301, an initial image of the area to be acquired is obtained.

[0127] In this embodiment, after obtaining the target coordinates of the area to be acquired, the medical device can control the image acquisition module to move to the target coordinates of the area to be acquired through a motion control component connected in communication with it. After that, when the medical device detects that the image acquisition module has moved into position, that is, moved to the target coordinates, the medical device can control the image acquisition module to acquire images of the range corresponding to the target coordinates, thereby obtaining the initial image of the area to be acquired.

[0128] It should be noted that the medical device has pre-stored standard images of different acquisition areas within the body of the scanned object. Therefore, the medical device can compare the initial image with the standard image of the area to be acquired to calculate the reliability of the initial image.

[0129] The medical device can then compare the aforementioned confidence level with a set threshold. This set threshold can be configured according to actual needs and is not restricted here.

[0130] In one embodiment of this application, when the medical device detects that the confidence level of the initial image is greater than or equal to a set threshold, it may execute step S302.

[0131] In another embodiment of this application, when the medical device detects that the confidence level is less than the above-mentioned set threshold, it may execute step S303.

[0132] In S302, if the confidence level of the initial image is greater than or equal to a set threshold, then the initial image is determined as the target image.

[0133] In this embodiment, when the medical device detects that the confidence level is greater than or equal to the above-mentioned set threshold, it indicates that the initial image is not much different from the standard image. In other words, the medical device has successfully acquired the image of the area to be acquired. Therefore, the medical device can directly determine the above-mentioned initial image as the final target image.

[0134] In S303, if the confidence level is less than the set threshold, the motion offset is determined based on the difference between the confidence level and the set threshold; and the image acquisition module is controlled to move by the motion offset to acquire the image and obtain the target image.

[0135] In this embodiment, when the medical device detects that the confidence level is less than the set threshold, it indicates that the initial image differs significantly from the standard image. In other words, the medical device fails to acquire the image of the area to be acquired. Therefore, the medical device can calculate the difference between the confidence level and the set threshold.

[0136] It should be noted that the medical device pre-stores the correspondence between different difference ranges and different motion offsets. Therefore, in this embodiment, the medical device can determine the difference range between the confidence level of the initial image and the set threshold. Then, based on the difference range between the confidence level of the initial image and the set threshold, and the correspondence between different difference ranges and different motion offsets, the medical device can determine the motion offset of the image acquisition module at this time.

[0137] Afterwards, the medical device can control the image acquisition module to move by the aforementioned motion offset to acquire images and obtain the final target image.

[0138] The above method evaluates the initial image by setting a confidence threshold. If the confidence level is greater than or equal to the threshold, it is directly identified as the target image, ensuring that the used images meet certain quality standards. If the confidence level is less than the threshold, the motion offset is determined based on the difference between the confidence level and the threshold, and adjustments are made accordingly. This is an intelligent optimization method. Compared to blindly repeating acquisitions, this targeted adjustment can acquire high-quality images more quickly, reducing the randomness and haphazardness of adjustments and further improving acquisition efficiency.

[0139] In some possible embodiments, the aforementioned confidence level can be replaced with a degree of certainty. For details on how to obtain the target image based on the degree of certainty, please refer to [link to relevant documentation]. Figure 3 Steps S302 to S303 are not described in detail here.

[0140] In some other possible embodiments, after obtaining the initial image described above, the medical device may also use a convolutional neural network to score the clarity of blood vessels in the initial image.

[0141] In this embodiment, taking the example of a medical device driving the C-arm of a DSA device to move along a target coordinate system and performing low-dose pulse fluoroscopy to acquire an image after reaching the position corresponding to the target coordinates, if the medical device detects that the vascular clarity score is less than a set score, it indicates that the quality of the initial image is poor. Therefore, the medical device can calculate the pose compensation amount of the C-arm based on the gradient descent algorithm, and adjust the C-arm based on this pose compensation amount to perform the image acquisition operation again to obtain the latest initial image. The vascular clarity score is then recalculated, and the C-arm is adjusted in this cyclical manner until the vascular clarity score of the final initial image is greater than or equal to the set score. At this point, the final initial image is determined as the target image. The set score can be determined according to actual needs and is not limited here.

[0142] As can be seen from the above, the image acquisition method provided in this application involves determining the acquisition protocol required when using medical equipment; obtaining the human body surface coordinates of the scanned object based on the acquisition protocol; acquiring the reference coordinates of the area to be acquired in the scanned object; fusing the human body surface coordinates and the reference coordinates to obtain the target coordinates of the area to be acquired; controlling the image acquisition module to move to the target coordinates and acquiring the target image of the area to be acquired. Determining the acquisition protocol in this application means comprehensively considering factors such as the patient's condition, the purpose of the examination, and the performance of the equipment, laying the foundation for subsequent operations. Based on the human body surface coordinates and the reference coordinates of the area to be acquired obtained from the acquisition protocol, and by fusing these two sets of coordinates, the actual position of the area to be acquired in the scanned object's body can be accurately located. This eliminates the need for manual intervention in positioning and continuous fluoroscopy, thereby avoiding excessive radiation damage to the scanned object. Simultaneously, the clearly defined acquisition protocol and target coordinates enable the image acquisition module to quickly move to the designated position to begin acquisition, significantly shortening preparation time and improving image acquisition efficiency compared to repeated positioning attempts.

[0143] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0144] Corresponding to the image acquisition method described in the above embodiments, Figure 4 A schematic diagram of an image acquisition device according to an embodiment of this application is shown. For ease of explanation, only the parts related to the embodiment of this application are shown. (Refer to...) Figure 4 The image acquisition device 400 includes: a protocol determination unit 41, a first coordinate determination unit 42, a first acquisition unit 43, a processing unit 44, and a control unit 45. Wherein:

[0145] The protocol determination unit 41 is used to determine the protocol to be collected when using medical equipment.

[0146] The first coordinate determination unit 42 is used to obtain the human body surface coordinates of the scanned object based on the acquisition protocol.

[0147] The first acquisition unit 43 is used to acquire the reference coordinates of the area to be acquired in the scanned object; the reference coordinates are used to describe the reference position of the area to be acquired on the human body.

[0148] The processing unit 44 is used to fuse the human body surface coordinates and the reference coordinates to obtain the target coordinates of the area to be collected.

[0149] The control unit 45 is used to control the image acquisition module to move to the target coordinates and acquire the target image of the area to be acquired.

[0150] In one embodiment of this application, the first coordinate determination unit 42 specifically includes a range determination unit and a selection unit.

[0151] in:

[0152] The range determination unit is used to determine the body size range of the scanned object.

[0153] The selection unit is used to select preset body surface coordinates corresponding to the body size range from the protocol to be collected, and to use the preset body surface coordinates as the human body surface coordinates.

[0154] In one embodiment of this application, the first coordinate determination unit 42 specifically includes: a second acquisition unit and a second coordinate determination unit. Wherein:

[0155] The second acquisition unit is used to acquire the first historical sequence image of the scanned object under the acquisition protocol; the first historical sequence image corresponds to the acquisition area.

[0156] The second coordinate determination unit is used to determine the coordinates of the human body surface based on the first historical sequence image.

[0157] In one embodiment of this application, the first coordinate determination unit 42 specifically includes: a shooting unit.

[0158] The imaging unit is used to capture images of the scanned object through a camera module under the acquisition protocol, thereby obtaining the coordinates of the human body surface.

[0159] In one embodiment of this application, the first acquisition unit 43 specifically includes: a third acquisition unit and a third coordinate determination unit. Wherein:

[0160] The third acquisition unit is used to acquire the second historical sequence image of the scanned object under the acquisition protocol.

[0161] The third coordinate determination unit is used to determine the reference coordinates based on the second historical sequence image.

[0162] In one embodiment of this application, the processing unit 44 specifically includes: a superposition unit.

[0163] The overlay unit is used to overlay the reference coordinates onto the human body surface coordinates to obtain the target coordinates.

[0164] In one embodiment of this application, the control unit 45 specifically includes: a first acquisition unit, an image determination unit, and a second acquisition unit. Wherein:

[0165] The first acquisition unit is used to acquire the initial image of the area to be acquired.

[0166] The image determination unit is used to determine the initial image as the target image if the confidence level of the initial image is greater than or equal to a set threshold.

[0167] The second acquisition unit is used to determine the motion offset based on the difference between the confidence level and the set threshold if the confidence level is less than the set threshold; and to control the image acquisition module to move by the motion offset and then acquire the image to obtain the target image.

[0168] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0169] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0170] Figure 5This is a schematic diagram of the structure of a medical device provided in one embodiment of this application. Figure 5 As shown, the medical device 5 of this embodiment includes: at least one processor 50 ( Figure 5 (Only one is shown) a processor, a memory 51, and a computer program 52 stored in the memory 51 and executable on the at least one processor 50, wherein the processor 50 executes the computer program 52 to implement the steps in any of the above-described image acquisition method embodiments.

[0171] The medical device may include, but is not limited to, a processor 50 and a memory 51. Those skilled in the art will understand that... Figure 5 This is merely an example of medical device 5 and does not constitute a limitation on medical device 5. It may include more or fewer components than shown in the figure, or combine certain components, or different components, such as input / output devices, network access devices, etc.

[0172] The processor 50 may be a Central Processing Unit (CPU), or it may be other 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. A general-purpose processor may be a microprocessor or any conventional processor.

[0173] In some embodiments, the memory 51 may be an internal storage unit of the medical device 5, such as the RAM of the medical device 5. In other embodiments, the memory 51 may be an external storage device of the medical device 5, such as a plug-in hard drive, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the medical device 5. Furthermore, the memory 51 may include both internal and external storage units of the medical device 5. The memory 51 is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory 51 can also be used to temporarily store data that has been output or will be output.

[0174] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps described in the various method embodiments above.

[0175] This application provides a computer program product that, when run on a medical device, enables the medical device to perform the steps described in the above-described method embodiments.

[0176] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a medical device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0177] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0178] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. An image acquisition method, characterized in that, include: Determine the data collection protocol required when using medical devices; Based on the acquisition protocol, the coordinates of the human body surface of the scanned object are obtained; Obtain the reference coordinates of the area to be collected in the scanned object; The reference coordinates are used to describe the reference position of the area to be collected on the human body; The coordinates of the human body surface and the reference coordinates are fused to obtain the target coordinates of the area to be collected. The image acquisition module is controlled to move to the target coordinates and acquire the target image of the area to be acquired.

2. The image acquisition method as described in claim 1, characterized in that, The process of obtaining the human body surface coordinates of the scanned object based on the acquisition protocol includes: Determine the size range of the scanned object; Select preset body surface coordinates corresponding to the body size range from the data collection protocol, and use the preset body surface coordinates as the human body surface coordinates.

3. The image acquisition method as described in claim 1, characterized in that, The process of obtaining the human body surface coordinates of the scanned object based on the acquisition protocol includes: Acquire a first historical sequence image of the scanned object under the acquisition protocol; the first historical sequence image corresponds to the acquisition area. Based on the first historical sequence images, the coordinates of the human body surface are determined.

4. The image acquisition method as described in claim 1, characterized in that, The process of obtaining the human body surface coordinates of the scanned object based on the acquisition protocol includes: Under the aforementioned acquisition protocol, the scanning object is photographed using a camera module to obtain the coordinates of the human body surface.

5. The image acquisition method as described in claim 1, characterized in that, The step of obtaining the reference coordinates of the area to be collected in the scanned object includes: Acquire the second historical sequence image of the scanned object under the acquisition protocol; The reference coordinates are determined based on the second historical sequence image.

6. The image acquisition method as described in claim 1, characterized in that, The process of fusing the human body surface coordinates and the reference coordinates to obtain the target coordinates of the area to be collected includes: The reference coordinates are superimposed on the human body surface coordinates to obtain the target coordinates.

7. The image acquisition method according to any one of claims 1 to 6, characterized in that, The acquisition of the target image of the area to be acquired includes: Acquire an initial image of the area to be acquired; If the confidence level of the initial image is greater than or equal to a set threshold, then the initial image is determined as the target image; If the confidence level is less than the set threshold, the motion offset is determined based on the difference between the confidence level and the set threshold; and the image acquisition module is controlled to move by the motion offset to acquire the image and obtain the target image.

8. An image acquisition device, characterized in that, include: The protocol determination unit is used to determine the protocol to be collected when using medical devices. The first coordinate determination unit is used to obtain the human body surface coordinates of the scanned object based on the acquisition protocol. The first acquisition unit is used to acquire the reference coordinates of the area to be collected in the scanned object; The reference coordinates are used to describe the reference position of the area to be collected on the human body; The processing unit is used to fuse the coordinates of the human body surface and the reference coordinates to obtain the target coordinates of the area to be collected; The control unit is used to control the image acquisition module to move to the target coordinates and acquire the target image of the area to be acquired.

9. A medical device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the image acquisition method as described in any one of claims 1 to 7.

10. A computer program product, characterized in that, It includes a computer program that, when run, implements the image acquisition method as described in any one of claims 1 to 7.

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