Scanning positioning method, apparatus, device, and storage medium

Abstract

The application discloses a scanning positioning method and device, equipment and storage medium, and relates to the technical field of scanning imaging. The main purpose is to solve the problems that the scanning range needs to be judged artificially or manually operated when a positioning sheet is scanned, so that the scanning accuracy of the positioning sheet is low, and the efficiency is not high. The method comprises the following steps: acquiring basic data of a to-be-detected person and scanning protocol data; determining a target position according to the basic data of the to-be-detected person and based on a pre-trained positioning model, wherein the target position comprises a scanning starting position and a scanning bed height; and controlling the relative position of a scanning bed and a gantry according to the target position and the scanning protocol data.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of scanning imaging technology, in particular to a scanning positioning method, device, equipment and storage medium. BACKGROUND

[0002] Computed tomography (CT) technology can construct images according to received X-ray tomography data penetrating a subject, has the advantages of fast imaging, high density resolution of reconstructed images, and convenient image dimension switching, and is widely used in medical diagnosis. When using a scanning device, the subject needs to be scanned first, and the true scanning range is determined for subsequent spiral scanning or tomographic sequence scanning.

[0003] At present, the starting position and scanning length of the positioning sheet are mainly determined according to the experience of clinicians, or the position of the scanning bed is manually adjusted through the mark irradiated by the positioning lamp on the patient, that is, the scanning range needs to be judged artificially or manually operated during the existing positioning sheet scanning, so that the positioning sheet scanning accuracy is low and the efficiency is not high. Therefore, there is an urgent need for a positioning sheet scanning method to overcome the defects of the prior art. SUMMARY

[0004] Therefore, the present application provides a scanning positioning method, device, equipment and storage medium, which mainly aims to improve the technical problem that the existing positioning sheet scanning needs artificial judgment of the scanning range or manual operation, thereby making the positioning sheet scanning accuracy low and the efficiency not high.

[0005] According to one aspect of the present application, a scanning positioning method is provided, comprising:

[0006] Obtaining basic data of a subject to be detected and scanning protocol data;

[0007] Determining a target position according to the basic data of the subject to be detected and based on a pre-trained positioning model, the target position at least including a scanning starting position and a scanning bed height;

[0008] Controlling the relative position of the scanning bed and the gantry according to the target position and the scanning protocol data.

[0009] Preferably, controlling the scanning bed movement according to the target position and the scanning protocol data comprises:

[0010] Analyzing the scanning protocol data to obtain the relative position relationship between the target position and the actual position of the scanning bed;

[0011] Controlling the relative position of the scanning bed and the gantry according to the relative position relationship and the target position.

[0012] Preferably, before the acquisition of the basic data of the to-be-detected person and the scanning protocol data, the method further comprises:

[0013] Acquiring scanning positioning sample data, wherein the scanning positioning sample data contains a user identity, and basic data corresponding to the user identity, a scanning position, and a scanning type;

[0014] Taking the basic data, the scanning position, and the scanning type corresponding to each user identity as a first dimension, and taking the user identity as a second dimension, panel data is generated;

[0015] According to the panel data, a neural network model is trained to obtain the positioning model.

[0016] Preferably, the determination of the target position according to the basic data of the to-be-detected person and based on the pre-trained positioning model comprises:

[0017] When a target position adjustment instruction is monitored, a request for confirmation of adjustment prompt information is outputted;

[0018] If a confirmation of adjustment response information is received, an adjustment instruction is acquired and parsed, and the initial target position is changed to obtain the target position.

[0019] Preferably, the method further comprises:

[0020] The changed target position, the scanning type of the to-be-detected person when the target position is changed, and the basic data are extracted;

[0021] The positioning model is updated according to the changed target position, the scanning type of the to-be-detected person when the target position is changed, and the basic data.

[0022] Preferably, the basic data of the to-be-detected person includes at least one of the height, the age, the weight parameter, and the scanning type of the to-be-detected person, and the determination of the target position according to the basic data of the to-be-detected person and based on the pre-trained positioning model comprises:

[0023] At least one of the height, the age, the weight parameter, and the scanning type of the to-be-detected person is inputted into the positioning model to obtain a scanning bed height, a starting position, and an ending position of a positioning scan when a positioning scan operation corresponding to the scanning type is performed on the to-be-detected person.

[0024] Preferably, after the control of the movement of the scanning bed according to the target position and the scanning protocol data, the method further comprises:

[0025] A positioning film scan is triggered to be performed to obtain positioning film data of the to-be-detected person.

[0026] According to another aspect of the present application, there is provided a scanning positioning device, comprising:

[0027] an acquisition module configured to acquire basic data of a subject to be detected and scanning protocol data;

[0028] a determination module configured to determine a target position based on the basic data of the subject to be detected and based on a pre-trained positioning model, the target position comprising at least a scanning start position and a scanning bed height;

[0029] a control module configured to control a relative position of a scanning bed and a gantry according to the target position and the scanning protocol data.

[0030] Preferably, the control module comprises:

[0031] a parsing unit configured to parse the scanning protocol data to obtain a relative position relationship between the target position and an actual position of the scanning bed;

[0032] a control unit configured to control the relative position of the scanning bed and the gantry according to the relative position relationship and the target position.

[0033] Preferably, the device further comprises a generation module and a training module,

[0034] the acquisition module is further configured to acquire scanning positioning sample data, the scanning positioning sample data comprising a user identity, and basic data, a scanning position and a scanning type corresponding to the user identity;

[0035] the generation module is configured to generate panel data with the basic data, the scanning position and the scanning type corresponding to each user identity as a first dimension, and the user identity as a second dimension;

[0036] the training module is configured to train a neural network model according to the panel data to obtain the positioning model.

[0037] Preferably, the determination module comprises:

[0038] an output unit configured to output a request confirmation adjustment prompt information when a target position adjustment instruction is monitored;

[0039] the change unit is further configured to, if a confirmation adjustment response information is received, acquire and parse the adjustment instruction, and change the initial target position to obtain the target position.

[0040] Preferably, the device further comprises:

[0041] an extraction module configured to extract the changed target position, and the scanning type and the basic data of the subject to be detected when the target position is changed.

[0042] an updating module configured to update the positioning model according to the changed target position, the scanning type of the to-be-detected person when the target position is changed, and basic data.

[0043] Preferably, the basic data of the to-be-detected person includes at least one of height, age, weight parameter, and scanning type of the to-be-detected person.

[0044] The determining module is specifically configured to input at least one of the height, age, weight parameter, and scanning type of the to-be-detected person into the positioning model to obtain a scanning bed height used when performing a positioning scanning operation corresponding to the scanning type on the to-be-detected person, and a starting position and an ending position of the positioning scanning.

[0045] Preferably, the device further comprises:

[0046] a triggering module configured to trigger the positioning slice scanning to obtain positioning slice data of the to-be-detected person.

[0047] According to another aspect of the present application, a storage medium is provided, and the storage medium stores at least one executable instruction, and the executable instruction causes a processor to perform operations corresponding to the above-mentioned scanning positioning method.

[0048] According to still another aspect of the present application, a computer device is provided, and the computer device comprises a processor, a memory, a communication interface, and a communication bus, and the processor, the memory, and the communication interface complete communication with each other through the communication bus.

[0049] The memory is used to store at least one executable instruction, and the executable instruction causes the processor to perform operations corresponding to the above-mentioned scanning positioning method.

[0050] By means of the above technical solutions, the technical solutions provided by the embodiments of the present application have at least the following advantages:

[0051] The application provides a scanning positioning method and device, which comprises the following steps: firstly, obtaining basic data of a to-be-detected person and scanning protocol data; secondly, determining a target position according to the basic data of the to-be-detected person and based on a pre-trained positioning model, wherein the target position at least comprises a scanning starting position and a scanning bed height; finally, controlling the relative position of a scanning bed and a gantry according to the target position and the scanning protocol data. Compared with the prior art, the embodiment of the application pre-trains a scanning positioning model, and positions a scanning area according to the basic data of a target scanning object and the scanning protocol data during scanning, thereby automatically determining the scanning area and the scanning bed height and controlling the relative position between the scanning bed and the gantry so as to position the scanning area, thereby avoiding the problems of low efficiency and low accuracy caused by manual positioning of the scanning area, and improving the performance of scanning positioning.

[0052] The above description is only a summary of the technical scheme of the application, in order to more clearly understand the technical means of the application, the application can be implemented according to the content of the specification, and in order to make the above and other purposes, characteristics and advantages of the application more obvious and easy to understand, the following specific embodiments of the application are described. BRIEF DESCRIPTION OF DRAWINGS

[0053] Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The accompanying drawings are included to provide a description of the preferred embodiments and are not meant to limit the present application. Furthermore, the same reference numerals are used throughout the several drawings to denote the same or similar parts. In the drawings:

[0054] Figure 1 A scanning positioning method flow chart provided by an embodiment of the application is shown;

[0055] Figure 2 Another scanning positioning method flow chart provided by an embodiment of the application is shown;

[0056] Figure 3 A scanning positioning device composition block diagram provided by an embodiment of the application is shown;

[0057] Figure 4 Another scanning positioning device composition block diagram provided by an embodiment of the application is shown;

[0058] Figure 5 A structure schematic diagram of a computer device provided by an embodiment of the application is shown. DETAILED DESCRIPTION

[0059] Exemplary embodiments of the present disclosure will be described in greater detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it is understood that the present disclosure can be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the present disclosure to those skilled in the art.

[0060] For the existing positioning scan, it is necessary to determine the scanning range or manually operate, so that the positioning scan is not accurate and efficient. Therefore, the embodiment of the present application provides a scanning positioning method, as shown in the figure, which comprises the following steps: Figure 1

[0061] 101. Obtain the basic data of the to-be-detected person and the scanning protocol data.

[0062] The basic data of the to-be-detected person can include patient height, weight, age, gender, scanning type, etc., and the basic data can be added when the patient is admitted to the hospital, or some basic data can be shared from a third party, such as sharing the height, weight, age, gender, etc. of the user from a certain health habit application, and combining the scanning type information in the diagnosis result to construct the basic data of the to-be-detected person in this step. The scanning type data can be obtained from the scanning protocol data, that is, the obtained basic data of the to-be-detected person includes the input data of the patient (patient height, weight, age, gender) and the scanning type extracted from the scanning protocol data. In other words, the basic data of the to-be-detected person and the scanning protocol data can be integrated and processed data.

[0063] It should be noted that when using a CT scanning device to scan a lesion, the scanning protocol has an impact on scanning and reconstruction related parameters, scanning operation steps, etc., and the scanning protocol is also related to the scanning device and the personal settings of the scanning device operator. Therefore, the scanning protocol data needs to be obtained during scanning positioning in order to adaptively adjust the scanning positioning for different protocols.

[0064] 102. Determine the target position according to the basic data of the to-be-detected person and based on a pre-trained positioning model.

[0065] The target position at least includes a scanning start position and a scanning bed height.

[0066] In the medical diagnosis process, the CT device can scan different parts of the to-be-detected person, such as the head, chest, abdomen, etc. Since the scanning frame of the CT scanning device is usually fixed, the scanning bed needs to be moved during scanning so that the scanning device can scan the corresponding part. By limiting the start position of the scanning bed and the end position of the scanning bed, the scanning area can be limited, and the accurate target position can be obtained by combining the scanning bed height.​

[0067] 103. controlling a relative position of the scanning bed and the gantry according to the target position and the scanning protocol data.

[0068] According to the target position and the scanning protocol data, the relative position of the scanning bed and the gantry can be controlled to move the scanning bed to achieve the relative movement of the scanning bed and the gantry, such as a conventional CT, or to move the gantry to achieve the relative movement of the scanning bed and the gantry, such as a suspended rail CT used in an operating room. The following technical solutions are described by taking the movement of the scanning bed as an example. It should be noted that the target position predicted based on the pre-trained positioning model and the basic data of the to-be-detected person is not necessarily the position of the scanning bed coordinate system, i.e., the target position determined according to the positioning model is the starting position 350 mm and the ending position 380 mm, and the scanning bed is 400 mm high, which is not necessarily the region with the bed code of 350 mm to 380 mm. This is because some clinicians will create a coordinate system that meets personal habits, such as establishing a coordinate system with the scanning starting point as the origin. In this case, the system will write the coordinate system conversion relationship into the scanning protocol data, so that when scanning and positioning, the target position is first predicted, and then the scanning bed is moved to the corresponding position in combination with the coordinate conversion relationship in the scanning protocol data.

[0069] The present application provides a scanning positioning method, which first acquires basic data of a to-be-detected person and scanning protocol data, then determines a target position according to the basic data of the to-be-detected person and based on a pre-trained positioning model, the target position at least including a scanning starting position and a scanning bed height, and finally controls a relative position of a scanning bed and a gantry according to the target position and the scanning protocol data. Compared with the prior art, the embodiment of the present application trains a scanning positioning model in advance, and positions a scanning region according to basic data of a target scanning object and scanning protocol data during scanning. The scanning region and the scanning bed height are automatically determined to adapt to the use requirements of different operators, and the relative position between the scanning bed and the gantry is controlled to position the scanning region, thereby avoiding the problems of low efficiency and accuracy caused by manual positioning of the scanning region, and improving the performance of scanning positioning.

[0070] Further, as a refinement and extension of the above embodiment, in order to completely describe the specific implementation process of the above embodiment, another scanning positioning method is provided, as shown in Figure 2 The method comprises:

[0071] 201. acquiring scanning positioning sample data.

[0072] The scan positioning sample data includes a user identification identifier and corresponding basic data, scan location, and scan type. The scan positioning sample data can be user medical data collected from multiple sources. Each user can have one or more data entries. For example, if patient A's scan is a head scan in one medical visit and an abdominal scan in another, the obtained scan positioning sample data could contain two data entries for that user. After obtaining medical data from multiple sources, the data can be preprocessed, such as merging the data according to the identification identifier to obtain data entries that correspond one-to-one with the identification identifier, and then labeling the data according to the identification identifier.

[0073] It should be noted that factors affecting body size, such as the height, weight, and age of the person being tested, will influence the scanning and positioning area, especially weight and height. Therefore, to train the positioning model, data containing at least the user's height, weight, age, and gender is required. However, in practical applications, there will inevitably be data lacking certain attribute information. For example, a data entry may only contain user identity information, gender, age, and height, but not weight information. To avoid data waste caused by invalid data due to missing attribute information, this embodiment can pre-train an attribute information addition model. That is, a prediction model can be trained using user data containing all attribute information. This allows the model to predict the missing data when one or more attribute information is missing from a data entry, thus completing the user data.

[0074] 202. Using the basic data, scanning location, and scanning type corresponding to each of the aforementioned user identity identifiers as the first dimension and the user identity identifier as the second dimension, generate panel data.

[0075] The user identification can be a user ID number or a unique code created when the user seeks medical treatment. The scan type can be a head scan, lung scan, abdominal scan, elbow scan, etc., which can be extracted from the scan protocol. Specifically, both the user identification and the scan type can be extracted from the user's medical data. Since the scan positioning sample data contains the user identification, basic data, scan type, and scan bed starting position, and the corresponding scan bed position differs for the same user depending on the scanned area, in order to obtain a neural network model that can predict the scan bed position, the scan sample data needs to be divided according to the user identification and scan type first. This allows for targeted training based on the scan type, resulting in an accurate scan positioning model.

[0076] For example, the scanned localization sample data collected during the training of the localization model includes:

[0077] User 1: male, 172cm, 75kg, 55 years old, head scan, scan bed start position 350mm, end position 380mm, scan bed height 400mm; lung scan, scan bed start position 380mm, end position 402mm, scan bed height 390mm;

[0078] User 2: female, 162cm, 58kg, 52 years old, abdominal scan, scan bed start position 450mm, end position 470mm, scan bed height 400mm;

[0079] User 3: female, 170cm, 75kg, 27 years old, head scan, scan bed start position 360mm, end position 380mm, scan bed height 360mm;

[0080] User 4: male, 180cm, 80kg, 36 years old, lung scan, scan bed start position 500mm, end position 520mm, scan bed height 385mm; abdominal scan, scan bed start position 525mm, end position 540mm, scan bed height 385mm;

[0081] …

[0082] Based on the scan positioning sample data, the panel data generated according to the user identity and the scan type can be as follows:

[0083]

[0084] It should be noted that the data table in the embodiments of the present application is only an example, and in the specific application process, any form of panel data can be generated according to the user identity, the scan type, etc. to facilitate subsequent training of the neural network model according to the sample data.

[0085] 203. Training a neural network model according to the panel data to obtain the positioning model.

[0086] From the above steps, after obtaining the scan positioning sample data, the sample data can be preprocessed and panel data can be generated, and each piece of data according to the scan type can be extracted from the panel data to train the neural network model, so that the corresponding positioning model can be obtained.

[0087] Specifically, when training the positioning model according to the panel data, in addition to the above attribute information such as gender, height, weight, age, scan type, etc. as input parameters, it can also include scan bed direction, subject positioning, etc.

[0088] 204. Obtain the subject basic data and scan protocol data.

[0089] The basic data of the to-be-detected person can include patient height, weight, age, gender, scan type, etc., and the basic data can be added when the patient is admitted to the hospital, or part of the basic data can be shared from a third party.

[0090] It should be noted that when a lesion is scanned using a scanning device, the scanning protocol has an impact on scanning and reconstruction related parameters, scanning operation steps, etc., and the scanning protocol is related to the scanning device and the personal settings of the scanning device operator, so the scanning protocol data needs to be obtained when scanning positioning is performed, so as to adapt to different protocols.

[0091] 205. determining a target position according to the basic data of the to-be-detected person and based on a pre-trained positioning model.

[0092] In the embodiment of the application, the execution subject can be an intelligent control system with scanning function, for example, an intelligent positioning scanning system, a digital scanning system, etc. For example, when the execution subject is an intelligent positioning scanning system, if the system learns that the to-be-detected person needs to be scanned and positioned according to automatic sensing, receiving scanning positioning instructions, etc., the system can determine the target position for scanning the to-be-detected person according to the basic data of the to-be-detected person.

[0093] Specifically, in the embodiment of the application, step 205 includes: inputting at least one of the height, age, weight parameters and scan type of the to-be-detected person into the positioning model to obtain the height of the scanning bed, the starting position and the ending position of the positioning scan when the positioning scan operation corresponding to the scan type is performed on the to-be-detected person. The intelligent positioning scanning system inputs the parameters in the basic data of the to-be-detected person that have an impact on the positioning scan position into the pre-trained positioning model. Specifically, the input data of the positioning model in the embodiment of the application can include at least one of the height, weight, age and scan type of the to-be-detected person, so that the intelligent positioning scanning system can determine the starting position, ending position and scanning bed height of the positioning scan according to the scanning position suitable for the to-be-detected person to perform the scan corresponding to the current scan type output by the positioning model. As a preferred embodiment, the input data of the positioning model includes height and weight. Further, the scan type can also be included.

[0094] In order to more accurately perform positioning scan, step 205 in the embodiment of the application can further include: when a target position adjustment instruction is monitored, outputting a request confirmation adjustment prompt information; if a confirmation adjustment response information is received, the adjustment instruction is obtained and analyzed, and the initial target position is changed to obtain the target position.

[0095] The request confirmation adjustment prompt information can be in one or more of the following forms: text information, picture information, audio information, video information, and vibration prompt information. The target position adjustment instruction can be generated by the clinician manually modifying the scanning positioning position. The intelligent positioning scanning system outputs a request confirmation information when it detects that the operator modifies the positioning position, and responds to the adjustment instruction after receiving the confirmation modification instruction. The scanning bed is controlled to move, avoiding the problem of inaccurate behavior caused by unintentional adjustment of the operator. Therefore, the safety and accuracy of scanning positioning are improved.

[0096] Further, in order to optimize the accuracy of the positioning model positioning, the embodiment of the present application further comprises: extracting the changed target position and the scanning type and basic data of the to-be-detected person when the target position is changed; and updating the positioning model according to the changed target position, the scanning type and basic data of the to-be-detected person when the target position is changed.

[0097] When the clinician manually adjusts the scanning positioning, the to-be-detected person's basic data, scanning type, and adjusted scanning positioning area at this time are extracted, and the positioning model is optimized according to the adjusted data, so that the positioning model can more accurately perform scanning positioning, and the accuracy of the positioning model is improved.

[0098] 206, control the relative position of the scanning bed and the gantry according to the target position and the scanning protocol data.

[0099] The target position of the to-be-detected person under a certain specified scanning type predicted by the pre-trained positioning model is not always the position of the scanning bed in its own coordinate system. That is, the position predicted by the positioning model is a reference position, which needs to be converted and adjusted in combination with the coordinate system set by the operator, and then the scanning bed movement is controlled.

[0100] The scanning protocol data is analyzed to obtain the relative position relationship between the target position and the actual position of the scanning bed, and the scanning bed is controlled to move to the scanning start position according to the relative position relationship and the target position.

[0101] In the specific application process, the operator can enter the scanning interface after selecting the scanning protocol. If the operator creates a personal setting coordinate system at this time, the coordinate system parameters will be written into the scanning protocol data, so that the scanning positioning server can obtain the data and perform coordinate conversion in combination with the target position to obtain the final bed code corresponding to the scanning bed.

[0102] Specifically, taking the movement of the scan bed as an example, the step 206 comprises: parsing the scan protocol data to obtain a relative position relationship between an operation coordinate system of a target position and an actual coordinate system of the scan bed; and controlling the scan bed to move to an initial scan position according to the relative position relationship and the target position. Wherein, the operation coordinate system is a coordinate system generated based on an operator setting, and the actual coordinate system is a coordinate system in which the scan bed is located.

[0103] According to the above, it can be known that the conversion relationship between the personal setting coordinate system created by the operator and the actual coordinate system is recorded in the scan protocol data, and the position predicted by the positioning model is in the actual coordinate system. Therefore, in order to obtain the coordinate position conforming to the operator, the predicted position and the relative position relationship in the device protocol data need to be converted to obtain the current scan bed position, so that the current bed position can be accurately positioned and adapted to different operator habits.

[0104] In addition, generally, the initial position of the scan bed is determined, and after each scan is completed, the scan bed is reset to the initial position. When the next round of scanning is needed, the intelligent positioning scanning system can calculate the scan target position at this time, i.e., the scan start position, the scan end position and the scan bed height, according to the basic data of the next person to be detected, the scan type and the pre-trained positioning model. That is, the starting point and the ending point in the three-dimensional space are known, so the intelligent positioning scanning system can solve the optimal path at this time and control the path as the motion trail of the scan bed. When the intelligent system receives a scan completion instruction, the scan bed is controlled to reset and move to the initial position. Specifically, the scan completion instruction can be sent when the reset key is touched, or the scan completion instruction can be automatically triggered and sent when the sensor on the scanning device detects that the person to be detected has safely left the scanning device. The embodiments of the present application do not make specific limitations on this.

[0105] 207、triggering to perform a positioning sheet scan to obtain positioning sheet data of the person to be detected.

[0106] After the intelligent positioning scanning system determines the target position of the positioning sheet scan based on the basic data of the person to be detected, the scan bed is controlled to move to the target position, and then the positioning sheet scan of the person to be detected is triggered at the target position, so as to subsequently perform the regular scan according to the positioning sheet information obtained by the scan at the target position.

[0107] The application provides a scanning positioning method, which comprises the following steps: firstly, obtaining basic data of a to-be-detected person and scanning protocol data; secondly, determining a target position according to the basic data of the to-be-detected person and based on a pre-trained positioning model, wherein the target position at least comprises a scanning starting position and a scanning bed height; and finally, controlling the relative position of a scanning bed and a gantry according to the target position and the scanning protocol data. Compared with the prior art, the embodiment of the application can pre-train a scanning positioning model, and can determine the scanning region and the scanning bed height automatically while adapting to the use requirements of different operators, and can control the relative position of the scanning bed and the gantry to the scanning positioning region, thereby avoiding the problems of low efficiency and low accuracy caused by manual positioning of the scanning region, and improving the performance of scanning positioning.

[0108] Further, as Figure 1 and Figure 2 The specific implementation of the method, the embodiment provides a scanning positioning device, as shown in the figure, the device comprises: an acquisition module 31, a determination module 32, a control module 33. Figure 3

[0109] The acquisition module 31 is used for acquiring basic data of a to-be-detected person and scanning protocol data;

[0110] The determination module 32 is used for determining a target position according to the basic data of the to-be-detected person and based on a pre-trained positioning model, wherein the target position at least comprises a scanning starting position and a scanning bed height;

[0111] The control module 33 is used for controlling the relative movement of a scanning bed and a gantry according to the target position and the scanning protocol data.

[0112] In a specific application scenario, Figure 4 As shown in the figure, the control module 33 comprises:

[0113] The analysis unit 331 is used for analyzing the scanning protocol data to obtain the relative position relationship between the target position and the actual position of the scanning bed;

[0114] The control unit 332 is used for controlling the relative position of the scanning bed and the gantry according to the relative position relationship and the target position.

[0115] In a specific application scenario, as Figure 4 As shown in the figure, the device further comprises a generation module 34 and a training module 35,

[0116] The acquisition module 31 is further used for acquiring scanning positioning sample data, wherein the scanning positioning sample data comprises a user identity, and basic data, a scanning position and a scanning type corresponding to the user identity.​

[0117] The generation module 34 is configured to generate panel data by taking the respective base data, scanning position and scanning type corresponding to each user identity as a first dimension, and taking the user identity as a second dimension.

[0118] The training module 35 is configured to train a neural network model according to the panel data to obtain the positioning model.

[0119] In a specific application scenario, as shown in Figure 4 The determination module 32 includes:

[0120] The output unit 321 is configured to output a request confirmation adjustment prompt information when a target position adjustment instruction is monitored.

[0121] The change unit 322 is further configured to, if the confirmation adjustment response information is received, obtain and parse the adjustment instruction, and change the initial target position to obtain the target position.

[0122] In a specific application scenario, as shown in Figure 4 The device further includes:

[0123] The extraction module 36 is configured to extract the changed target position, and the scanning type and the base data of the to-be-detected person when the target position is changed.

[0124] The update module 37 is configured to update the positioning model according to the changed target position, the scanning type and the base data of the to-be-detected person when the target position is changed.

[0125] In a specific application scenario, as shown in Figure 4 The base data of the to-be-detected person includes at least one of a height, an age, a weight parameter and a scanning type of the to-be-detected person,

[0126] The determination module 32 is specifically configured to input at least one of the height, the age, the weight parameter and the scanning type of the to-be-detected person into the positioning model to obtain a scanning bed height when the positioning scanning operation corresponding to the scanning type is performed on the to-be-detected person, and a starting position and an ending position of the positioning scanning.

[0127] In a specific application scenario, as shown in Figure 4 The device further includes:

[0128] The triggering module 38 is configured to trigger the execution of the positioning sheet scanning to obtain the positioning sheet data of the to-be-detected person.

[0129] The application provides a scanning positioning device, which first acquires basic data of a to-be-detected person and scanning protocol data, secondly determines a target position according to the basic data of the to-be-detected person and based on a pre-trained positioning model, the target position at least including a scanning starting position and a scanning bed height, and finally controls relative positions of a scanning bed and a gantry according to the target position and the scanning protocol data. Compared with the prior art, the embodiment of the application pre-trains a scanning positioning model, and positions a scanning area according to basic data of a target scanning object and scanning protocol data during scanning, thereby automatically determining the scanning area and the scanning bed height while adapting to different operator use requirements, and controlling the relative positions of the scanning bed and the gantry to scan the positioning area, so as to avoid the problems of low efficiency and low accuracy caused by manual positioning of the scanning area, thereby improving the performance of scanning positioning.

[0130] According to an embodiment of the application, a storage medium is provided, which stores at least one executable instruction, and the computer executable instruction can execute the scanning positioning method in any method embodiment.

[0131] Figure 5 A structural schematic diagram of a computer device according to an embodiment of the application is shown, and specific embodiments of the application do not limit the specific implementation of the computer device.

[0132] As shown in Figure 5 the computer device can include a processor 402, a communications interface 404, a memory 406, and a communications bus 408.

[0133] The processor 402, the communications interface 404, and the memory 406 can complete mutual communication through the communications bus 408.

[0134] The communications interface 404 is configured to communicate with network elements of other devices, such as clients or other servers.

[0135] The processor 402 is configured to execute the program 410, and specifically can execute related steps in the scanning positioning method embodiments.

[0136] Specifically, the program 410 can include program code, and the program code includes computer operation instructions.

[0137] The processor 402 can be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to perform the embodiments of the present application. The computer device can include one or more processors of the same type or different types, such as one or more CPUs and one or more ASICs.

[0138] The memory 406 is configured to store a program 410. The memory 406 can include a high-speed RAM memory, and can further include a non-volatile memory, such as at least one disk memory.

[0139] The program 410 can be specifically configured to cause the processor 402 to perform the following operations:

[0140] Obtaining basic data of a subject to be detected and scanning protocol data;

[0141] Determining a target position based on the basic data of the subject to be detected and based on a pre-trained positioning model, the target position including at least a scanning start position and a scanning bed height;

[0142] Controlling relative positions of a scanning bed and a gantry according to the target position and the scanning protocol data.

[0143] Obviously, those skilled in the art should understand that the modules or steps of the present application described above can be realized by general computing devices, which can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be realized by program codes executable by computing devices, so that they can be stored in storage devices and executed by computing devices, and in some cases, the steps shown or described can be executed in different orders, or they can be respectively manufactured into individual integrated circuit modules, or multiple modules or steps among them can be manufactured into a single integrated circuit module. Thus, the present application is not limited to any specific combination of hardware and software.

[0144] The above only describes the preferred embodiments of the present application, and is not intended to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A scanning and positioning method, characterized in that, The method is used for positioning slice scanning, including: Acquire basic data of the subject to be tested and scanning protocol data, wherein the basic data of the subject to be tested includes the patient's input data and the scan type extracted from the scanning protocol data; The target location is determined based on the subject's basic data and a pre-trained localization model, and the target location includes the scanning start position and the scanning bed height. The relative positions of the scanning bed and the gantry are controlled according to the target position and the scanning protocol data.

2. The method according to claim 1, characterized in that, The step of controlling the scanning bed movement according to the target position and the scanning protocol data includes: The scanning protocol data is analyzed to obtain the relative positional relationship between the target position and the actual position of the scanning bed; The relative positions of the scanning bed and the gantry are controlled according to the relative positional relationship and the target position.

3. The method according to claim 1, characterized in that, Before acquiring the basic data of the subject to be tested and the scanning protocol data, the method further includes: Obtain scan positioning sample data, which includes a user identity identifier and basic data, scan location, and scan type corresponding to the user identity identifier; Panel data is generated using the basic data, scanning location, and scanning type corresponding to each user identity identifier as the first dimension and the user identity identifier as the second dimension. The neural network model is trained based on the panel data to obtain the localization model.

4. The method according to claim 1, characterized in that, The step of determining the target location based on the basic data of the subject and a pre-trained localization model includes: When a target position adjustment command is detected, a confirmation message is output. If a confirmation response is received, the adjustment instruction is obtained and parsed, and the initial target position is changed to obtain the target position.

5. The method according to claim 4, characterized in that, The method further includes: Extract the changed target location and the scan type and basic data of the subject being tested when the target location was changed; The positioning model is updated based on the changed target location, the scan type of the subject being detected when the target location is changed, and the basic data.

6. The method according to claim 1, characterized in that, The basic data of the subject includes at least one of the subject's height, age, weight parameters, and scan type. Determining the target location based on the basic data of the subject and a pre-trained localization model includes: By inputting at least one of the height, age, weight parameters and scan type of the subject to be tested into the positioning model, the scanning bed height, the start position and end position of the positioning scan are obtained when performing a positioning scan operation corresponding to the scan type on the subject to be tested.

7. The method according to any one of claims 1 to 6, characterized in that, After controlling the scanning bed to move according to the target position and the scanning protocol data, the method further includes: Trigger the execution of a positioning patch scan to obtain the positioning patch data of the person to be tested.

8. A scanning and positioning device, characterized in that, The device is used for positioning piece scanning and includes: The acquisition module is used to acquire the basic data of the subject to be tested and the scanning protocol data, wherein the basic data of the subject to be tested includes the patient's input data and the scan type extracted from the scanning protocol data; The determination module is used to determine the target location based on the basic data of the subject to be tested and a pre-trained positioning model. The target location includes the scanning start position and the scanning bed height. The control module is used to control the relative position of the scanning bed and the gantry according to the target position and the scanning protocol data.

9. A storage medium storing at least one executable instruction that causes a processor to perform an operation corresponding to the scanning and positioning method as described in any one of claims 1-7.

10. A computer device, comprising: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the scanning and positioning method as described in any one of claims 1-7.

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