Control method of medical imaging system and medical imaging system

Abstract

The present application relates to a control method of a medical imaging system and a medical imaging system, which obtains the relative position relationship between the part to be detected of the detection object and the FOV of the current scanning protocol, determines whether the area where the part to be detected is located will produce curling according to the relative position relationship, and outputs a prompt message when curling is produced in the area where the part to be detected is located. The method can adjust the FOV of the scanning protocol in time before scanning, avoiding the need to find artifacts only after the inspection is completed and then adjust them too late, thereby improving the scanning success rate and saving scanning time, so as to efficiently remove curling artifacts in the area where the part to be detected is located.

Description

Technical Field

[0001] The present application relates to the field of medical technology, and in particular to a control method of a medical imaging system and a medical imaging system. Background Art

[0002] Artifacts are often encountered in medical images generated during the scanning process of imaging equipment. For example, curling artifacts are encountered during magnetic resonance (MR) scanning. Curling artifacts cause areas outside the field of view (FOV) to be superimposed on the image within the FOV, resulting in image overlap, which in some cases affects image reading and clinical diagnosis.

[0003] Usually during the scanning process, users have to pay attention to many scanning contents and often ignore some links. For example, the anti-curling parameter settings are not considered in the protocol editing stage before scanning. This will result in the image being found to be aliased outside the FOV after the scan is completed. Then, the anti-curling parameters are modified and the scan is repeated, and the image results are observed again until the image meets the requirements.

[0004] Therefore, in the prior art, there is a problem that the curling artifact cannot be removed efficiently when performing MR scanning. Summary of the invention

[0005] Based on this, it is necessary to provide a control method for a medical imaging system and a medical imaging system that can effectively remove curling artifacts in order to solve the above technical problems.

[0006] In a first aspect, an embodiment of the present application provides a control method for a medical imaging system, the method comprising:

[0007] Obtaining the relative position relationship between the part to be inspected of the inspection object and the FOV of the current scanning protocol;

[0008] According to the relative position relationship, determine whether the area where the part to be detected is located will produce wrinkles;

[0009] If the area where the part to be detected is located will produce wrinkles, a prompt message will be output.

[0010] In one embodiment, the above-mentioned obtaining the relative position relationship between the to-be-detected part of the detection object and the FOV of the current scanning protocol includes:

[0011] Obtain a preset machine learning algorithm model; the machine learning algorithm model is trained based on the FOV of the historical scanning protocol and its corresponding part to be detected;

[0012] The part to be inspected of the inspection object and the FOV of the current scanning protocol are input into the machine learning algorithm model to obtain the relative position relationship.

[0013] In one embodiment, determining whether a region where the detected part is located will produce wrinkles based on the relative position relationship includes:

[0014] Matching the relative position relationship with historical data in a fold database; the historical data includes multiple data groups that will produce folds, each data group includes a historical scanning part, a historical FOV, and a relative position relationship between the historical scanning part and the historical FOV;

[0015] Determine whether the area where the part to be detected is located will produce curling according to the matching result.

[0016] In one embodiment, the prompt information includes an adjustment strategy, and the adjustment strategy is used to adjust the FOV of the current scanning protocol, so that the adjusted current scanning protocol is adapted to the part to be detected of the detection object.

[0017] In one embodiment, the adjustment strategy is determined as follows:

[0018] According to the relative position relationship, the curling range of the area where the part to be detected is located is determined;

[0019] Determine the adjustment strategy based on the range of pleats.

[0020] In one embodiment, the adjustment strategy includes adjusting the position of the FOV and / or the angle of the FOV of the current scanning protocol; or,

[0021] The adjustment strategy includes adjusting the size range of the FOV of the current scanning protocol.

[0022] In one embodiment, before obtaining the relative position relationship between the part to be detected of the detection object and the field of view FOV of the current scanning protocol, the method further includes:

[0023] The detection object is controlled to move to the imaging area of ​​the medical imaging system, and the current scanning protocol set by the user through the graphic user interface of the medical imaging system is received.

[0024] In a second aspect, an embodiment of the present application provides a medical imaging system, the medical imaging system comprising: a display, a processor, and a memory;

[0025] The display has a graphical user interface;

[0026] The processor is used to control the medical imaging system;

[0027] The memory is used to store machine executable instructions executed by the processor when controlling the medical imaging system;

[0028] The processor executes the machine executable instructions to implement the following steps:

[0029] Acquire a positioning image of the detection object;

[0030] Get the current scanning protocol;

[0031] Display the scout image and the FOV of the current scanning protocol on the image user interface;

[0032] Determine the part of the object to be tested;

[0033] Determine whether a wrinkle will be generated in the area where the part to be detected is located when executing the current scanning protocol;

[0034] If the area where the part to be detected is located will produce wrinkles, a prompt message will be displayed on the image user interface.

[0035] In one embodiment, the prompt information includes one or more of the following information:

[0036] The expected location of the curling artifact;

[0037] The location of the interference area corresponding to the curling artifact;

[0038] The recommended adjustment position or size of the FOV;

[0039] The recommended adjustment range for the phase encoding direction in the current scan protocol.

[0040] In one embodiment, the processor executes the machine executable instructions to further implement the following steps:

[0041] The optimization parameters of the current scanning protocol input by the user on the image user interface are received, and the FOV of the scanning protocol optimized according to the optimization parameters is displayed on the image user interface.

[0042] In a third aspect, an embodiment of the present application provides a control device for a medical imaging system, the device comprising:

[0043] An acquisition module, used for acquiring the relative position relationship between the part to be detected of the detection object and the FOV of the current scanning protocol;

[0044] A determination module, used to determine whether the area where the part to be detected is located will produce curling according to the relative position relationship;

[0045] The output module is used to output prompt information if the area where the part to be detected is located will produce wrinkles.

[0046] In a fourth aspect, an embodiment of the present application provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the method steps of any one of the embodiments of the first aspect when executing the computer program.

[0047] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method steps of any one of the embodiments in the first aspect above.

[0048] The embodiment of the present application provides a control method of a medical imaging system and a medical imaging system, which obtains the relative position relationship between the part to be detected of the detection object and the FOV of the current scanning protocol, determines whether the area where the part to be detected is located will produce curling according to the relative position relationship, and outputs a prompt message when curling will be produced in the area where the part to be detected is located. In this method, before the formal scanning is carried out, the relative position relationship between the FOV of the scanning protocol and the part to be detected of the detection object is pre-detected, and according to the relative position relationship between the two, it is determined whether the area where the part to be detected is located will produce curling artifacts, so as to give an early warning, and the FOV of the scanning protocol can be adjusted in time before scanning, so as to avoid discovering the artifacts only after the inspection is completed and then adjusting them too much, thereby improving the scanning success rate and saving scanning time, so as to efficiently remove the curling artifacts in the area where the part to be detected is located. Moreover, the prompt information can be an automatically output adjustment strategy, which is determined by analyzing the relative position relationship between the FOV of the scanning protocol and the part to be detected of the detection object. In this way, the accuracy of the adjustment strategy is improved by combining the analysis with the actual data, so that after adjusting the FOV according to the adjustment strategy, it can be ensured that the current scanning protocol is adapted to the part to be detected of the detection object, thereby further improving the efficiency of removing the curling artifacts in the area where the part to be detected is located. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 An application environment diagram of a control method for a medical imaging system provided in one embodiment;

[0050] Figure 1a is an internal structure diagram of a computer device in one embodiment;

[0051] Figure 2 A schematic flow chart of a control method for a medical imaging system provided in an embodiment;

[0052] Figure 3 A schematic diagram of the FOV range and the part to be detected provided in one embodiment;

[0053] Figure 4 A schematic diagram of a curling artifact generated by a FOV range provided in another embodiment;

[0054] Figure 5 A schematic flow chart of a control method for a medical imaging system provided in another embodiment;

[0055] Figure 6A schematic flow chart of a control method for a medical imaging system provided in another embodiment;

[0056] Figure 7 A schematic flow chart of a control method for a medical imaging system provided in another embodiment;

[0057] Figure 8 A flow chart of a control method for a medical imaging system provided in another embodiment;

[0058] Fig. 9 A flow chart of a control method for a medical imaging system provided in another embodiment;

[0059] Fig.10 A flow chart of a control method for a medical imaging system provided in another embodiment;

[0060] Fig.11 A schematic diagram of an artifact position provided in an embodiment;

[0061] Fig.12 A flow chart of a control method for a medical imaging system provided in one embodiment;

[0062] Fig.13 A schematic diagram of an artifact position and a region of interest provided in an embodiment;

[0063] Fig.14 A schematic diagram of imaging without adjusting the FOV size provided in an embodiment;

[0064] Fig.15 A schematic diagram of an interference area in imaging provided in an embodiment;

[0065] Fig.16 A schematic diagram of imaging after adjusting the FOV size provided in an embodiment;

[0066] Fig.17 An imaging schematic diagram of adjusting the FOV size by oversampling provided in an embodiment;

[0067] Fig.18 is a structural block diagram of a control device for a medical imaging system provided in one embodiment;

[0068] Fig.19 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0069] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0070] The control method of the medical imaging system provided in this application can be applied to Figure 1 In the application environment shown. Wherein, a control system of a medical imaging system is run in the computer device, which is used to control the medical imaging system to perform medical examinations on the diagnosis and treatment object. Wherein, the computer device communicates with the imaging examination device through a network. Wherein, the communication method includes but is not limited to wired or wireless communication. Wherein, the scanner included in the medical imaging system includes but is not limited to a magnetic resonance (Magnetic Resonance, MR) scanning device, a computer tomography (Computed Tomography, CT) device, a positron emission computed tomography (Positron Emission Computed Tomography, PET) scan, or a multimodal system formed by a combination of two or more of the foregoing. Wherein, the computer device can be but is not limited to various personal computers, laptops, smart phones, tablet computers and portable wearable devices.

[0071] The internal structure of the computer equipment can be found in Figure 1a As shown, Figure 1a The processor in the device is used to provide computing and control capabilities. The memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database is used to store relevant data of the control method process of the medical imaging system. The network interface is used to communicate with other external devices through a network connection. When the computer program is executed by the processor, a control method of a medical imaging system is implemented.

[0072] Take MR equipment as an example. During the application process, when the field of view or field of view (FOV) set by the MR equipment is smaller than the human body / model range of the detected object, curling artifacts (also called aliasing artifacts or overlapping artifacts) are common. There is no prompt during the scanning process, and it depends entirely on the user's personal experience to make judgments in advance. However, in actual applications, the scanning process is relatively complicated, and the user has to pay attention to a lot of scanning content. Before the formal scan, the protocol editing of the anti-curling parameters is often ignored. It is not until the scan is completed that it is realized that the anti-curling parameter setting was not considered in the protocol editing stage before the scan. As a result, after the scan is completed, it is found from the results that images outside the FOV are aliased on the image. Then, the anti-curling parameters are modified and the scan is re-scanned, and the image results are observed again until the image meets the requirements, resulting in very low scanning efficiency.

[0073] Based on this, the embodiments of the present application provide a control method for a medical imaging system and a medical imaging system, which can efficiently remove curling artifacts. The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems will be described in detail below through embodiments and in combination with the accompanying drawings. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. It should be noted that the control method of a medical imaging system provided by the present application, its executor is a computer device, wherein its executor can also be a control device of the medical imaging system, wherein the device can be implemented as part or all of the computer device through software, hardware, or a combination of software and hardware.

[0074] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments.

[0075] In one embodiment, Figure 2 As shown, a control method for a medical imaging system is provided. This embodiment involves a computer device determining whether a region where a part to be detected is located will produce curling according to a relative position relationship between a part to be detected of a detection object and a FOV of a current scanning protocol, and outputting prompt information when curling is produced. This embodiment includes the following steps:

[0076] S101, obtaining the relative position relationship between the part to be inspected of the inspection object and the FOV of the current scanning protocol.

[0077] In actual applications, when performing medical imaging scans, specific parts of the subject to be tested are scanned in a targeted manner, where the parts to be tested include but are not limited to the shoulder joint, knee joint, heart, brain, chest, etc. The equipment for performing medical imaging scans is the imaging inspection equipment, and the operation and management of the imaging inspection equipment are controlled by the control equipment, which is also called computer equipment (hereinafter referred to as computer equipment for explanation).

[0078] When performing a specific medical imaging scan, the object to be tested needs to be moved to the imaging area of ​​the imaging inspection device in advance, and then the imaging inspection device is controlled to scan the part to be tested of the object to be tested.

[0079] Taking magnetic resonance examination (MR) as an example, after the object to be detected is moved to the imaging area of ​​the magnetic resonance system, the position data of the part to be detected of the object to be detected can be obtained at this time. For example, the coordinate positions of the pixel points on each boundary of the part to be detected can be detected, and the coordinate positions of these pixel points are used to represent the position data of the part to be detected.

[0080] Optionally, the detection object is controlled to move to an imaging area of ​​the medical imaging system, and a current scanning protocol set by a user through a graphic user interface of the medical imaging system is received; the current scanning protocol corresponds to the field of view FOV.

[0081] Let's continue to take the MR device as an example. When the MR device performs medical imaging scanning, the user needs to set the scanning protocol in the image user interface of the magnetic resonance system in advance. The scanning protocol includes: scanning direction, pulse sequence scanning parameters, receiving coil type, sampling center and other types of related parameters; for example, the FOV parameter can be set in the scanning protocol. The FOV parameter represents the actual scanning range, and the corresponding MR imaging is the actual size of the image area in the frequency encoding direction and the phase encoding direction. Scanning protocols with different parameters are adapted to the parts to be detected under different circumstances. Adaptively editing the parameters in the scanning protocol can ensure that the area where the part to be detected is finally located is scanned under conditions that meet the requirements. Among them, the current scanning protocol set by the user in the image user interface of the magnetic resonance system can be directly input with a specific parameter value, or it can be selected according to the optional items provided by the magnetic resonance system, or it can be the default parameter automatically set by the magnetic resonance system according to the registration information of the detection object, and the embodiment of the present application does not limit this. Optionally, the registration information of the detection object can include a combination of one or more of height, age, gender, weight, and the part to be detected.

[0082] For a computer device, obtaining the FOV parameter of the current scanning protocol may be directly reading the FOV parameter in the current scanning protocol, and then combining the acquired position data of the part to be detected of the detection object to further obtain the relative position relationship between the part to be detected and the FOV of the current scanning protocol.

[0083] See also Figure 3 As shown, Figure 3 A schematic diagram illustrating the position between a part to be detected and the FOV range of a scanning protocol. Figure 3 Take the abdomen as an example. Figure 3 The middle elliptical area represents the abdomen, and the square area represents the range corresponding to the FOV of the current scanning protocol.

[0084] Optionally, when calculating the relative position relationship between the part to be detected and the FOV of the scanning protocol, the part to be detected and the FOV of the scanning protocol can be placed in the same coordinate system and in the same display interface window, or the relative position relationship can be directly determined by a preset neural network model, or it can be calculated by other algorithms, for example, using an AI algorithm, a calculation method derived from big data experience, etc., which is not limited to the embodiments of the present application.

[0085] It should be noted that when determining the relative position relationship, the reference data selected to represent the relative position relationship is not limited. For example, it can be the position of the part to be detected relative to the FOV range, or the FOV range relative to the part to be detected, or the part to be detected and the FOV relative to a third-party reference data.

[0086] S102, determining whether the area where the part to be detected is located will produce wrinkles based on the relative position relationship.

[0087] After obtaining the relative position relationship between the part to be detected and the FOV of the current scanning protocol, it is further determined based on the relative position relationship whether curling artifacts will be generated in the area where the part to be detected is located when scanning the part to be detected of the object with the current scanning protocol.

[0088] Generally, when the FOV range is smaller than the part to be detected, the area where the part to be detected is located will produce curling artifacts. This process is similar to the need to stuff the part to be detected into a FOV smaller than its own range for imaging, which is very likely to cause curling artifacts. For example, Figure 4 The positional relationship between different FOV ranges and the parts to be detected is shown; Figure 4 Take the abdomen + arms as an example. The oval area in the middle represents the abdomen, and the small circles on both sides of the abdomen represent the arms. Figure 4In the figure (a), the FOV range is much larger than the part to be detected. In this case, when scanning the part to be detected, no curling artifacts will be generated in the area where the part is located. Figure 4 The FOV range in (b) is smaller than the part to be detected. When scanning in this case, because the arm is close to the abdomen, the arm will also be excited by the RF pulse while the abdomen is excited by the RF pulse. The arm area in (b) will be folded into the dotted line range in (c), resulting in a curling artifact in the abdominal area.

[0089] Among them, when determining whether the area where the part to be detected is located will produce curling, the preset neural network model can also be used to take the relative position relationship between the two as input, and the output result obtained will directly determine whether there will be curling artifacts. Alternatively, it is determined in advance based on empirical values ​​whether there are curling artifacts in the area where the part to be detected is located corresponding to different relative position relationships, and then based on these corresponding relationships and the relative position relationship between the part to be detected and the FOV of the current scanning protocol, it is determined whether curling artifacts will be produced in the area where the part to be detected is located. The embodiment of the present application does not limit the specific determination method, as long as it is determined based on the relative position relationship between the two.

[0090] S103: If the area where the part to be detected is located will produce wrinkles, output a prompt message.

[0091] In one implementation, the prompt information may be an automatically generated adjustment strategy; the adjustment strategy is used to adjust the FOV of the current scanning protocol, and the adjusted current scanning protocol is adapted to the part to be detected of the detection object.

[0092] If it is determined in the above steps that the area where the part to be detected is located will produce folds, then an adjustment strategy is output, and the adjustment strategy is used to adjust the FOV of the current scanning protocol so that the adjusted current scanning protocol is adapted to the part to be detected of the object to be detected. Adaptation means that the FOV range of the adjusted scanning protocol completely covers the part to be detected, and the FOV range will not be too much larger than the part to be detected, nor will it be smaller than the part to be detected, and the two match. The adjusted current scanning protocol is adapted to the part to be detected of the object to be detected, so that the FOV of the adjusted current scanning protocol scans the area where the part to be detected is located without folding artifacts (corresponding to MR), or the FOV of the adjusted current scanning protocol scans the area where the part to be detected is located without truncation (corresponding to CT).

[0093] Optionally, the adjustment strategy includes adjusting the position of the FOV and / or the angle of the FOV of the current scanning protocol; or, the adjustment strategy includes adjusting the size range of the FOV of the current scanning protocol.

[0094] In order to adapt the FOV range of the current scanning protocol to the part to be detected, any one of the parameters of the position, angle, and size range of the FOV can be adjusted. This is equivalent to adjusting the FOV range by translation, rotation, and stretching. The FOV range can also be adjusted by increasing oversampling so that the adjusted range of the current scanning protocol is adapted to the part to be detected.

[0095] Among them, the method of outputting the adjustment strategy can be to pop up a warning box, and indicate the specific adjustment method in the warning box. Among them, the adjustment strategy can be expressed in text form, indicating the specific value to which the FOV of the current scanning protocol needs to be adjusted, or it can be in the form of numbers, agreed special characters, etc., which are not limited in this embodiment of the present application. Optionally, after outputting the warning box of the adjustment strategy, if the user accepts that the area where the current part to be detected is located will produce curling artifacts, then the user can choose to ignore the prompt and continue the scan; or choose to adjust the current scanning protocol according to the parameters recommended in the adjustment strategy, so that no curling artifacts are produced in the area where the part to be detected is located. Furthermore, when outputting the adjustment strategy, a voice method can be added to increase the flexibility of the output method of the adjustment strategy.

[0096] Optionally, after outputting the adjustment strategy, the computer device can directly control a preset automatic program according to the content of the adjustment strategy, and the automatic program is used to automatically correct the parameter value of the FOV in the current scanning protocol. Using the pre-configured automatic program to execute the adjustment strategy can improve the efficiency and accuracy of the current scanning protocol adjustment.

[0097] Optionally, in one embodiment, the prompt information may also be used to prompt the relevant information of the curling artifact, or to prompt the specific method of the suggested adjustment, for example, the expected position of the curling artifact, the position of the interference area corresponding to the curling artifact, the recommended adjustment position or size of the FOV, the recommended adjustment range of the phase encoding direction in the current scanning protocol, etc. It can be understood that the content displayed in the prompt information is part or all of the information in the adjustment strategy. For the prompt information, please refer to the description in the subsequent embodiments. The embodiments of the present application do not limit the prompt method, prompt content, and prompt type of the prompt information.

[0098] The control method of the medical imaging system provided in the embodiment of the present application obtains the relative position relationship between the part to be detected of the detection object and the FOV of the current scanning protocol, determines whether the area where the part to be detected is located will produce curling according to the relative position relationship, and outputs a prompt message when curling will be produced in the area where the part to be detected is located. The prompt information can provide an early warning to the operator before scanning, so as to find out the problems with the current scanning protocol as early as possible. In this method, before the formal scanning, the relative position relationship between the FOV of the scanning protocol and the part to be detected of the detection object is pre-detected, and according to the relative position relationship between the two, it is determined whether the area where the part to be detected is located will produce curling artifacts, so as to give an early warning and output a prompt message, so that the FOV of the scanning protocol can be adjusted in time before scanning, so as to avoid discovering the artifacts only after the inspection is completed and then adjusting them too much, thereby improving the scanning success rate and saving scanning time, so as to efficiently remove the curling artifacts in the area where the part to be detected is located. Moreover, the output prompt information is determined based on the analysis of the relative position relationship between the FOV of the scanning protocol and the part to be detected of the detection object. In this way, the accuracy of the prompt information is improved by combining the analysis with the actual data, so that after adjusting the FOV according to the prompt information, it can be ensured that the current scanning protocol is compatible with the part to be detected of the detection object, thereby further improving the efficiency of removing the curling artifacts in the area where the part to be detected is located.

[0099] Based on the above embodiment, the corresponding relationship between the relative position relationship and whether there is a curling artifact in the area where the part to be detected is located is taken as an example to illustrate the process of determining whether curling will occur in the area where the part to be detected is located based on the relative position relationship.

[0100] In one embodiment, the relative position relationship between the part to be detected of the detection object and the FOV of the current scanning protocol can indicate whether the part to be detected is within the FOV of the current scanning protocol, outside the FOV of the current scanning protocol, whether there are other tissues within the FOV of the current scanning protocol that are jointly excited by the part to be detected, etc.

[0101] like Figure 5 As shown, in one embodiment, the above S102 includes the following steps:

[0102] S201, matching the relative position relationship with the historical data in the fold database; the historical data includes multiple data groups that will produce folds, each data group includes a historical scanning part, a historical FOV, and a relative position relationship between the historical scanning part and the historical FOV.

[0103] According to big data analysis or AI algorithms, when it is determined that folds will be generated in the area where the part to be detected is located, the relative position relationship between the corresponding part to be detected and the FOV of the scanning protocol is determined, and the corresponding relationship between these relative position relationships and whether folds will be generated in the area where the part to be detected is located is determined, and then stored in the fold database. When used later, the computer device matches the relative position relationship between the part to be detected of the detected object and the FOV of the current scanning protocol with the relative position relationship in each corresponding relationship stored in the fold database.

[0104] Among them, the historical data stored in the fold database may be a list of relative position relationships between multiple parts to be detected and the FOV of the scanning protocol, or a list of ranges of relative position relationships that will cause fold artifacts in the area where the parts to be detected are located. The embodiments of the present application are not limited to this.

[0105] Of course, the historical data in the fold database can be updated in real time in combination with the newly generated data in actual clinical practice to improve the accuracy of the matching results.

[0106] S202, determining whether the area where the part to be detected is located will produce curling according to the matching result.

[0107] Regardless of whether the relative position relationship stored in the curling database is a range, or a list of multiple relative position relationships that will cause curling artifacts in the area where the part to be detected is located, when matching the current relative position relationship with the relative position relationship in the curling database, the similarity can be matched, and based on the similarity matching result, it can be determined whether the current relative position relationship will cause curling in the area where the part to be detected is located.

[0108] For example, if a variety of relative position relationships are listed one by one in the fold database, a similarity preset value can be defined. As long as there is any matching similarity greater than or equal to the preset value, it means that the current relative position relationship will cause folds to occur in the area where the part to be detected is located.

[0109] For another example, if the curling database stores the range of relative positional relationships, another similarity preset value can be defined to calculate the similarity between the current relative positional relationship and the mean value determined by the range in the curling database. If the similarity is less than or equal to the preset value, it is determined that the current relative positional relationship will cause curling artifacts to be generated in the area where the part to be detected is located. In this case, it can also be determined by directly detecting whether the current relative positional relationship falls within the range of relative positional relationships stored in the curling database, that is, if it falls within the range, it is determined that the current relative positional relationship will cause curling artifacts to be generated in the area where the part to be detected is located.

[0110] In the embodiment of the present application, the relative position relationship is matched with the historical data in the curling database; the historical data is the relative position relationship between the historical scanning part and the historical FOV when curling is generated in the historical scanning result, and when the similarity after matching satisfies the set relationship, it is determined that the area where the part to be detected is located will produce curling. In this method, the relative position relationship currently obtained is matched with the relative position relationship stored in the curling database that will cause the area where the part to be detected is located to produce curling artifacts, and the actual calculated similarity is used as the judgment basis, and the result is judged from a quantitative perspective, so that the judgment result is more accurate.

[0111] After determining the relative position relationship between the FOV of the current scanning protocol and the part to be detected, it is necessary to determine an adjustment strategy based on the relative position relationship. The following provides an embodiment in which the prompt information is an automatically generated adjustment strategy, and the specific process of determining the adjustment strategy is described, such as Figure 6 As shown, the above S103 includes the following steps:

[0112] S301, determining the curling range of the area where the to-be-detected part is located according to the relative position relationship.

[0113] This embodiment is described by dividing the curling generated in the area where the detected part is located into ranges, and the curling range refers to different curling degrees or different types of curling.

[0114] According to the acquired relative position relationship, the curl range corresponding to the relative position relationship may be acquired from the curl database, or the corresponding curl range may be analyzed by a preset algorithm model. This embodiment of the present application does not limit this.

[0115] Assume that the curling database mentioned in the above embodiment further stores the curling range corresponding to each relative position relationship when storing the corresponding relationship, that is, different relative position relationships correspond to different curling ranges. Of course, different relative position relationship ranges may correspond to different curling ranges, and the embodiment of the present application does not limit this. Then, the computer device may determine the corresponding curling range in the curling database according to the relative position relationship. Furthermore, after the computer device determines in the curling database whether the relative position relationship will cause the area where the part to be detected is located to produce a curling artifact, the corresponding curling range is also obtained.

[0116] S302, determining an adjustment strategy according to the curling range.

[0117] After the fold range is determined, the corresponding adjustment strategy is determined according to the fold range. The adjustment strategy is a strategy used to adjust the current scanning protocol, so it can be a data output adjustment strategy that is directly adjusted according to actual needs, or it can be determined according to the fold range of the fold that will be caused by the current scanning protocol. The adjustment strategy that needs to be adjusted. For example, different fold ranges represent different fold degrees, and an adjustment strategy can be defined for a fold degree. Then, after the fold range is determined, the adjustment strategy defined by the fold range is used as the final adjustment strategy.

[0118] The adjustment strategy includes adjusting the position of the FOV and / or the angle of the FOV of the current scanning protocol, and adjusting the size range of the FOV of the current scanning protocol. In advance, the amplitude and direction of the adjustment of the position, angle or size range of the FOV need to be determined for different curling ranges. In this case, the adjustment strategy determined according to the curling range corresponding to the relative position relationship is the amplitude and direction of the adjustment of the position, angle or size range of the FOV preset under the curling range.

[0119] In this embodiment, by dividing the curling artifacts caused by different relative position relationships into different curling ranges, when determining the adjustment strategy, the final adjustment strategy is determined according to the different curling ranges. In this way, the adjustment strategy can be quickly determined to achieve the effect of efficiently removing the curling artifacts, thereby improving the image imaging and scanning effect.

[0120] The present application also provides an embodiment to illustrate the process of obtaining the relative position relationship between the to-be-detected part of the detection object and the FOV of the current scanning protocol. Figure 7 This embodiment includes the following steps:

[0121] S401, obtaining a preset machine learning algorithm model; the machine learning algorithm model is trained based on the FOV of the historical scanning protocol and its corresponding part to be detected.

[0122] Pre-train a machine learning algorithm model, which is trained based on the FOV of the historical scanning protocol and its corresponding part to be detected. That is, when training the machine learning algorithm model, first obtain the training sample data from the historical data, wherein the training sample data includes the FOV of the historical scanning protocol and its corresponding part to be detected. Then, train the initial machine algorithm model according to the training sample data, and monitor whether the preset convergence conditions are met at any time during the training process. If the convergence conditions are met, it is determined that the machine algorithm model training is completed, and the final machine learning algorithm model is obtained. Among them, when obtaining the training sample data, data of different parts to be detected can be obtained, and different parts to be detected refer to parts to be detected in different ranges or parts to be detected in different parts. The training sample data can also be stretched, cropped, flipped, translated, etc. to increase the diversity of the training sample data, so that the trained machine learning algorithm model is more accurate.

[0123] S402, inputting the part to be inspected of the inspection object and the FOV of the current scanning protocol into the machine learning algorithm model to obtain the relative position relationship.

[0124] Based on the pre-trained machine learning algorithm model, the part to be inspected of the inspection object and the FOV of the current scanning protocol are input into the machine learning algorithm model to obtain the corresponding relative position relationship.

[0125] In this embodiment, the part to be detected of the detection object and the FOV of the current scanning protocol are directly input into the machine learning algorithm model through the pre-trained machine learning algorithm model to obtain the relative position relationship, making the method of obtaining the relative position relationship faster and simpler. Moreover, since the machine learning algorithm model is trained based on the training sample data obtained from the historical data, the machine learning algorithm model trained with the historical real data can ensure the accuracy of the relative position relationship it obtains.

[0126] In addition, if Figure 8 As shown, a control method for a medical imaging system is provided. This embodiment takes a magnetic resonance system as an example. The embodiment includes:

[0127] S501, controlling the detection object to move to the imaging area of ​​the magnetic resonance system, and receiving the current scanning protocol set by the user through the image user interface of the magnetic resonance system; the current scanning protocol corresponds to the FOV.

[0128] S502, obtaining a preset machine learning algorithm model; the machine learning algorithm model is trained based on the FOV of the historical scanning protocol and its corresponding part to be detected.

[0129] S503: Input the part to be inspected of the inspection object and the FOV of the current scanning protocol into the machine learning algorithm model to obtain the relative position relationship.

[0130] S504, matching the relative position relationship with the historical data in the fold database; the historical data is the relative position relationship between the historical FOV and the historical scanning part and the historical FOV when the fold is generated by the historical scanning result.

[0131] S505: Determine, based on the matching result, that the area where the part to be detected is located will produce wrinkles.

[0132] S506: Determine the curling range of the area where the to-be-detected part is located according to the relative position relationship.

[0133] S507: Determine an adjustment strategy according to the fold range.

[0134] S508 , adjusting the FOV of the current scanning protocol according to the adjustment strategy, so that the adjusted current scanning protocol is adapted to the part to be inspected of the inspection object.

[0135] The implementation principle and technical effect of each step in the control method of the medical imaging system provided in this embodiment are similar to those of the previous control method embodiments of the medical imaging system, and will not be repeated here. The implementation method of each step in this embodiment is only an example, and the implementation method is not limited. The order of each step can be adjusted in actual application as long as the purpose of each step can be achieved.

[0136] In addition, in order to solve the problem that the scanned image is easy to alias the image outside the FOV, the embodiment of the present application also provides a medical imaging system, which is suitable for scanning medical images; the medical imaging system includes: a display, a processor and a memory; wherein the display has a graphic user interface; the processor is used to control the medical imaging system; the memory is used to store machine executable instructions executed by the processor when controlling the medical imaging system; wherein, Fig. 9 As shown, the processor implements the following steps when executing the machine executable instructions:

[0137] S601, obtaining a positioning image of the detection object.

[0138] S602: Obtain the current scanning protocol.

[0139] S603: Display the positioning image and the FOV of the current scanning protocol on the image user interface.

[0140] S604: Determine the part of the object to be inspected.

[0141] S605: Determine whether a curl will be generated in the area where the part to be detected is located when executing the current scanning protocol.

[0142] S606: If the area where the part to be detected is located will produce wrinkles, a prompt message is displayed on the image user interface.

[0143] Specifically, the processor first obtains the positioning image of the detection object and the current scanning protocol (i.e., the protocol to be scanned), and displays the positioning image and the FOV corresponding to the current scanning protocol on the image user interface of the display. After display, the processor determines the part to be detected of the detection object, and automatically determines whether the execution of the current scanning protocol will cause the area where the part to be detected is located to produce a curling artifact based on the specific information of the part to be detected and the current scanning protocol. If it is determined whether the execution of the previous scanning protocol will cause the area where the part to be detected is located to produce a curling artifact, then the processor responds to the conclusion and displays a prompt message on the image user interface of the display.

[0144] Among them, the prompt information may include: the expected position of the curling artifact, the position of the interference area corresponding to the curling artifact, the adjusted position or size of the FOV, the recommended adjustment range of the phase encoding direction in the current scanning protocol, or one or more combinations of the adjustment suggestions of other scanning parameters, and the embodiments of the present application are not limited to this. Of course, the prompt information can also be a simple warning mark, for example, a pop-up warning mark, a prompt beep, etc. It is understandable that when it is automatically determined that the execution of the current scanning protocol will not cause the area of ​​the to-be-detected part to be detected to produce a curling artifact, a prompt information can also be generated and displayed. The prompt information in this case can be "can be executed", "please continue scanning", etc., indicating that the user is scanning normally, or it can be a green mark, indicating that everything is normal. The embodiments of the present application do not limit the prompt method, prompt content, and prompt type of the prompt information.

[0145] In one embodiment, based on the above medical imaging system, an embodiment is also provided. Fig.10 As shown, in this embodiment, when the processor controls the medical imaging system, the machine executable instructions executed by the processor can implement the following steps:

[0146] S701, obtaining a positioning image of the detection object.

[0147] S702: Obtain the current scanning protocol.

[0148] S703: Display the positioning image and the FOV of the current scanning protocol on the image user interface.

[0149] S704: Determine the part of the object to be inspected.

[0150] S705: Display the estimated position of the curling artifact on the image user interface.

[0151] S706: Determine whether the estimated position of the curling artifact is within the FOV corresponding to the current scanning protocol.

[0152] S707: If the estimated position of the curling artifact is within the FOV corresponding to the current scanning protocol, adjust the current scanning protocol; otherwise, use the current scanning protocol to perform scanning on the detection object.

[0153] Specifically, the processor first obtains the positioning image of the detection object and the current scanning protocol (i.e., the protocol to be scanned), and displays the positioning image and the FOV corresponding to the current scanning protocol on the image user interface of the display, and determines the part to be detected of the detection object in the positioning image. After that, the processor displays the estimated position of the curling artifact on the image user interface, and determines whether the estimated position of the curling artifact is within the FOV corresponding to the current scanning protocol. If the estimated position of the curling artifact is within the FOV corresponding to the current scanning protocol, the current scanning protocol is adjusted; otherwise, the current scanning protocol is used to perform scanning on the detection object.

[0154] For example, please refer to Fig.11 As shown, the positioning image of the detection object includes the part to be detected and the interference area (non-to-be-detected part A and non-to-be-detected part B), and the image user interface shows that the expected positions of the images generated by the non-to-be-detected part A and the non-to-be-detected part B are A' and B' respectively, and A' is in the FOV but does not overlap with the part to be detected, and B' is in the FOV and overlaps with the part to be detected (in this case, folds will be generated). The computer device can adjust the size, angle, etc. of the FOV corresponding to the current scanning protocol according to the expected position of the displayed fold artifact (A' and B'), so that the position of the part to be detected in the FOV corresponding to the adjusted current scanning protocol does not have a fold artifact, or the position of the part to be detected in the FOV corresponding to the adjusted current scanning protocol does not overlap with the expected position of the non-to-be-detected part.

[0155] In another embodiment, based on the above medical imaging system, an embodiment is also provided, such as Fig.12 As shown, in this embodiment, when the processor controls the medical imaging system, the machine executable instructions executed by the processor can implement the following steps:

[0156] S801, obtaining a positioning image of the detection object.

[0157] S802: Obtain the current scanning protocol.

[0158] S803: Display the positioning image and the FOV of the current scanning protocol on the image user interface.

[0159] S804: Determine the part of the object to be inspected.

[0160] S805: Display the estimated position of the curling artifact on the image user interface.

[0161] S806: Determine whether the estimated position of the curling artifact is within the FOV corresponding to the current scanning protocol.

[0162] S807 . In response to the estimated position of the curling artifact not being within the FOV corresponding to the current scanning protocol, scanning the detection object using the current scanning protocol.

[0163] S808: In response to the predicted position of the curling artifact being within the FOV corresponding to the current scanning protocol, determine whether the predicted position of the curling artifact falls within the position of the region of interest.

[0164] S809: If the estimated position of the curling artifact does not fall within the position of the region of interest, the object to be detected is scanned using the current scanning protocol.

[0165] S810: If the estimated position of the curling artifact falls within the position of the region of interest, adjust the current scanning protocol.

[0166] Specifically, the processor first obtains the positioning image of the detection object and the current scanning protocol (i.e., the protocol to be scanned), and displays the positioning image and the FOV corresponding to the current scanning protocol on the image user interface of the display, and determines the part to be detected of the detection object in the positioning image. After that, the processor displays the expected position of the fold artifact on the image user interface, and determines whether the expected position of the fold artifact is within the FOV corresponding to the current scanning protocol. If the expected position of the fold artifact is not within the FOV corresponding to the current scanning protocol, the current scanning protocol is used to scan the detection object. However, if the expected position of the fold artifact is within the FOV corresponding to the current scanning protocol, it is further determined whether the expected position of the fold artifact falls within the position of the region of interest. If the judgment result is that the expected position of the fold artifact does not fall within the position of the region of interest, then the current scanning protocol is used to scan the detection object. Otherwise, if the judgment result is that the expected position of the fold artifact falls within the position of the region of interest, the current scanning protocol is adjusted.

[0167] For example, see Fig.13 As shown, the positioning image of the detection object includes the part to be detected and the interference area (parts A and B not to be detected). The image user interface shows that the estimated positions of the images generated by the non-detected parts A and B are A' and B' respectively, and A' is within the FOV but does not overlap with the part to be detected, and B' is within the FOV and overlaps with the part to be detected (in this case, folds will be generated). The computer device determines the position of a region of interest in the positioning image (C in the figure), and further determines whether the estimated positions of the images generated by the non-detected parts A and B (A' and B') will fall into the position of the region of interest. If they fall into the position of the region of interest, then the current scanning protocol needs to be adjusted. If they do not fall into the position of the region of interest, the current scanning protocol can be used to scan the detection object.

[0168] The following is a schematic diagram of an actual lower abdomen scan to illustrate the process of performing a lower abdomen scan without adjusting the FOV using the prior art, and performing a lower abdomen scan with adjusting the FOV provided in an embodiment of the present application.

[0169] See also Fig.14 As shown, Fig.14 This is a schematic diagram of directly performing scanning imaging by using the existing method to scan the lower abdomen without adjusting the FOV. Fig.14 From left to right in (a) are the coronal view and transverse view of the positioning image of the detection object. Fig.14 The arrow in (a) indicates the phase encoding direction (the arrows in subsequent figures have the same meaning and are not repeated here), and the area marked by the circle is the arm interference area. Fig.14 Middle (b) shows that after scanning, there are multiple curling artifacts on the outer edges of the arms and thighs on both sides of the lower abdomen, as indicated by the arrows in (b).

[0170] The interfering areas that produce curling artifacts when scanning the lower abdomen can be seen in Fig.15 In actual application, the interference area can be displayed on the image user interface of the display. Specifically, after the processor obtains the positioning image and the current scanning protocol of the detection object, the positioning image and the FOV corresponding to the current scanning protocol are displayed on the image user interface. At the same time, the interference area that will produce the folding artifact is also displayed as prompt information (the boxes M and N in the figure) to facilitate the adjustment of the current scanning protocol according to the position of the interference area. Fig.16 , Fig.16 It is indicated that after the FOV size corresponding to the current scanning protocol is adjusted according to the interference area, the FOV corresponding to the adjusted scanning protocol includes the part to be detected and the interference area.

[0171] In one possible implementation, the range of the adjusted current scanning protocol can be adapted to the part to be detected by increasing oversampling. Fig.17 , which is a schematic diagram of setting oversampling along the phase encoding direction (the direction in which the FOV is set to be smaller) and displaying only the part to be detected after reconstructing the acquired magnetic resonance signal.

[0172] The implementation principle and technical effect of each step performed by the processor provided in this embodiment when controlling the medical imaging system are similar to those of the previous control method embodiments of the medical imaging system, and will not be repeated here. The implementation method of each step in this embodiment is only an example, and the implementation method is not limited. The order of each step can be adjusted in actual application as long as the purpose of each step can be achieved.

[0173] It should be understood that, although the various steps in the flow chart of the above-described embodiment are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the above-described embodiment may include a plurality of steps or a plurality of stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the steps or stages in other steps.

[0174] In one embodiment, Fig.18 As shown, a control device for a medical imaging system is provided, the device comprising: a receiving module 10, a determining module 11 and an output module 12, wherein:

[0175] An acquisition module 10 is used to acquire the relative position relationship between the part to be detected of the detection object and the FOV of the current scanning protocol;

[0176] A determination module 11 is used to determine whether a curling will occur in the area where the part to be detected is located according to the relative position relationship;

[0177] The output module 12 is used to output prompt information if the area where the part to be detected is located will produce wrinkles.

[0178] In one embodiment, the acquisition module 10 includes:

[0179] A model acquisition unit, used to acquire a preset machine learning algorithm model; the machine learning algorithm model is trained based on the FOV of the historical scanning protocol and its corresponding part to be detected;

[0180] The input unit is used to input the part to be detected of the detection object and the FOV of the current scanning protocol into the machine learning algorithm model to obtain the relative position relationship.

[0181] In one embodiment, the determination module 11 includes:

[0182] A matching unit, used for matching the relative position relationship with the historical data in the fold database; the historical data will generate multiple data groups of the fold, each data group including the historical scanning part, the historical FOV and the relative position relationship between the historical scanning part and the historical FOV;

[0183] The result determination unit is used to determine whether the area where the part to be detected is located will produce curling according to the matching result.

[0184] In one embodiment, the prompt information includes an adjustment strategy, and the adjustment strategy is used to adjust the FOV of the current scanning protocol, so that the adjusted current scanning protocol is adapted to the part to be detected of the detection object.

[0185] In one embodiment, the adjustment strategy is determined as follows:

[0186] According to the relative position relationship, the curling range of the area where the part to be detected is located is determined; and the adjustment strategy is determined according to the curling range.

[0187] In one embodiment, the adjustment strategy includes adjusting the position of the FOV and / or the angle of the FOV of the current scanning protocol; or, the adjustment strategy includes adjusting the size range of the FOV of the current scanning protocol.

[0188] In one embodiment, the device further includes: a pre-processing module, which is used to control the detection object to move to the imaging area of ​​the medical image imaging system, and receive the current scanning protocol set by the user through the image user interface of the medical image imaging system.

[0189] For the specific definition of the control device of the medical imaging system, please refer to the definition of the control method of the medical imaging system above, which will not be repeated here. Each module in the control device of the medical imaging system can be implemented in whole or in part by software, hardware and a combination thereof. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0190] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Fig.10 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a control method for a medical imaging system is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0191] Those skilled in the art will understand that Fig.10 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0192] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0193] Obtaining the relative position relationship between the part to be inspected of the inspection object and the FOV of the current scanning protocol;

[0194] According to the relative position relationship, determine whether the area where the part to be detected is located will produce wrinkles;

[0195] If the area where the part to be detected is located will produce wrinkles, a prompt message will be output.

[0196] In one embodiment, the processor implements the following steps when executing the computer program:

[0197] Obtain a preset machine learning algorithm model; the machine learning algorithm model is trained based on the FOV of the historical scanning protocol and its corresponding part to be detected;

[0198] The part to be inspected of the inspection object and the FOV of the current scanning protocol are input into the machine learning algorithm model to obtain the relative position relationship.

[0199] In one embodiment, the processor implements the following steps when executing the computer program:

[0200] Matching the relative position relationship with historical data in a fold database; the historical data includes multiple data groups that will produce folds, each data group includes a relative position relationship between a historical scanning part and a historical FOV;

[0201] Determine whether the area where the part to be detected is located will produce curling according to the matching result.

[0202] In one embodiment, the prompt information includes an adjustment strategy, and the adjustment strategy is used to adjust the FOV of the current scanning protocol, so that the adjusted current scanning protocol is adapted to the part to be detected of the detection object.

[0203] In one embodiment, the adjustment strategy is determined as follows:

[0204] According to the relative position relationship, the curling range of the area where the part to be detected is located is determined;

[0205] Determine the adjustment strategy based on the range of pleats.

[0206] In one embodiment, the adjustment strategy includes adjusting the position of the FOV and / or the angle of the FOV of the current scanning protocol; or, the adjustment strategy includes adjusting the size range of the FOV of the current scanning protocol.

[0207] In one embodiment, the processor implements the following steps when executing the computer program:

[0208] The detection object is controlled to move to the imaging area of ​​the medical imaging system, and the current scanning protocol set by the user through the graphic user interface of the medical imaging system is received.

[0209] The above embodiment provides a computer device, whose implementation principle and technical effect are similar to those of the above method embodiment, and will not be repeated here.

[0210] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0211] Obtaining the relative position relationship between the part to be inspected of the inspection object and the FOV of the current scanning protocol;

[0212] According to the relative position relationship, determine whether the area where the part to be detected is located will produce wrinkles;

[0213] If the area where the part to be detected is located will produce wrinkles, a prompt message will be output.

[0214] In one embodiment, the computer program, when executed by a processor, implements the following steps:

[0215] Obtain a preset machine learning algorithm model; the machine learning algorithm model is trained based on the FOV of the historical scanning protocol and its corresponding part to be detected;

[0216] The part to be inspected of the inspection object and the FOV of the current scanning protocol are input into the machine learning algorithm model to obtain the relative position relationship.

[0217] In one embodiment, the computer program, when executed by a processor, implements the following steps:

[0218] Matching the relative position relationship with historical data in a fold database; the historical data includes multiple data groups that will produce folds, each data group includes a relative position relationship between a historical scanning part and a historical FOV;

[0219] Determine whether the area where the part to be detected is located will produce curling according to the matching result.

[0220] In one embodiment, the prompt information includes an adjustment strategy, and the adjustment strategy is used to adjust the FOV of the current scanning protocol, so that the adjusted current scanning protocol is adapted to the part to be detected of the detection object.

[0221] In one embodiment, the adjustment strategy is determined as follows:

[0222] According to the relative position relationship, the curling range of the area where the part to be detected is located is determined;

[0223] Determine the adjustment strategy based on the range of pleats.

[0224] In one embodiment, the adjustment strategy includes adjusting the position of the FOV and / or the angle of the FOV of the current scanning protocol; or, the adjustment strategy includes adjusting the size range of the FOV of the current scanning protocol.

[0225] In one embodiment, the computer program, when executed by a processor, implements the following steps:

[0226] The detection object is controlled to move to the imaging area of ​​the medical imaging system, and the current scanning protocol set by the user through the graphic user interface of the medical imaging system is received.

[0227] The above embodiment provides a computer-readable storage medium, whose implementation principle and technical effect are similar to those of the above method embodiment, and will not be repeated here.

[0228] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0229] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0230] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A control method for a medical imaging system, characterized in that: The method comprises: Obtaining a preset machine learning algorithm model; the machine learning algorithm model is trained based on the FOV of the historical scanning protocol and its corresponding part to be detected; Inputting the part to be detected of the detection object and the FOV of the current scanning protocol into the machine learning algorithm model to obtain the relative position relationship between the part to be detected of the detection object and the FOV of the current scanning protocol; Determining whether the area where the part to be detected is located will produce wrinkles according to the relative position relationship; If the area where the part to be detected is located will produce wrinkles, a prompt message is output.

2. The method according to claim 1, characterized in that Determining whether a wrinkle will occur in the area where the part to be detected is located according to the relative position relationship includes: Matching the relative position relationship with historical data in a fold database; the historical data includes multiple data groups that will produce folds, each data group includes a historical scanning part, a historical FOV, and a relative position relationship between the historical scanning part and the historical FOV; It is determined whether the area where the part to be detected is located will produce curling according to the matching result.

3. The method according to claim 1, characterized in that The prompt information includes an adjustment strategy, and the adjustment strategy is used to adjust the FOV of the current scanning protocol, so that the adjusted current scanning protocol is adapted to the part to be detected of the detection object.

4. The method according to claim 3, characterized in that The adjustment strategy is determined by: determining the curling range of the area where the to-be-detected part is located according to the relative position relationship; The adjustment strategy is determined according to the curling range.

5. The method according to claim 3, characterized in that: The adjustment strategy includes adjusting the position of the FOV and / or the angle of the FOV of the current scanning protocol; or The adjustment strategy includes adjusting the size range of the FOV of the current scanning protocol.

6. The method according to claim 1, characterized in that Before acquiring the relative position relationship between the part to be detected of the detection object and the FOV of the current scanning protocol, the method further includes: The detection object is controlled to move to an imaging area of ​​a medical imaging system, and the current scanning protocol set by a user through a graphic user interface of the medical imaging system is received.

7. A control device for a medical imaging system, characterized in that: The device comprises: an acquisition module, a determination module and an output module; The acquisition module is used to acquire a preset machine learning algorithm model, input the part to be detected of the detection object and the FOV of the current scanning protocol into the machine learning algorithm model, and obtain the relative position relationship between the part to be detected of the detection object and the FOV of the current scanning protocol; the machine learning algorithm model is trained based on the FOV of the historical scanning protocol and its corresponding part to be detected; The determination module is used to determine whether the area where the part to be detected is located will produce wrinkles according to the relative position relationship; The output module is used to output prompt information if the area where the part to be detected is located will produce wrinkles.

8. A medical imaging system, characterized in that: The medical imaging system comprises: a display, a processor and a memory; The display has a graphical user interface; The processor is used to control the medical imaging system; The memory is used to store machine executable instructions executed by the processor when controlling the medical imaging system; The processor executes the machine executable instructions to implement the following steps: Acquire a positioning image of the detection object; Get the current scanning protocol; Displaying the scout image and the FOV of the current scanning protocol on the image user interface; Determining a part of the object to be detected; Obtaining a preset machine learning algorithm model; the machine learning algorithm model is trained based on the FOV of the historical scanning protocol and its corresponding part to be detected; Inputting the part to be detected of the detection object and the FOV of the current scanning protocol into the machine learning algorithm model to obtain the relative position relationship between the part to be detected of the detection object and the FOV of the current scanning protocol; Determining, based on the relative position relationship, whether a wrinkle will be generated in the area where the part to be detected is located when executing the current scanning protocol; If the area where the part to be detected is located will produce wrinkles, a prompt message is displayed on the image user interface.

9. The medical imaging system according to claim 8, characterized in that: The prompt information includes one or more of the following information: an estimated location of the curling artifact; The position of the interference area corresponding to the curling artifact; a proposed adjusted position or size of the FOV; The recommended adjustment range of the phase encoding direction in the current scanning protocol.

10. The medical imaging system according to claim 9, characterized in that: The processor executes the machine executable instructions to further implement the following steps: The optimization parameters of the current scanning protocol input by the user on the image user interface are received, and the FOV of the scanning protocol optimized according to the optimization parameters is displayed on the image user interface.

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