Method, device and system for acquiring use information of medical imaging equipment

Abstract

The embodiment of the invention provides a method, device and system for obtaining use information of medical imaging equipment, and the method comprises the steps: obtaining an image sequence which is generated by the medical imaging equipment and comprises a plurality of images in a time dimension; performing text recognition on a specific area of the image to generate text information; and generating use information of the medical imaging equipment according to the text information.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of medical equipment technology, and in particular, to a method, device, and system for obtaining usage information of a medical imaging device. Background Art

[0002] Medical institutions usually use a large number of different types of medical imaging equipment, such as ultrasound imaging equipment (Ultrasound), computed tomography equipment (CT), magnetic resonance imaging equipment (MRI), positron emission tomography (PET), etc. Various medical imaging equipment may include different models of medical imaging equipment provided by different equipment manufacturers. Medical institutions have the need to manage these large numbers of medical imaging equipment, such as understanding the use of equipment, predictive maintenance, and improving the use efficiency. In order to manage these medical imaging equipment, relevant information can be collected from the medical imaging equipment.

[0003] It should be noted that the above introduction to the background technology is only for the purpose of providing a clear and complete description of the technical solution of the present application and for facilitating the understanding of those skilled in the art. Summary of the invention

[0004] The inventors have found that for medical imaging devices, the information formats of different medical systems are different. Therefore, the workload of determining the usage information of each medical imaging device based on different medical systems is very large, and the efficiency of obtaining the usage information of the medical imaging device is low.

[0005] In response to at least one of the above technical problems, embodiments of the present application provide a method, apparatus, and system for obtaining usage information of a medical imaging device.

[0006] According to one aspect of an embodiment of the present application, a method for obtaining usage information of a medical imaging device is provided, the method comprising: obtaining an image sequence, wherein the image sequence is generated by a medical imaging device and includes multiple images in a time dimension; performing text recognition on specific areas of the image to generate text information; and generating usage information of the medical imaging device based on the text information.

[0007] According to one aspect of an embodiment of the present application, an imaging device management apparatus is provided, wherein the apparatus comprises: an acquisition unit, which acquires an image sequence, wherein the image sequence is generated by a medical imaging device and comprises a plurality of images in a time dimension; a recognition unit, which performs text recognition on a specific area of ​​the image to generate text information; and a generation unit, which generates usage information of the medical imaging device based on the text information.

[0008] According to one aspect of an embodiment of the present application, a medical imaging system is provided, comprising: a medical imaging device, which generates an image sequence, wherein the image sequence includes multiple images in a time dimension; and an equipment management device, which acquires the image sequence, performs text recognition on specific areas of the images in the image sequence, generates text information, and generates usage information of the medical imaging device based on the text information.

[0009] One of the beneficial effects of the embodiments of the present application is that by performing text recognition on specific areas of images in an image sequence generated by a medical imaging device, usage information of the medical imaging device is generated based on the recognized text information, which can reduce the workload of text recognition, save computing resources, and improve the efficiency of generating usage information of the medical imaging device.

[0010] With reference to the following description and accompanying drawings, the specific implementation of the embodiment of the present application is disclosed in detail, indicating the way in which the principle of the embodiment of the present application can be adopted. It should be understood that the implementation of the present application is not limited in scope. Within the scope of the spirit and clauses of the attached claims, the implementation of the present application includes many changes, modifications and equivalents. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The included drawings are used to provide a further understanding of the embodiments of the present application, which constitute a part of the specification, are used to illustrate the implementation methods of the present application, and together with the text description, explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other implementation methods can be obtained based on these drawings without creative work. In the drawings:

[0012] Figure 1 is a schematic diagram of a method for obtaining usage information of a medical imaging device according to an embodiment of the present application;

[0013] Figure 2 is a schematic diagram of an implementation method of step 104 of the embodiment of the present application;

[0014] Figure 3 is a schematic diagram of a specific area of ​​an embodiment of the present application;

[0015] Figure 4 is a schematic diagram of an imaging device management apparatus according to an embodiment of the present application;

[0016] Figure 5 is another schematic diagram of the imaging device management apparatus according to an embodiment of the present application;

[0017] Figure 6 is a schematic diagram of a first computer device of the present application;

[0018] Figure 7 is a schematic diagram of a medical imaging system according to an embodiment of the present application. DETAILED DESCRIPTION

[0019] With reference to the accompanying drawings, the foregoing and other features of the embodiments of the present application will become apparent through the following description. In the description and the accompanying drawings, specific embodiments of the present application are specifically disclosed, which show some embodiments in which the principles of the embodiments of the present application can be adopted. It should be understood that the present application is not limited to the described embodiments. On the contrary, the embodiments of the present application include all modifications, variations and equivalents that fall within the scope of the attached claims.

[0020] In the embodiments of the present application, the terms "first", "second", etc. are used to distinguish different elements in terms of title, but do not indicate the spatial arrangement or temporal order of these elements, etc., and these elements should not be limited by these terms. The term "and / or" includes any one and all combinations of one or more of the associated listed terms. The terms "comprising", "including", "having", etc. refer to the presence of the stated features, elements, components or components, but do not exclude the presence or addition of one or more other features, elements, components or components.

[0021] In the embodiments of the present application, the singular forms "a", "the", etc. include plural forms and should be broadly understood as "a kind" or "a type" rather than being limited to the meaning of "one"; in addition, the term "said" should be understood to include both singular and plural forms, unless the context clearly indicates otherwise. In addition, the term "according to" should be understood as "at least in part according to...", and the term "based on" should be understood as "at least in part based on...", unless the context clearly indicates otherwise.

[0022] Features described and / or shown for one embodiment may be used in one or more other embodiments in the same or similar manner, combined with features in other embodiments, or replace features in other embodiments. The term "includes / comprising" when used herein refers to the presence of a feature, an entirety, a step, or a component, but does not exclude the presence or addition of one or more other features, entireties, steps, or components.

[0023] The medical imaging device described in this article can be applicable to various medical imaging modalities, including but not limited to ultrasound imaging (Ultrasound Imaging) equipment, endoscopic equipment, computed tomography (CT) equipment, magnetic resonance imaging (MRI) equipment, positron emission tomography (PET) equipment, single photon emission computed tomography (SPECT) equipment, PET / CT, PET / MR or any other suitable medical imaging equipment.

[0024] Ultrasonic imaging uses ultrasonic beams to scan and obtain image data by receiving and processing reflected signals.

[0025] Endoscopic imaging is achieved by transmitting light from a light source placed at the front end of the probe, or from a rear light source, to the front end via an optical fiber bundle, illuminating the detection area. The objective lens images the detection area on the CCD photosensitive surface, and the light signal is converted into an electrical signal to obtain image data.

[0026] CT is a continuous cross-sectional scan using X-rays around a certain part of the scanned object. The detector receives the X-rays that pass through the cross-section and converts them into visible light, or directly converts the received photon signals and forms medical imaging data after a series of processing.

[0027] MRI is based on the principle of nuclear magnetic resonance of atomic nuclei. It transmits radio frequency pulses to the scanned object, receives electromagnetic signals released by the scanned object, and reconstructs images.

[0028] PET uses a cyclotron to accelerate charged particles to bombard target nuclei, produce positron-carrying radionuclides through nuclear reactions, and synthesize imaging agents, which are introduced into the body and located in target organs. They emit positively charged electrons during the decay process. After traveling a short distance in the tissue, these positrons interact with electrons in the surrounding matter, produce annihilation radiation, and emit two photons with equal energy in opposite directions. PET imaging uses a series of paired probes that are arranged 180 degrees from each other and connected to a matching circuit to detect the photons of annihilation radiation generated by the tracer in vitro. The collected information is processed by a computer to obtain a reconstructed image.

[0029] SPECT uses radioactive isotopes as tracers, which are injected into the human body to concentrate on the organ being tested, making the organ a source of gamma rays. A detector that rotates around the human body outside the body records the distribution of radioactivity in the organ tissue. A set of data can be obtained when the detector rotates one angle, and several sets of data can be obtained when the detector rotates one circle. Based on these data, a series of tomographic plane images can be established, and the computer reconstructs the image in a cross-sectional manner.

[0030] Starting from the molecular level, PET and SPECT extend the tissue pathology examination to the display of local tissue biochemistry. The images they provide are images of human physiological metabolism. They excel in functional imaging and can detect functional and metabolic changes in the occurrence and development of diseases. CT and MRI excel in accurately reflecting morphological and structural changes. In existing methods, CT or MRI can be used to perform attenuation correction on PET or SPECT images, that is, PET or SPECT and CT or MRI are integrated into one, realizing the complementarity of functional image and anatomical image information for better identification and diagnosis.

[0031] The medical imaging system may include the aforementioned medical imaging device, and / or a separate computer device connected to the medical imaging device, and / or a computer device connected to the Internet cloud, and the computer device may be connected to the medical imaging device or a memory storing medical images via the Internet. The imaging method may be implemented independently or jointly by the aforementioned medical imaging device, the computer device connected to the medical imaging device, and the computer device connected to the Internet cloud.

[0032] In addition, the medical imaging workstation can be set up locally in the medical imaging device, that is, the medical imaging workstation is set up near the medical imaging device, and the medical imaging workstation and the medical imaging device can be co-located in the scanning room, imaging department or the same medical institution. The medical image cloud platform analysis system can be located away from the medical imaging device, for example, in the cloud that communicates with the medical imaging device.

[0033] As an example, after a medical institution completes an imaging scan using medical imaging equipment, the scanned data is stored in a storage device; a medical imaging workstation can directly read the scanned data and perform image processing through its processor. As another example, a medical image cloud platform analysis system can read medical images in a storage device through remote communication to provide "Software as a Service" (SaaS). SaaS can exist between hospitals, between hospitals and imaging centers, or between hospitals and third-party online diagnosis and treatment service providers.

[0034] In some embodiments, the medical imaging device can be used to scan and image body parts of a human body or other living organisms. However, the present application is not limited thereto, and the medical imaging device can also be used to scan and image non-living organisms.

[0035] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0036] The present application embodiment provides a method for obtaining usage information of a medical imaging device. Figure 1 is a schematic diagram of a method for obtaining usage information of a medical imaging device according to an embodiment of the present application. Figure 1 As shown, the method includes:

[0037] Step 101, acquiring an image sequence, wherein the image sequence is generated by a medical imaging device and includes a plurality of images in a time dimension;

[0038] Step 102, performing text recognition on a specific area of ​​the image to generate text information; and

[0039] Step 103: Generate usage information of the medical imaging device according to the text information.

[0040] According to the above embodiment, text recognition is performed on specific areas of images in an image sequence generated by a medical imaging device, and usage information of the medical imaging device is generated based on the recognized text information. Since it is not necessary to perform text recognition in the entire range of the image, only a small amount of text recognition is required in a specific area of ​​the image. Therefore, the workload of text recognition can be reduced, computing resources can be saved, and the efficiency of generating usage information of the medical imaging device can be improved.

[0041] In some embodiments, in step 101, a plurality of images (ie, an image sequence) in a time dimension are acquired from a medical imaging device, thereby enabling the use information of the medical imaging device within a period of time to be acquired from the information contained in the image sequence.

[0042] The usage information may include identification information, working mode information, working status information, etc. of the medical imaging device, or the usage information may also be information further generated based on the above information. For example, the usage information may also include information such as the utilization rate, intact rate, failure rate, function development rate, and rate of return of the medical imaging device.

[0043] This usage information can be used as a basis for performance management of medical imaging equipment. For example, according to the utilization rate of medical imaging equipment, medical imaging equipment can be reasonably deployed, and "idle" or "inefficient" medical imaging equipment can be promptly transferred to the departments in need for full use; or, according to the utilization rate or failure rate of medical imaging equipment, medical imaging equipment can be repaired or maintained in a timely manner, etc.

[0044] In some embodiments, the image sequence may be an image sequence output from a video transmission interface of a medical imaging device. The image sequence may be an image sequence output in real time by the video transmission interface, thereby being able to obtain images output by the medical imaging device in a full time period. Thus, the accuracy and reliability of the generated usage information of the medical imaging device can be ensured.

[0045] The video transmission interface of the medical imaging device may include various interfaces capable of outputting video data. For example, dedicated video transmission interfaces such as HDMI interface, DP interface, DVI interface, VGA interface, network communication interfaces such as RJ45 interface, or data transmission interfaces such as USB interface, etc. By acquiring the image sequence from the original video transmission interface of the medical imaging device, it is not necessary to change the hardware structure of the medical imaging device, thereby reducing the intrusiveness of the hardware connection of the medical imaging device; in addition, medical imaging devices are usually provided with a video transmission interface, and the above method of the embodiment of the present application has good universality.

[0046] In some embodiments, Figure 1 As shown, the method also includes:

[0047] Step 104: Determine a specific area.

[0048] Here, step 104 may be performed before step 101 , or may be performed after step 101 .

[0049] Figure 2 is a schematic diagram of an implementation of step 104 of the present application embodiment. In some embodiments, Figure 2 As shown, step 104 may include:

[0050] Step 201: for at least one image in the image sequence, perform text recognition in the entire range of the image to generate first text information; and

[0051] Step 202: setting the area where the first text message containing preset information is located as a specific area, wherein the preset information is related to the usage information.

[0052] According to the above embodiment, text recognition is performed in the entire range of the image, and the area containing preset information related to the usage information is set as the specific area, thereby automatically determining the specific area in the image. Compared with the method of manually or manually selecting the text position in the prior art, the operation steps can be simplified and the convenience can be improved; and the above method of determining the specific area is applicable to a variety of medical systems or different versions of medical systems, has good universality, and is easy to maintain.

[0053] In some embodiments, the specific area is a partial area within the entire range of the image, and the specific area is smaller than the size of the entire image.

[0054] In some embodiments, the determined specific area can be saved as a configuration text (for example, in the form of JSON, YML, XML, etc.) for use during the next recognition.

[0055] In some embodiments, in step 201, a portion of images may be selected from an image sequence for text recognition in the entire image range. The selected portion of images may be multiple images in the image sequence, thereby improving the reliability of the determined specific area. The present application is not limited thereto, and the portion of images may also be an image in the image sequence, thereby reducing the amount of calculation for the specific area.

[0056] In some embodiments, the image may include a scanned image and related fields, etc. The related fields may include, for example, date information, time information, patient information, identification information of the medical imaging device, working mode information, working status information, etc.

[0057] In step 201, when performing text recognition on the entire image range, one or more first text information may be generated according to relevant fields in the entire image range, and each first text information may correspond to an area, and the first text information is located in the area.

[0058] Among them, various methods can be used to perform text recognition to generate the first text information. For example, traditional OCR (Optical Character Recognition) technology can be used for text recognition, including text area positioning, text image correction, row and column segmentation, classifier recognition, post-processing, etc. of the input image; or, deep learning-based OCR technology can be used for text recognition, for example, text recognition based on the PaddleOCR framework.

[0059] The area corresponding to the first text information may be determined in various ways. For example, the area where the first text information is located may be determined based on a connected domain, edge features, stroke features, texture features, etc. For specific methods of text recognition, reference may be made to related technologies and will not be described in detail here.

[0060] In some embodiments, in step 202, when the area where the first text information is located contains preset information, the area where the first text information is located can be set as a specific area of ​​the image.

[0061] The preset information is related to the usage information of the medical imaging device. The preset information may include at least one indicator information used to generate the usage information, and each indicator information includes at least one indicator data.

[0062] For example, the indicator information may include identification information, working mode information, working status information, etc. of the medical imaging device.

[0063] The identification information of the medical imaging device includes, for example, type information of the medical imaging device, such as the model of the ultrasound probe.

[0064] The working mode information includes, for example, scanning site information, such as abdomen, neck, etc., or liver, gallbladder, kidney, breast, thyroid, etc.

[0065] The working state information includes various information related to the working state of the medical imaging device. Taking an ultrasound device as an example, its working state may include a static state (outputting a static ultrasound image), a non-static state (outputting a real-time ultrasound image), and the like.

[0066] In some embodiments, in the preset information, one indicator information may include all possible indicator data, and these indicator data may cover different medical systems, thereby further improving the universality of the method described in the embodiment of the present application.

[0067] For example, taking ultrasound equipment as an example, the indicator data representing the abdomen in the working mode information (indicator information) may include: abdomen, adult abdomen, Abdomen, etc., the indicator data representing stillness in the working status information (indicator information) may include: still, freeze, etc., and the indicator data representing non-stillness may include non-still, unfreeze, live, etc.

[0068] In some embodiments, when the indicator data of the first text information is the same as the preset information, it is determined that the area where the first text information is located contains the preset information, and the area where the first text information is located is set as the specific area.

[0069] For example, the first text information is “adult abdomen”, which is the same as the indicator data “adult abdomen” of the preset information, and the area where the first text information is located is set as the specific area.

[0070] In some embodiments, when the similarity between the index data of the first text information and the preset information is greater than a preset threshold, it can also be determined that the area where the first text information is located contains the preset information, and the area where the first text information is located is set as a specific area. In this way, it can be compatible with more medical systems or software versions, reduce maintenance costs, and further improve the universality of the method described in the embodiments of the present application.

[0071] Among them, the similarity between the first text information and the indicator data can be determined in various ways, for example, the similarity is calculated based on a character string, a corpus, etc. The specific calculation method can refer to the relevant technology and will not be elaborated here; the preset threshold can be an empirical value or a value determined according to actual conditions.

[0072] For example, the first text information is “adult abdomen”, and its similarity with the indicator data “adult abdomen” exceeds 98%. In this case, the area where the first text information is located can also be set as the specific area.

[0073] In some embodiments, in the preset information, there may be multiple indicator information for generating usage information. In this case, a specific area corresponding to each indicator information may be determined. For example, when the first text information is the same as the first indicator data of the first indicator information among the multiple indicator information or the similarity is greater than a preset threshold, the area where the first text information is located is set as the specific area of ​​the first indicator information.

[0074] For example, the preset information may include three indicator information: identification information, working mode information, and working status information of the medical imaging device. Corresponding specific areas may be determined for each of the three indicator information.

[0075] In some embodiments, the preset information may be pre-stored in a database, thereby facilitating query or search. For example, after obtaining the first text message, it may be possible to query in the database whether there is indicator data that is the same as the first text message or has a similarity exceeding a preset threshold. If the indicator data exists in the database, the area where the first text message is located may be set as the corresponding specific area.

[0076] The database may be any type of database. For example, a non-relational database (e.g., Elasticsearch, MongoDB, etc.) may be used to store preset information (e.g., an indicator data set storing three indicator information, i.e., identification information, working mode information, and working status information of a medical imaging device) in a segmented form, and retrieved using an index query.

[0077] For another example, an in-memory database (e.g., Redis, Memecache, etc.) can be used to store preset information in a hash table and retrieve it using keyword queries; or, a Bloom filter can be used to store it and compare it by determining whether each keyword exists in the preset information (e.g., an indicator data set of three indicator information: identification information, working mode information, and working status information of medical imaging equipment).

[0078] Figure 3 is a schematic diagram of a specific area of ​​an embodiment of the present application. Figure 3 An example of a specific area in an ultrasound image is shown. It can be understood that the following description of the specific area is also applicable to other types of images.

[0079] like Figure 3 As shown, image 300 is an image in an image sequence. Text recognition is performed on the entire image range of image 300 to obtain a plurality of first text information, such as "2023 / 10 / 18", "09:20:32", "abc", "abdomen", "freeze", and regions 301-305 corresponding to the first text information.

[0080] Each of the first text information is used as a keyword to search in a database storing preset information, and the database includes, for example, an identification information database, a working mode information database, and a working status information database.

[0081] When the identification information library includes the first text information "abc", the area 303 where the first text information "abc" is located is used as the specific area of ​​the identification information; when the working mode information library includes the first text information "abdomen", the area 304 where the first text information "abdomen" is located is used as the specific area of ​​the working mode information; when the working status information library includes the first text information "freeze", the area 305 where the first text information "freeze" is located is used as the specific area of ​​the working status information.

[0082] In some embodiments, if more than one image is selected from the image sequence for text recognition in the entire range to determine the specific area, candidate specific areas can be generated according to each image, and the final specific area can be determined according to the multiple candidate specific areas. The method for determining the candidate specific areas can refer to the above content and will not be described in detail here.

[0083] In some embodiments, the final specific area may be an area selected from multiple candidate specific areas. For example, based on the similarity between the first text information and the indicator data, the area where the first text information with the highest similarity is located is selected from multiple candidate specific areas as the specific area. The present application is not limited thereto, and the specific area may also be selected based on other criteria.

[0084] Alternatively, the final specific area may be an average value of multiple candidate specific areas. For example, the specific area may be represented by location information, and the location information may include at least one of the following: coordinate information (x, y) of the first pixel in the area where the first text information is located, height information (h) of the area where the first text information is located, or width information (w) of the area where the first text information is located. Correspondingly, the candidate specific area may also be represented by the above location information.

[0085] The above x, y, h, and w can be represented by pixel positions in an image. For example, if the image includes 1920*1080 pixels, the position information (x, y, h, w) can be represented as [1795, 45, 125, 25].

[0086] Among them, in the location information of the specific area, the location information of the first pixel can be the average value of the location information of the first pixel of the candidate specific area; the height information can be the average value of the height information of the candidate specific area; and the width information can be the average value of the width information of the candidate specific area.

[0087] In some embodiments, the first pixel may be any pixel in the area where the first text information is located. For example, the area where the first text information is located is a rectangle, and the first pixel is the pixel corresponding to the upper left corner of the rectangle; or the first pixel is the pixel corresponding to the center of the rectangle, and so on.

[0088] In some embodiments, Figure 2 As shown, step 104 may also include:

[0089] Step 203, when the specific regions of other image sequences are predetermined, the specific regions of the image sequence are determined according to the similarity between the images in the other image sequences and the images in the image sequence, and the specific regions of the other image sequences.

[0090] For example, when the similarity between an image in another image sequence and an image in the image sequence is greater than a first threshold, the specific region of the other image sequence is used as the specific region of the image sequence.

[0091] The similarity of images can be expressed in various ways, such as the similarity of image data, or the similarity of digital fingerprints (or digital summaries) of images. The specific method of obtaining the similarity of images can refer to the relevant technology, which will not be described in detail here.

[0092] For example, for the same model and the same (medical system) software version, when the image similarity reaches more than 98%, the original configuration file (specific area) can be reused.

[0093] According to the above embodiment, text recognition can be performed on the entire image range to generate first text information and corresponding area information. After searching the indicator database for each indicator information in the database, the location information of the specific area can be determined and written into the configuration file for storage. The configuration file can be used as the current independent configuration file of the current medical imaging device and provided for subsequent text recognition operations; or, when the image similarity is greater than the first threshold, the configuration file can also be used as a configuration file for other medical imaging devices. While saving computing resources, a large amount of human cost resources are also saved.

[0094] In some embodiments, in step 102, when performing text recognition on a specific area of ​​an image to generate text information, the text recognition result may be converted with reference to the aforementioned preset information or a database including the preset information to generate standardized text information.

[0095] For example, in the working mode information (indicator information) database, the data sets (indicator data) representing the abdomen include abdomen, adult abdomen, and Abdomen. The result of text recognition for a specific area is Abdomen, that is, the result of text recognition is the same as at least one of the data sets representing the abdomen, then the result of text recognition can be standardized as "abdomen"; or, the result of text recognition is "adult abdomen", that is, the similarity between the result of text recognition and at least one of the data sets representing the abdomen exceeds a preset threshold, then the result of text recognition can also be standardized as "abdomen".

[0096] In some embodiments, in step 103, the use information of the medical imaging device is generated according to the text information. For example, the use information includes identification information, working mode information, and working status information of the medical imaging system. When any one of the above three information changes, the above three information and time information are recorded. For example, the use information may include multiple entries. When any one of the identification information, working mode information, and working status information changes, a new entry is created, and each entry may record the start time and the end time.

[0097] Table 1 is an example of usage information. As shown in Table 1, item 1 indicates that during the period from 9:00 to 9:30, ultrasound probe ABC scanned the abdomen of an adult and output a real-time scan image; item 2 indicates that during the period from 19:10 to 19:15, ultrasound probe ABC scanned the abdomen of an adult and output a static scan image.

[0098] Table 1 Example of usage information

[0099] Item 1 9 o'clock 9:30 ABC Adult abdomen FREEZE Entry 2 19:10 19:15 ABC Adult abdomen Live

[0100] The present application is not limited thereto, and the usage information may also include other content or other forms.

[0101] In some embodiments, the usage information may be written into a database so that performance analysis or management of the medical imaging device may be performed based on the usage information.

[0102] It is worth noting that the above Figure 1-3 The embodiments of the present application are only schematically described, but the present application is not limited thereto. For example, the execution order of the various operations can be appropriately adjusted, and other operations can be added or some operations can be reduced. Those skilled in the art can make appropriate modifications based on the above content, and are not limited to the above appended Figure 1-3 Records of.

[0103] It can be seen from the above embodiments that text recognition is performed on a specific area of ​​an image in an image sequence generated by a medical imaging device, and usage information of the medical imaging device is generated based on the recognized text information. Since there is no need to perform text recognition in the entire range of the image, the workload of text recognition can be reduced, computing resources can be saved, and the efficiency of generating usage information of the medical imaging device can be improved.

[0104] The embodiment of the present application also provides an imaging device management device, and the parts repeated in the above-mentioned embodiment are not repeated here. Figure 4 is a schematic diagram of an imaging device management apparatus according to an embodiment of the present application, such as Figure 4 As shown, the imaging device management apparatus 400 includes: an acquisition unit 401 , an identification unit 402 , and a generation unit 403 .

[0105] The acquisition unit 401 acquires an image sequence, wherein the image sequence is generated by a medical imaging device and includes multiple images in a time dimension; the recognition unit 402 performs text recognition on a specific area of ​​the image to generate text information; and the generation unit 403 generates usage information of the medical imaging device based on the text information.

[0106] In some embodiments, Figure 4 As shown, the device 400 further includes: a determining unit 404.

[0107] The determination unit 404 determines the specific area, performs text recognition in the entire range of at least one image in the image sequence, generates first text information, and sets the area where the first text information containing preset information is located as the specific area, wherein the preset information is related to the usage information.

[0108] In some embodiments, the preset information includes at least one indicator information used to generate the usage information, and each of the indicator information includes at least one indicator data.

[0109] In some embodiments, when the first text information is identical to the indicator data or the similarity is greater than a preset threshold, the area where the first text information is located contains the preset information.

[0110] In some embodiments, there are multiple indicator information. When the first text information is the same as the first indicator data of the first indicator information among the multiple indicator information or the similarity is greater than a preset threshold, the area where the first text information is located is set as the specific area of ​​the first indicator information.

[0111] In some embodiments, the determination unit 404 determines the specific area of ​​the image sequence based on the similarity between the images in the other image sequences and the images in the image sequence, and the specific area of ​​the other image sequences, when the specific area of ​​the other image sequences is predetermined.

[0112] In some embodiments, when the similarity between the images in the other image sequences and the images in the image sequence is greater than a first threshold, the specific region of the other image sequence is used as the specific region of the image sequence.

[0113] In some embodiments, the image sequence is an image sequence output by a video transmission interface of the medical imaging device.

[0114] In some embodiments, the preset information is pre-stored in a database.

[0115] In some embodiments, the specific area is represented by location information, and the location information includes at least one of the following: coordinate information of a first pixel in the area where the first text information is located, height information of the area where the first text information is located, or width information of the area where the first text information is located.

[0116] Figure 5 FIG. 3 is another schematic diagram of the device management apparatus 300 according to an embodiment of the present application. Figure 5 As shown, the equipment management apparatus 300 includes an analysis terminal 307 and a first computer device 306. The analysis terminal 307 can be directly connected to a video transmission interface of a medical imaging device to receive an image sequence output by the medical imaging device from the video transmission interface.

[0117] In some embodiments, the analysis terminal 307 may be a microprocessor. For example, the analysis terminal 307 may include a processor and a memory, which may run an embedded system such as Linux / Debian, and the memory may store a program, which may use a scripting language (shell / python), image processing technology (ffmpeg, opencv), and OCR text recognition for processing.

[0118] The analysis terminal 307 can be configured to implement Figure 4 The imaging device management apparatus 300 shown in FIG. 3 is a device for managing an image of an image. The imaging device management apparatus 300 shown in FIG. 3 is a device for managing ...

[0119] In some embodiments, the first computer device 306 may be a computer server, a cloud platform, a workstation, etc., but the embodiments of the present application are not limited thereto.

[0120] Figure 6 306 is a schematic diagram of the first computer device 306 of the present application. Figure 6 As shown, the first computer device 306 may include: one or more processors (e.g., central processing unit CPU) 1410 and one or more memories 1420; the memory 1420 is coupled to the processor 1410. The memory 1420 may store a program 1421 and / or data, and execute the program 1421 under the control of the processor 1410. The memory 1420 may include, for example, a ROM, a floppy disk, a hard disk, an optical disk, a magneto-optical disk, a CD-ROM, or a non-volatile memory card.

[0121] In some embodiments, part or all of the functions of the imaging device management apparatus 300 may be integrated into the processor 1410 for implementation. The processor 1410 is configured to implement Figure 4 The imaging device management apparatus 300 shown has at least one function of the identification unit 402, the generation unit 403, and the determination unit 404. The implementation of the processor 1410 can refer to the above-mentioned embodiment, which will not be described in detail here.

[0122] like Figure 6 As shown, the first computer device 306 may also include: an input device 1430 and a display 1440, etc. The functions of the above components are similar to those of the prior art and are not described in detail here. It is worth noting that the first computer device 306 does not necessarily include Figure 6 In addition, the first computer device 306 may also include Figure 6For components not shown in the figure, reference may be made to the related art.

[0123] It can be seen from the above embodiments that text recognition is performed on a specific area of ​​an image in an image sequence generated by a medical imaging device, and usage information of the medical imaging device is generated based on the recognized text information. Since there is no need to perform text recognition in the entire range of the image, the workload of text recognition can be reduced, computing resources can be saved, and the efficiency of generating usage information of the medical imaging device can be improved.

[0124] An embodiment of the present application also provides a medical imaging system. Figure 7 Schematic diagram of a medical imaging system according to an embodiment of the present application. Figure 7 As shown, the medical imaging system 700 includes a medical imaging device 701 and a device management apparatus 300. The relevant contents of the medical imaging device 701 and the device management apparatus 300 can refer to the aforementioned embodiments, and the repeated parts will not be repeated.

[0125] The medical imaging device 701 generates an image sequence, wherein the image sequence includes multiple images in a time dimension; the equipment management device 300 obtains the image sequence, performs text recognition on specific areas of the images in the image sequence, generates text information, and generates usage information of the medical imaging device based on the text information.

[0126] In some embodiments, the image processing device 300 is connected to a video transmission interface of the medical imaging device 701 to obtain the image sequence from the video transmission interface.

[0127] In some embodiments, Figure 7 As shown, the medical imaging system 700 may further include a second computer device 703 connected to the medical imaging device 701. The second computer device 703 may run a medical system (e.g., PACS / RIS, etc.) for managing the medical imaging device 701. The structure of the second computer device 703 may be similar to that of the first computer device 306.

[0128] In some embodiments, the first computer device 306 and the second computer device 703 may be separately configured, or may be integrated together.

[0129] In some embodiments, Figure 7 As shown, the medical imaging system 700 may further include a storage device 702, which may be used to store at least one of the preset information, configuration text, and usage information in the aforementioned embodiments. The storage device 702 may be separately provided, or may be integrated in the first computer device 306 or the second computer device 703.

[0130] An embodiment of the present application also provides a computer-readable program, wherein when the program is executed, the program enables the computer to execute the method for obtaining usage information of the medical imaging device described in the above embodiment in the apparatus or system or computer device.

[0131] An embodiment of the present application also provides a storage medium storing a computer-readable program, wherein the computer-readable program enables a computer to execute the method for obtaining usage information of a medical imaging device as described in the aforementioned embodiment in an apparatus, system or computer device.

[0132] The above devices and methods of the present application can be implemented by hardware, or by hardware combined with software. The present application relates to such a computer-readable program, which, when executed by a logic component, enables the logic component to implement the above-mentioned devices or components, or enables the logic component to implement the various methods or steps described above. The present application also relates to a storage medium for storing the above program, such as a hard disk, a magnetic disk, an optical disk, a DVD, a flash memory, etc.

[0133] The method / device described in conjunction with the embodiments of the present application may be directly embodied as hardware, a software module executed by a processor, or a combination of the two. For example, one or more of the functional block diagrams shown in the figure and / or one or more combinations of the functional block diagrams may correspond to various software modules of the computer program flow or to various hardware modules. These software modules may correspond to the various steps shown in the figure, respectively. These hardware modules may be implemented by solidifying these software modules, for example, using a field programmable gate array (FPGA).

[0134] The software module may be located in a RAM memory, a flash memory, a ROM memory, an EPROM memory, an EEPROM memory, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. A storage medium may be coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium; or the storage medium may be an integral part of the processor. The processor and the storage medium may be located in an ASIC. The software module may be stored in a memory of a mobile terminal or in a memory card that can be inserted into the mobile terminal. For example, if a device (such as a mobile terminal) uses a large-capacity MEGA-SIM card or a large-capacity flash memory device, the software module may be stored in the MEGA-SIM card or the large-capacity flash memory device.

[0135] One or more of the functional blocks and / or one or more combinations of the functional blocks described in the drawings may be implemented as a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, or any appropriate combination thereof for performing the functions described in the present application. One or more of the functional blocks and / or one or more combinations of the functional blocks described in the drawings may also be implemented as a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, or any appropriate combination thereof.

[0136] It is a combination of computing devices, for example, a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in communication with a DSP, or any other such configuration. The above embodiments are only exemplary descriptions of the embodiments of the present application, but the present application is not limited thereto, and appropriate modifications can be made on the basis of the above embodiments. For example, the above embodiments can be used alone, or one or more of the above embodiments can be combined.

[0137] The present application is described above in conjunction with specific implementation methods, but it should be clear to those skilled in the art that these descriptions are exemplary and are not intended to limit the scope of protection of the present application. Those skilled in the art can make various modifications and variations to the present application based on the spirit and principles of the present application, and these modifications and variations are also within the scope of the present application.

[0138] The preferred embodiments of the present application are described above with reference to the accompanying drawings. Many features and advantages of these embodiments are clear from this detailed description, and therefore the appended claims are intended to cover all such features and advantages of these embodiments that fall within their true spirit and scope. In addition, since many modifications and variations are easily conceivable to those skilled in the art, the embodiments of the present application are not intended to be limited to the precise structures and operations illustrated and described, but all suitable modifications, variations, and equivalents that fall within their scope may be covered.

Claims

1. A method for obtaining usage information of a medical imaging device, characterized in that: The method comprises: Acquire an image sequence, wherein the image sequence is generated by the medical imaging device and includes a plurality of images in a time dimension; Performing text recognition on a specific area of ​​the image to generate text information; and The usage information of the medical imaging device is generated according to the text information.

2. The method according to claim 1, characterized in that The image sequence is an image sequence output by a video transmission interface of the medical imaging device.

3. The method according to claim 1, characterized in that The method further includes: determining the specific area, wherein determining the specific area includes: For at least one image in the image sequence, perform text recognition in the entire range of the image to generate first text information; and An area where the first text information containing preset information is located is set as the specific area, wherein the preset information is related to the usage information.

4. The method according to claim 3, characterized in that: The preset information is pre-stored in a database.

5. The method according to claim 3, characterized in that: The preset information includes at least one indicator information used to generate the usage information, and each of the indicator information includes at least one indicator data.

6. The method according to claim 5, characterized in that When the first text information is identical to the indicator data or the similarity is greater than a preset threshold, the area where the first text information is located contains the preset information.

7. The method according to claim 5, characterized in that There are multiple indicator information. When the first text information is identical to the first indicator data of the first indicator information among the multiple indicator information or the similarity is greater than a preset threshold, the area where the first text information is located is set as the specific area of ​​the first indicator information.

8. The method according to claim 7, characterized in that The specific area is represented by position information, and the position information includes at least one of the following: coordinate information of a first pixel in the area where the first text information is located, height information of the area where the first text information is located, or width information of the area where the first text information is located.

9. The method according to claim 3, characterized in that: Determining the specific area further includes: When a specific region of another image sequence is predetermined, the specific region of the image sequence is determined based on the similarity between images in the other image sequence and images in the image sequence and the specific region of the other image sequence.

10. The method according to claim 9, characterized in that When the similarity between the images in the other image sequences and the images in the image sequence is greater than a first threshold, the specific region of the other image sequence is used as the specific region of the image sequence.

11. An imaging device management device, characterized in that: The device comprises: an acquisition unit, which acquires an image sequence, wherein the image sequence is generated by a medical imaging device and includes a plurality of images in a time dimension; a recognition unit, which performs text recognition on a specific area of ​​the image to generate text information; and A generating unit generates usage information of the medical imaging device according to the text information.

12. The device according to claim 11, characterized in that The device also includes: A determination unit determines the specific area, performs text recognition in the entire range of at least one image in the image sequence, generates first text information, and sets the area where the first text information containing preset information is located as the specific area, wherein the preset information is related to the usage information.

13. The device according to claim 12, characterized in that The preset information includes at least one indicator information used to generate the usage information, and each of the indicator information includes at least one indicator data.

14. The device according to claim 13, characterized in that When the first text information is identical to the indicator data or the similarity is greater than a preset threshold, the area where the first text information is located contains the preset information.

15. The device according to claim 13, characterized in that There are multiple indicator information. When the first text information is identical to the first indicator data of the first indicator information among the multiple indicator information or the similarity is greater than a preset threshold, the area where the first text information is located is set as the specific area of ​​the first indicator information.

16. The device according to claim 12, characterized in that The determining unit determines the specific area of ​​the image sequence according to the similarity between the images in the other image sequence and the images in the image sequence and the specific area of ​​the other image sequence when the specific area of ​​the other image sequence is determined in advance.

17. The device according to claim 16, characterized in that When the similarity between the images in the other image sequences and the images in the image sequence is greater than a first threshold, the specific region of the other image sequence is used as the specific region of the image sequence.

18. A medical imaging system, characterized in that: A medical imaging device that generates an image sequence, wherein the image sequence includes a plurality of images in a time dimension; and The equipment management device acquires the image sequence, performs text recognition on specific areas of the images in the image sequence to generate text information, and generates usage information of the medical imaging equipment according to the text information.

19. The system according to claim 18, characterized in that The image processing device is connected to a video transmission interface of the medical imaging device and acquires the image sequence from the video transmission interface.

Images