Data loading method and device, electronic device and storage medium

Abstract

The present disclosure relates to a data loading method and device, an electronic device and a storage medium, wherein the method comprises: identifying target data to be loaded and obtaining an identification result; in response to the loading process of the target data, displaying an application set corresponding to the target data according to the identification result, wherein the application set includes at least one application. With the present disclosure, it is not necessary to determine which application to use before loading, and an application set consisting of at least one application corresponding to the identification result of the target data can be obtained, so that the user can select the best one or more applications in the application set, and it is not necessary to perform application switching processing, thereby improving data processing efficiency.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing, and in particular to a data loading method and device, an electronic device, and a storage medium. Background Art

[0002] In an application scenario for data processing, medical image data can be obtained through tomography imaging. During the data processing of the medical image data, the data can be processed by loading an application for the data processing. However, before loading, it is not certain which application to use. If the application is loaded incorrectly, it is necessary to exit the application and perform application switching processing, resulting in low data processing efficiency. There is no effective solution in the related art. Summary of the invention

[0003] In view of this, the present disclosure proposes a technical solution for data loading.

[0004] According to one aspect of the present disclosure, a data loading method is provided, the method comprising:

[0005] Identify the target data to be loaded and obtain the identification result;

[0006] In response to the loading process of the target data, an application set corresponding to the target data is displayed according to the recognition result, and the application set includes at least one application.

[0007] By adopting the present disclosure, the target data to be loaded can be identified to obtain an identification result. In response to the loading processing of the target data, an application set consisting of at least one application corresponding to the target data identification result can be used. There is no need to determine which application to use before loading. The user can select the best one or more applications in the application set during the real-time loading data processing process, and there is no need to perform application switching processing, thereby improving data processing efficiency.

[0008] In a possible implementation, the step of identifying the target data to be loaded and obtaining the identification result includes:

[0009] Performing feature extraction on the target data to be loaded to obtain a feature extraction result;

[0010] According to the feature extraction result, the body parts and / or organs corresponding to the target data are obtained, and a first set consisting of the body parts and / or organs is used as the recognition result.

[0011] By adopting the present disclosure, feature extraction can be performed on the target data to be loaded to obtain a feature extraction result. Based on the feature extraction result, the body parts and / or organs corresponding to the target data can be more accurately obtained, and the first set consisting of the body parts and / or organs can be used as the recognition result, thereby improving the recognition accuracy.

[0012] In a possible implementation, the step of identifying the target data to be loaded and obtaining the identification result includes:

[0013] Performing attribute analysis on the target data to be loaded to obtain analysis results;

[0014] According to the analysis result, the attributes corresponding to the target data are obtained, and a second set consisting of the attributes is used as the recognition result.

[0015] By adopting the present disclosure, the target data to be loaded can be subjected to attribute analysis to obtain analysis results. According to the analysis results, the attributes corresponding to the target data can be obtained, and the second set composed of the attributes is used as the recognition result, thereby improving the diversity of the recognition results.

[0016] In a possible implementation, the attribute includes: at least one of a data source of the target data, a data type, an imaging type, a scanning type, and auxiliary information associated with the target data.

[0017] By adopting the present disclosure, attribute analysis can be performed on the target data to be loaded, wherein the attributes include: the data source of the target data, the data type, the imaging type, the scanning type, and at least one of the auxiliary information associated with the target data. Then, the analysis results obtained after performing the attribute analysis also have diversity, and the diverse analysis results can be used in the subsequent recognition process, thereby improving the recognition accuracy.

[0018] In a possible implementation, before the response to the target data loading process, the method further includes:

[0019] Acquire a lookup operation based on the target data;

[0020] The loading process in response to the target data includes:

[0021] The loading process is executed to load the target data.

[0022] By adopting the present disclosure, a search operation based on the target data can be obtained in a visual preview interface, and an interaction can be implemented for the search operation, so as to respond to the loading process of the target data, execute the loading process, and load the target data. The data loading process implemented in an interactive manner is simpler and easier to use for users.

[0023] In a possible implementation, when the target data is obtained from a preview interface and the application set is presented in an application interface, displaying the application set corresponding to the target data according to the recognition result includes:

[0024] According to the recognition result, jump from the preview interface to the application interface, and display at least two applications corresponding to the target data in the application interface;

[0025] According to the analysis of the at least two applications, a selection strategy is obtained, so as to obtain an application currently recommended for use according to the selection strategy;

[0026] The display mode of the selection strategy includes at least one of an information prompt box and a voice prompt.

[0027] By adopting the present disclosure, it is possible to jump from the preview interface to the application interface according to the recognition result, and at least two applications corresponding to the target data are displayed in the application interface. According to the analysis of the at least two applications, a selection strategy can be obtained, so as to obtain an application currently recommended for use according to the selection strategy. The interaction is realized by displaying at least one selection strategy including an information prompt box and a voice prompt, so as to obtain an application currently recommended for use according to the selection strategy in response to the loading process of the target data. The selection operation in the data loading process realized in an interactive manner is simpler and easier to use for users.

[0028] In a possible implementation, when the target data is obtained from a preview interface and the application set is presented in an application interface, displaying the application set corresponding to the target data according to the recognition result includes:

[0029] According to the recognition result, the preview interface is jumped to the application interface, and an application corresponding to the target data is displayed in the application interface.

[0030] By adopting the present disclosure, it is possible to jump from the preview interface to the application interface based on the recognition result, accurately display an application corresponding to the target data in the application interface, accurately locate and jump to an application corresponding to the target data in the application interface, thereby improving the recognition accuracy.

[0031] According to another aspect of the present disclosure, a data loading device is provided, the device comprising:

[0032] The first processing unit is used to identify the target data to be loaded and obtain an identification result;

[0033] The second processing unit is configured to, in response to the loading process of the target data, display an application set corresponding to the target data according to the recognition result, wherein the application set includes at least one application.

[0034] In a possible implementation, the first processing unit is configured to:

[0035] Performing feature extraction on the target data to be loaded to obtain a feature extraction result;

[0036] According to the feature extraction result, the body parts and / or organs corresponding to the target data are obtained, and a first set consisting of the body parts and / or organs is used as the recognition result.

[0037] In a possible implementation, the first processing unit is configured to:

[0038] Performing attribute analysis on the target data to be loaded to obtain analysis results;

[0039] According to the analysis result, the attributes corresponding to the target data are obtained, and a second set consisting of the attributes is used as the recognition result.

[0040] In a possible implementation, the attribute includes: at least one of a data source of the target data, a data type, an imaging type, a scanning type, and auxiliary information associated with the target data.

[0041] In a possible implementation, the second processing unit is configured to:

[0042] When a lookup operation based on the target data is obtained, the loading process is performed to load the target data.

[0043] In a possible implementation, the second processing unit is configured to:

[0044] The target data is obtained from the preview interface, and when the application set is presented in an application interface, jumping from the preview interface to the application interface according to the recognition result, and displaying at least two applications corresponding to the target data in the application interface;

[0045] According to the analysis of the at least two applications, a selection strategy is obtained, so as to obtain an application currently recommended for use according to the selection strategy;

[0046] The display mode of the selection strategy includes at least one of an information prompt box and a voice prompt.

[0047] In a possible implementation, the second processing unit is configured to:

[0048] The target data is obtained from the preview interface. When the application set is presented in an application interface, the preview interface is jumped to the application interface according to the recognition result, and an application corresponding to the target data is displayed in the application interface.

[0049] According to another aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to execute the above method.

[0050] According to another aspect of the present disclosure, a non-volatile computer-readable storage medium is provided, on which computer program instructions are stored, wherein the computer program instructions implement the above method when executed by a processor.

[0051] By adopting the present disclosure, the target data to be loaded can be identified to obtain an identification result, without having to determine which application to use before loading. Instead, in response to the loading process of the target data, an application set consisting of at least one application corresponding to the target data identification result can be provided for the user to select the best one or more applications in the application set, without having to perform application switching processing, thereby improving data processing efficiency.

[0052] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

[0053] Further features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate exemplary embodiments, features, and aspects of the disclosure and, together with the description, serve to explain the principles of the disclosure.

[0055] The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and are used to illustrate the technical solutions of the present disclosure together with the specification.

[0056] Figure 1 A flow chart of a data loading method according to an embodiment of the present disclosure is shown.

[0057] Figure 2 A schematic diagram of an application list according to an embodiment of the present disclosure is shown.

[0058] Figure 3 A schematic diagram showing an image data reading scenario for medical treatment according to an embodiment of the present disclosure is shown.

[0059] Figure 4A block diagram of a data loading device according to an embodiment of the present disclosure is shown.

[0060] Figure 5 A block diagram of an electronic device according to an embodiment of the present disclosure is shown.

[0061] Figure 6 A block diagram of an electronic device according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0062] Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise specified.

[0063] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0064] The term "and / or" herein is only a description of the association relationship of the associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the term "at least one" herein represents any combination of at least two of any one or more of a plurality of. For example, including at least one of A, B, and C can represent including any one or more elements selected from the set consisting of A, B, and C.

[0065] In addition, in order to better illustrate the present disclosure, numerous specific details are given in the following specific embodiments. It should be understood by those skilled in the art that the present disclosure can also be implemented without certain specific details. In some examples, methods, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the subject matter of the present disclosure.

[0066] In the related technology, in the data processing process of data loading, for example, for medical image data, multi-layer two-dimensional tomographic images generated by technologies such as computed tomography (CT) and magnetic resonance imaging (MRI) can be used to perform three-dimensional reconstruction, which can be used to observe the distribution of lesions on the surface of the human body cavity, and the distribution of lesions inside or outside the surface of the inner cavity. The observation angle and position can also be adjusted arbitrarily according to customized needs. In conjunction with a variety of three-dimensional reconstruction technologies, such as multi-planner reformation (MPR) and volume rendering (VR), the position of lesions in the human body can be easily located.

[0067] Based on the above-mentioned medical image data, users can use reading software, reading platforms (such as PACS reading systems), medical image post-processing workstations, or private cloud image services deployed by hospitals to read the medical image data in medical image data reading scenarios, such as assisting daily diagnosis and surgical planning.

[0068] By consulting the above-mentioned medical image data to assist daily diagnosis and surgical planning, the user needs to manually load a specific examination for the medical image data and jump to a specific application corresponding to the specific examination. Before the application is loaded, it is unclear what the medical image data obtained by scanning the patient may reflect. For example, the image data in a CT image may reflect the condition of multiple diseases. For example, in a chest and lung CT image, the patient's chest, lungs, trachea, blood vessels, etc. may be scanned, and the ribs near the chest and lungs may also be scanned. In other words, when the image data in a CT image reflects multiple diseases, it is necessary to further check and load the corresponding examination application for data processing, and it is necessary to clarify the multiple applications involved. For example, the sequence of manually loaded examinations contains the lesion "pulmonary nodule" and jumps to the pulmonary nodule specific pulmonary nodule application. If other lesions are found during the analysis process (such as arteriosclerosis of chest blood vessels), it is also necessary to exit the current pulmonary nodule application and load it into another chest blood vessel application to continue the analysis. It can be seen that it is impossible to provide comprehensive control over multiple diseases in the examination sequence, and it is easy for users to neglect other disease conditions that may be included in the examination sequence due to their stereotyped thinking. For example, a chest and lung scan may include multiple diseases such as rib fractures and pneumonia near the chest and lungs, and there are multiple applications that analyze these disease conditions respectively.

[0069] However, before loading, the user is not sure which application or applications to use. If an application is loaded incorrectly, the currently loaded application needs to be exited and a switch process to another application needs to be performed, resulting in low data processing efficiency.

[0070] By adopting the present disclosure, the inspection can be pre-calculated, that is, the target data to be loaded is identified to obtain the identification result. The pre-calculated data processing process can be launched after the film reading platform (such as PACS film reading system) receives the image (such as CT, MRI image, etc.) uploaded by the scanning device. The pre-calculated data processing process can use progressive analysis to obtain the identification result, so that when the user performs auxiliary diagnosis based on the identification result, for the inspection sequence composed of the identification result, an application corresponding to the inspection sequence and an application list composed of one or more applications can be automatically opened according to the pre-calculated result. Since there is no need to determine which application to use before loading, the user can select the best one or more applications in the application list, and there is no need to perform application switching processing, thereby improving data processing efficiency. For auxiliary diagnosis, it can save users the time cost of selecting applications. If there is only one application in the application list, they can jump directly to it. If there are multiple applications in the application list, users can choose from them without having to identify which examination sequence requires which application to select. It also provides a summary of the condition analysis of the examination to reduce users' diagnostic omissions. The pre-calculated data processing process also saves the time cost of real-time calculation in operating advanced applications (resource-consuming applications, such as applications for comprehensive analysis of multiple diseases).

[0071] Figure 1 A flow chart of a data loading method according to an embodiment of the present disclosure is shown. The method is applied to a data loading device. For example, when the processing device is deployed in a terminal device or a server or other processing device for execution, image classification, image detection, video processing, etc. can be performed. The terminal device may be a user equipment (UE), a mobile device, a cellular phone, a cordless phone, a personal digital assistant (PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, etc. In some possible implementations, the processing method may be implemented by a processor calling computer-readable instructions stored in a memory. For example, Figure 1 As shown, the process includes:

[0072] Step S101: Identify the target data to be loaded and obtain the identification result.

[0073] In one example, the target data to be loaded may be image data. The image data is not limited to the image data in the above-mentioned CT image or the image data in the MRI image, but may also include image data in the X-ray image, etc. As long as the image data can be obtained through radiation or computer imaging, it is within the protection scope of the present disclosure.

[0074] In one example, the image data is not limited to lung data, but can also be data of human organs and tissues such as brain data, heart data, liver data, spleen data, pancreas data, stomach / intestine data, kidney data, aorta and vein data.

[0075] In one example, the above-mentioned image data can be used as target data to be loaded, and feature extraction is performed on the target data to be loaded to obtain feature extraction results. Based on the feature extraction results, the body parts and / or organs corresponding to the target data are obtained, and the first set consisting of body parts and / or organs is used as the recognition result.

[0076] It should be pointed out that the recognition results disclosed in the present invention may be multiple, and may also include recognition results such as attribute information. For example, the image data may come from CT, MRI, X-ray, etc.; for example, for the attribute information, the image thickness may also be included (the image thickness may be 1 mm, etc.); for example, for the attribute information, whether intravenous fluid is used when scanning the patient; for example, for the attribute information, which scanning device is used to obtain the information; for example, for the attribute information, the scanning angle, scanning position and scanning depth; for example, for the attribute information, the clarity of the scanned image, etc. As long as the attribute information from the entire scanning process is involved, it is within the protection scope of the present invention.

[0077] Step S102: In response to the loading process of the target data, an application set corresponding to the target data is displayed according to the recognition result, and the application set includes at least one application.

[0078] In one example, the application set corresponding to the target data may include one or more applications, and the application set may be displayed in the form of an application list, or in the form of multiple application icons in a folder.

[0079] In the related technology, data (such as examination sequences) are loaded manually, and a certain examination sequence corresponds to a specific application, that is, a "one-to-one" relationship. However, a patient may suffer from multiple diseases and be reflected in an examination sequence, which is called a multi-disease situation. For example, a chest examination sequence may include possibilities such as lung nodules and chest fractures. On the one hand, manual data loading is inefficient; on the other hand, the "one-to-one" relationship cannot cover the various possibilities contained in the examination sequence. If it corresponds to a specific application for judgment and analysis, it is impossible to fully control multiple diseases and is prone to omissions.

[0080] By adopting the present disclosure, automatic data loading is realized, and the target data to be loaded can be identified to obtain the identification result. It is not necessary to determine which application to use before loading. Instead, in response to the loading process of the target data, an application set consisting of at least one application corresponding to the target data identification result (covering a "one-to-many" relationship) can be provided for the user to select the best one or more applications in the application set, and there is no need to perform application switching processing, thereby improving data processing efficiency. Moreover, the target data to be loaded is identified to obtain the identification result. Since the identification process is a data processing process pre-calculated before loading the application, the application can also be loaded in real time according to the pre-calculated result (i.e., the identification result), that is, the application set corresponding to the loaded data can be immediately displayed, further improving data processing efficiency.

[0081] Figure 2 A schematic diagram of an application list according to an embodiment of the present disclosure is shown as follows: Figure 2 As shown, multiple users can use their respective terminals (such as Figure 2 The PC terminal shown in the figure is connected to the film reading platform (such as a PACS film reading system) to obtain a continuously updated inspection sequence from the database of the server. The inspection sequence can be a CT image obtained based on chest and lung CT fluoroscopy. The inspection sequence can include: chest scan data, lung organ scan data, heart organ scan data, etc. With the present disclosure, the inspection sequence to be loaded is identified, and after the identification result is obtained, the application list is loaded in real time, that is, the application list corresponding to the automatically loaded inspection sequence can be immediately displayed. Optionally, the application list can include: lung nodule application, cardiac plaque application and chest rib fracture application, etc., to correspond to the inspection sequence of multiple diseases, provide users with multiple application options and automatically load the application list. The application currently selected by the user is the lung nodule application.

[0082] Figure 3A schematic diagram of a medical image data reading scene applied to image data according to an embodiment of the present disclosure is shown. Taking CT images as an example, CT images are medical image data obtained after tomographic imaging by using the characteristics of X-rays to produce different attenuation ray projections of organs and tissues of the human body. In terms of tomographic imaging, images can be reconstructed based on a collection obtained through countless projections, such as displaying the full picture of an organ or tissue through a collection of multiple layers, thereby avoiding the omission of lesions. CT images have a high density resolution, and the detection rate of subtle lesions with density changes is significantly improved. They can be enhanced by intravenous injection of contrast agents for further observation and identification, and the examination is fast and non-invasive. The image data in the CT image can be data for the surface of the human body cavity, or it can be the distribution of lesions that can be located inside or outside the surface of the cavity. The condition reflected by the image data in the CT image is not limited to one, and can be the condition of multiple diseases such as lung nodules, rib fractures, and vascular arteriosclerosis. For such multiple diseases, before loading a specific application for disease analysis, the target data to be loaded can be pre-identified to obtain an identification result. In response to the loading process of the target data, an application set consisting of at least one application corresponding to the target data identification result can be provided for the user to select the best one or more applications in the application set, without the need to perform application switching, thereby improving data processing efficiency. Moreover, it can at least provide auxiliary measures for subsequent disease diagnosis and surgical planning, so that the disease and lesion location can be accurately determined, and the lesion can be removed without destroying the tissue associated with the lesion information. Figure 3 As shown, the scene for CT image reading includes: an instrument 21 for scanning a human body, terminals for CT image reading (such as terminals 22-23), and a server (such as server 25) for providing data and computing support for the reading scene. After receiving the CT image obtained and uploaded by the instrument 21 (for example, multiple CT images can be obtained from different scanning angles, such as CT images 241-CT images 242 for the lungs), the terminals 22-23 can connect the terminals 22, 23 and the server 25 to a reading application that can be implemented by software or such as Figure 3 The film reading platform (such as a PACS film reading system) shown performs the following processing:

[0083] 1) Obtaining the inspection sequence to be loaded according to the image data in the CT image, identifying the inspection sequence, and obtaining the identification result.

[0084] 2) In response to the loading process of the inspection sequence, an application set corresponding to the inspection sequence is displayed according to the recognition result, and the application set includes at least one application.

[0085] In one embodiment, the identifying the target data to be loaded and obtaining the identification result may include: performing attribute analysis on the target data to be loaded to obtain an analysis result, obtaining attributes corresponding to the target data according to the analysis result, and using the second set of attributes as the above-mentioned identification result. The attributes may include: at least one of the data source, data type, imaging type, scanning type, and auxiliary information associated with the target data.

[0086] In one embodiment, before responding to the loading process of the target data, the method further includes: obtaining a search operation based on the target data, and then responding to the loading process of the target data includes: executing the loading process to load the target data.

[0087] In one embodiment, the target data is obtained from the preview interface, and when the application set is presented in the application interface, the application set corresponding to the target data is displayed according to the recognition result, including: jumping from the preview interface to the application interface according to the recognition result, displaying at least two applications corresponding to the target data in the application interface, and obtaining a selection strategy based on the analysis of at least two applications, so as to obtain an application currently recommended for use according to the selection strategy. The display method of the selection strategy includes at least one of an information prompt box and a voice prompt. For example, if the application list contains two applications, an information prompt for selecting one of the applications will pop up, thereby assisting the user in determining an accurate selection intention, which is faster and easier to use for the user.

[0088] In one embodiment, the target data is obtained from the preview interface, and when the application set is presented in the application interface, the application set corresponding to the target data is displayed according to the recognition result, including: jumping from the preview interface to the application interface according to the recognition result, and displaying an application corresponding to the target data in the application interface. For example, if the application list contains only one application, when the user double-clicks to open the check, the user can jump directly to the application without the user performing any selection operation, which can assist the user in determining the precise selection intention, which is faster and easier to use for the user.

[0089] Application examples:

[0090] In an application example of the present disclosure, it is applied to searching and observing diseases and their lesions in a CT image reading scenario. The data may be data on the surface of a human body's internal cavity, or the distribution of lesions that may be located inside or outside the surface of the internal cavity. The disease reflected by the image data in the CT image is not limited to one type (covering multiple diseases), and may be diseases of multiple types such as lung nodules, rib fractures, and vascular arteriosclerosis. For such a multi-disease condition, before loading a specific application for condition analysis, the target data to be loaded can be pre-identified to obtain an identification result. In response to the loading process of the target data, an application set consisting of at least one application corresponding to the target data identification result can be provided for the user to select the best one or more applications in the application set, without the need to perform application switching processing, thereby improving data processing efficiency and providing a richer data source for assisting users in diagnosing conditions and surgical planning analysis. In the processing process of this application example, for the multi-layer two-dimensional tomographic image data of the patient, a scanning device continuously monitors the data update status of the film reading platform (such as a PACS film reading system). Once new data is found to be incoming, the new data is synchronized, and the pre-calculated data processing logic is updated based on the new data, including the following contents:

[0091] 1. During the pre-calculated data processing, each inspection sequence of the inspection can be identified and calculated based on the above data to obtain the identification results of the body parts and organ sets contained in the inspection sequence. According to the body parts and organ sets contained in the inspection sequence, the analysis algorithm of specific parts and organs is used for pre-calculation. For example, according to different parts and organs, such as lungs, ribs, heart, etc., the lung nodule detection algorithm, rib segmentation algorithm, heart plate analysis algorithm and other algorithms are used to obtain the processing results for subsequent analysis of multiple diseases. The identification results and the processing results obtained by pre-calculation using various algorithms are stored in the database.

[0092] 2. When a user (such as a doctor) double-clicks to open the inspection sequence for auxiliary diagnosis operations, the database can be searched, and based on the above pre-calculation of the inspection (the recognition results and the processing results pre-calculated using various algorithms), an application list can be displayed. The application list can include one or more advanced applications. For example, if the inspection sequence includes chest scans, lung organs, heart organs, and analysis of lung nodules and heart plaques, the application list can provide lung nodule applications, heart plaque applications, etc., and provide brief information prompts to prompt users to select the most appropriate application. Usually the scan is performed for a specific type of disease, and it will be more effective and accurate to use one of the above algorithms corresponding to the specific disease for pre-calculation. Therefore, the application list may only include one application, so the user can jump directly to the application when double-clicking to open the inspection sequence.

[0093] By using this application example, when the user opens the examination sequence, the application list can be loaded and opened in real time according to the pre-calculated recognition results, thereby saving the time cost that the user may take to select the application, reducing the possibility of missing the condition analysis when there may be multiple diseases in the examination sequence, and saving the time cost of real-time calculation using each advanced application in the application list.

[0094] Those skilled in the art will appreciate that, in the above method of specific implementation, the order in which the steps are written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of the steps should be determined by their functions and possible internal logic.

[0095] The above-mentioned various method embodiments mentioned in the present disclosure can be combined with each other to form a combined embodiment without violating the principle logic. Due to space limitations, the present disclosure will not go into details.

[0096] In addition, the present disclosure also provides a data loading device, an electronic device, a computer-readable storage medium, and a program, all of which can be used to implement any data loading method provided by the present disclosure. The corresponding technical solutions and descriptions are referred to the corresponding records in the method part and will not be repeated here.

[0097] Figure 4 A block diagram of a data loading device according to an embodiment of the present disclosure is shown as follows: Figure 4 As shown, the processing device includes: a first processing unit 41, used to identify the target data to be loaded and obtain an identification result; a second processing unit 42, used to respond to the loading processing of the target data and display an application set corresponding to the target data according to the identification result, wherein the application set includes at least one application.

[0098] In one embodiment, the first processing unit is used to perform feature extraction on the target data to be loaded to obtain feature extraction results; based on the feature extraction results, the body parts and / or organs corresponding to the target data are obtained, and a first set consisting of the body parts and / or organs is used as the recognition result.

[0099] In one embodiment, the first processing unit is used to perform attribute analysis on the target data to be loaded to obtain an analysis result; obtain attributes corresponding to the target data based on the analysis result, and use a second set composed of the attributes as the recognition result.

[0100] In one embodiment, the attribute includes: at least one of a data source of the target data, a data type, an imaging type, a scanning type, and auxiliary information associated with the target data.

[0101] In one embodiment, the second processing unit is used to obtain a lookup operation based on the target data, execute the loading process, and load the target data.

[0102] In one embodiment, the second processing unit is used for jumping from the preview interface to the application interface based on the recognition result, when the target data is obtained from the preview interface and the application set is presented in the application interface, and displaying at least two applications corresponding to the target data in the application interface; obtaining a selection strategy based on the analysis of the at least two applications to obtain an application currently recommended for use according to the selection strategy; and displaying the selection strategy includes at least one of an information prompt box and a voice prompt.

[0103] In one embodiment, the second processing unit is used to jump from the preview interface to the application interface based on the recognition result when the target data is obtained from the preview interface and the application set is presented in the application interface, and an application corresponding to the target data is displayed in the application interface.

[0104] In some embodiments, the functions or modules included in the device provided by the embodiments of the present disclosure can be used to execute the method described in the above method embodiments. The specific implementation can refer to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0105] The present disclosure also provides a computer-readable storage medium on which computer program instructions are stored, and the computer program instructions implement the above method when executed by a processor. The computer-readable storage medium may be a volatile computer-readable storage medium or a non-volatile computer-readable storage medium.

[0106] The embodiments of the present disclosure also provide a computer program product, including a computer-readable code. When the computer-readable code is executed on a device, a processor in the device executes instructions for implementing the data loading method provided in any of the above embodiments.

[0107] The embodiment of the present disclosure also provides another computer program product for storing computer-readable instructions, which, when executed, enables a computer to perform the operations of the data loading method provided in any of the above embodiments.

[0108] The computer program product may be implemented in hardware, software or a combination thereof. In one optional embodiment, the computer program product is embodied as a computer storage medium, and in another optional embodiment, the computer program product is embodied as a software product, such as a software development kit (SDK) and the like.

[0109] The embodiment of the present disclosure further proposes an electronic device, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured as the above method.

[0110] The electronic device may be provided as a terminal, a server, or a device in other forms.

[0111] Figure 5 8 is a block diagram of an electronic device 800 according to an exemplary embodiment. For example, the electronic device 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, or the like.

[0112] Reference Figure 5 , the electronic device 800 may include one or more of the following components: a processing component 802 , a memory 804 , a power component 806 , a multimedia component 808 , an audio component 810 , an input / output (I / O) interface 812 , a sensor component 814 , and a communication component 816 .

[0113] The processing component 802 generally controls the overall operation of the electronic device 800, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the above-mentioned method. In addition, the processing component 802 may include one or more modules to facilitate the interaction between the processing component 802 and other components. For example, the processing component 802 may include a multimedia module to facilitate the interaction between the multimedia component 808 and the processing component 802.

[0114] The memory 804 is configured to store various types of data to support operations on the electronic device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phone book data, messages, pictures, videos, etc. The memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0115] The power supply component 806 provides power to the various components of the electronic device 800. The power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the electronic device 800.

[0116] The multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front camera and / or a rear camera. When the electronic device 800 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0117] The audio component 810 is configured to output and / or input audio signals. For example, the audio component 810 includes a microphone (MIC), and when the electronic device 800 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 804 or sent via the communication component 816. In some embodiments, the audio component 810 also includes a speaker for outputting audio signals.

[0118] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: home button, volume button, start button, and lock button.

[0119] The sensor assembly 814 includes one or more sensors for providing various aspects of status assessment for the electronic device 800. For example, the sensor assembly 814 can detect the open / closed state of the electronic device 800, the relative positioning of the components, such as the display and keypad of the electronic device 800, and the sensor assembly 814 can also detect the position change of the electronic device 800 or a component of the electronic device 800, the presence or absence of contact between the user and the electronic device 800, the orientation or acceleration / deceleration of the electronic device 800, and the temperature change of the electronic device 800. The sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0120] The communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices. The electronic device 800 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0121] In an exemplary embodiment, the electronic device 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above methods.

[0122] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 804 including computer program instructions, which can be executed by a processor 820 of an electronic device 800 to perform the above method.

[0123] Figure 6 is a block diagram of an electronic device 900 according to an exemplary embodiment. For example, the electronic device 900 may be provided as a server. Figure 6 , the electronic device 900 includes a processing component 922, which further includes one or more processors, and a memory resource represented by a memory 932 for storing instructions that can be executed by the processing component 922, such as an application. The application stored in the memory 932 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 922 is configured to execute instructions to perform the above method.

[0124] The electronic device 900 may also include a power supply component 926 configured to perform power management of the electronic device 900, a wired or wireless network interface 950 configured to connect the electronic device 900 to a network, and an input / output (I / O) interface 958. The electronic device 900 may operate based on an operating system stored in the memory 932, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™ or the like.

[0125] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 932 including computer program instructions, which can be executed by the processing component 922 of the electronic device 900 to perform the above method.

[0126] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0127] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0128] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0129] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0130] Various aspects of the present disclosure are described herein with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0131] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0132] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0133] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to multiple embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of the module, program segment or instruction includes one or more executable instructions for realizing the specified logical function. In some alternative implementations, the function marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of special hardware and computer instructions.

[0134] Different embodiments of the present application may be combined with each other without violating logic. The descriptions of different embodiments may have different emphases. For the emphasized parts, reference may be made to the records of other embodiments.

[0135] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A data loading method, characterized in that: The method comprises: Identify the target data to be loaded and obtain the identification result; In response to the loading process of the target data, displaying an application set corresponding to the target data according to the recognition result, the application set including at least one application; The target data to be loaded is identified to obtain an identification result, including: Performing attribute analysis on the target data to be loaded to obtain analysis results; According to the analysis result, attributes corresponding to the target data are obtained, and a second set consisting of the attributes is used as the recognition result; The attribute includes: at least one of an imaging type and a scanning type of the target data.

2. The method according to claim 1, characterized in that The target data to be loaded is identified to obtain an identification result, including: Performing feature extraction on the target data to be loaded to obtain a feature extraction result; The body parts corresponding to the target data are obtained according to the feature extraction result, and a first set consisting of the body parts is used as the recognition result.

3. The method according to claim 1, characterized in that The attributes further include: at least one of a data source of the target data, a data type, and auxiliary information associated with the target data.

4. The method according to any one of claims 1 to 3, characterized in that Before the loading process in response to the target data, the method further includes: Acquire a lookup operation based on the target data; The loading process in response to the target data includes: The loading process is executed to load the target data.

5. The method according to claim 4, characterized in that The target data is obtained from a preview interface, and when the application set is presented in an application interface, the application set corresponding to the target data is displayed according to the recognition result, including: According to the recognition result, jump from the preview interface to the application interface, and display at least two applications corresponding to the target data in the application interface; According to the analysis of the at least two applications, a selection strategy is obtained, so as to obtain an application currently recommended for use according to the selection strategy; The display mode of the selection strategy includes at least one of an information prompt box and a voice prompt.

6. The method according to claim 4, characterized in that The target data is obtained from a preview interface, and when the application set is presented in an application interface, the application set corresponding to the target data is displayed according to the recognition result, including: According to the recognition result, the preview interface is jumped to the application interface, and an application corresponding to the target data is displayed in the application interface.

7. A data loading device, characterized in that: The device comprises: The first processing unit is used to identify the target data to be loaded and obtain an identification result; a second processing unit, configured to, in response to the loading process of the target data, display an application set corresponding to the target data according to the recognition result, wherein the application set includes at least one application; The first processing unit is configured to: Performing attribute analysis on the target data to be loaded to obtain analysis results; According to the analysis result, attributes corresponding to the target data are obtained, and a second set consisting of the attributes is used as the recognition result; The attribute includes: at least one of an imaging type and a scanning type of the target data.

8. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; Wherein, the processor is configured to: execute the method described in any one of claims 1 to 6.

9. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the computer program instructions are executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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