Personalized video generation method, device, equipment and program product

Abstract

The invention provides a personalized video generation method, apparatus and device, and a program product. The method comprises the steps of obtaining an oral health examination report of a patient; extracting related data of the oral cavity abnormal area of the patient from the oral cavity health examination report; generating a personalized video according to the related data of the oral cavity abnormal region of the patient; the personalized video is used for interpreting related data of an abnormal region of the oral cavity of the patient. According to the method, the related data of the abnormal oral cavity area of the patient is interpreted by generating the personalized video, so that the patient can more easily understand the terminology in the oral cavity health examination report, and the personalized video can enable the patient to more easily and accurately understand the oral cavity health condition of the patient; and the acceptability and the understanding degree of the oral health information of the patient are improved.

Description

Technical Field

[0001] The present application belongs to the field of medical health technology, and in particular relates to a personalized video generation method, device, equipment and program product. Background Art

[0002] Currently, after receiving oral health examination reports, patients often do not have the patience to read them carefully, or they are difficult to understand because the reports contain some professional terms, resulting in patients being unable to accurately understand their own oral health status. Summary of the Invention

[0003] The embodiments of the present application provide a personalized video generation method, device, equipment and program product, which can solve the problem that patients currently do not have the patience to read oral health examination reports or cannot understand oral health examination reports, resulting in patients being unable to accurately understand their own oral health status.

[0004] In a first aspect, an embodiment of the present application provides a method for generating a personalized video, comprising:

[0005] Obtain oral health examination reports from patients;

[0006] Extracting relevant data of the patient's oral abnormal area from the oral health examination report;

[0007] A personalized video is generated based on the relevant data of the abnormal area of ​​the patient's oral cavity; the personalized video is used to interpret the relevant data of the abnormal area of ​​the patient's oral cavity.

[0008] In a possible implementation of the first aspect, generating a personalized video based on the relevant data of the abnormal oral area of ​​the patient includes:

[0009] Obtaining a lookup table, wherein the lookup table records the correspondence between the oral abnormality area and the cause of the oral abnormality area;

[0010] A first sub-segment of the personalized video is generated based on the cause of the abnormal oral area corresponding to the relevant data of the abnormal oral area of ​​the patient; the first sub-segment is used to provide scientific knowledge on the cause of the abnormal oral area of ​​the patient.

[0011] In a possible implementation of the first aspect, the lookup table further records the correspondence between the oral abnormality area and the treatment plan; and generating a personalized video based on the relevant data of the patient's oral abnormality area further includes:

[0012] A second sub-segment of the personalized video is generated based on the treatment plan corresponding to the relevant data of the abnormal area of ​​the patient's oral cavity; the second sub-segment is used to introduce the treatment plan.

[0013] In a possible implementation of the first aspect, when there are multiple treatment plans corresponding to the data related to the abnormal oral area of ​​the patient, generating the second sub-segment of the personalized video according to the treatment plans corresponding to the data related to the abnormal oral area of ​​the patient includes:

[0014] issuing an inquiry instruction, wherein the inquiry instruction is used to inquire the doctor to select a treatment plan suitable for the patient from the multiple treatment plans;

[0015] The treatment plan suitable for the patient selected by the doctor is received, and a second sub-segment of the personalized video is generated according to the treatment plan suitable for the patient.

[0016] In a possible implementation of the first aspect, the lookup table further records a correspondence between the abnormal oral area and the results of adopting a treatment plan and the consequences of not adopting the treatment plan; and generating a personalized video based on the relevant data of the abnormal oral area of ​​the patient further includes:

[0017] A third sub-segment of the personalized video is generated based on the results of adopting the treatment plan and the consequences of not adopting the treatment plan corresponding to the relevant data of the abnormal area of ​​the patient's mouth; the third sub-segment is used to explain and demonstrate the results of the patient adopting the treatment plan and the consequences of the patient not adopting the treatment plan.

[0018] In a possible implementation of the first aspect, the oral health examination report further includes a three-dimensional scan image of the patient's jaws and a three-dimensional scan image of the face; and when the relevant data of the abnormal oral area of ​​the patient includes an incorrect occlusion relationship of the patient, generating a personalized video based on the relevant data of the abnormal oral area of ​​the patient includes:

[0019] Determining the patient's jaw movement trajectory and the occlusal relationship based on the three-dimensional tooth and jaw scan image and the three-dimensional facial scan image;

[0020] A fourth sub-segment of the personalized video is generated based on the patient's jaw movement trajectory and the occlusion relationship; the fourth sub-segment is used to explain and demonstrate the patient's jaw movement trajectory and the occlusion relationship, as well as the correct jaw movement trajectory and the occlusion relationship.

[0021] In a possible implementation of the first aspect, generating a personalized video based on the relevant data of the abnormal oral area of ​​the patient includes:

[0022] Obtaining a video database; the video database contains a plurality of video clips, each of which corresponds to the cause of the abnormal oral area, the treatment plan, the result of adopting the treatment plan, the consequence of not adopting the treatment plan, the jaw movement trajectory, and the occlusal relationship;

[0023] determining one or said video segments corresponding to data related to an abnormal area of ​​said patient's oral cavity;

[0024] The personalized video is generated according to the one or more video clips.

[0025] In a possible implementation of the first aspect, the method further includes:

[0026] Obtain the patient's age;

[0027] Determining a target video template according to the age of the patient; the target video template is one of a plurality of video templates, and different video templates correspond to different styles;

[0028] Generate a personalized video based on the relevant data of the patient's oral abnormal area, including:

[0029] The personalized video is generated based on the relevant data of the abnormal area of ​​the patient's oral cavity and the target video template.

[0030] In a possible implementation of the first aspect, the method further includes:

[0031] Recording behavioral data of the patient watching the personalized video, wherein the behavioral data includes one or more of: fast forward, skip, slow play, replay, questioning, and screenshot;

[0032] The patient's treatment willingness is determined based on the behavioral data.

[0033] In a possible implementation of the first aspect, the method further includes:

[0034] Obtaining oral health examination reports of the patient at different times, wherein the plurality of oral health examination reports each include a first three-dimensional scan image;

[0035] Extracting one or more characteristic parameters for characterizing the abnormal area of ​​the oral cavity from the plurality of the first three-dimensional scan images;

[0036] Predicting the evolution information of the oral state through a prediction model based on one or more characteristic parameters of the oral abnormality area;

[0037] An evolution video of the abnormal area of ​​the oral cavity is generated based on the evolution information of the oral cavity state and the first three-dimensional scanning image.

[0038] In a second aspect, an embodiment of the present application provides a personalized video generation device, including:

[0039] An acquisition module is used to obtain the patient's oral health examination report;

[0040] An extraction module, configured to extract relevant data of the patient's oral abnormal area from the oral health examination report;

[0041] The personalized video generation module is used to generate a personalized video based on the relevant data of the abnormal area of ​​the patient's oral cavity; the personalized video is used to interpret the relevant data of the abnormal area of ​​the patient's oral cavity.

[0042] In a third aspect, an embodiment of the present application provides an electronic device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in any one of the first aspects when executing the computer program.

[0043] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method as described in any one of the first aspects is implemented.

[0044] In a fifth aspect, an embodiment of the present application provides a computer program product, which, when executed on an electronic device, enables the electronic device to execute any one of the methods described in the first aspect above.

[0045] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here.

[0046] The beneficial effects of the embodiments of the present application compared with the prior art are: the embodiments of the present application generate personalized videos to interpret the relevant data of abnormal areas of the patient's oral cavity, making it easier for patients to understand the professional terms in the oral health examination report, and the personalized videos can make patients understand their own oral health status more easily and accurately, thereby improving patients' acceptance and understanding of oral health information. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0048] Figure 1This is a flowchart of a personalized video generation method provided by an embodiment of the present application;

[0049] Figure 2 It is a structural diagram of a personalized video generation device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0050] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present application with unnecessary detail.

[0051] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0052] It will also be understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0053] As used in this specification and the appended claims, the term "if" can be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0054] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0055] References to "one embodiment" or "some embodiments" in this specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present application. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0056] Figure 1 A schematic flow chart of a personalized video generation method provided by the present application is shown, which is an example and not a limitation. The method can be applied to electronic devices with screens, such as mobile phones, computers, tablets, televisions, etc. The method includes S110-S130.

[0057] S110: Obtain the patient's oral health examination report.

[0058] Optionally, the electronic device obtains the patient's electronic oral health examination report from the hospital's oral health examination system through scanning or data interface. The oral health examination report is a document containing a variety of information such as text, charts, three-dimensional scanned images, etc., which records the patient's basic information (name, gender, age, medical record number, etc.) and examination items (such as gum color and morphology examination, tooth color and morphology examination, probing examination, bite examination, percussion examination, model analysis, X-ray examination, etc.). For example, the oral health examination report can also record the patient's habit data (such as brushing frequency, eating habits, smoking, drinking, etc.), historical disease data (such as whether there is diabetes, whether there is a history of gingivitis in the family, etc.).

[0059] S120: Extract relevant data of abnormal areas of the patient's oral cavity from the oral health examination report.

[0060] Specifically, relevant data of abnormal areas of the patient's oral cavity can be extracted from the oral health examination report, and normal data can also be extracted.

[0061] For example, the extracted data of abnormal areas of the patient's oral cavity are as follows:

[0062] Dental caries: The upper left first molar (tooth row number 26) has shallow caries;

[0063] Periodontal: Slightly red and swollen gums, positive bleeding on probing (BOP), periodontal pocket depth 2-3mm;

[0064] Dental calculus: There is a small amount of dental calculus in the lower front teeth area and the upper and lower molar areas, and the dental calculus is deep into the gums;

[0065] Oral hygiene: Oral hygiene is average, with a high plaque index (PLI);

[0066] Occlusion: Mandibular retrusion, upper front teeth overly covering lower front teeth.

[0067] For example, the data of the patient's oral abnormality area can be sorted according to a preset rule, and the top three relevant data can be selected according to priority. The preset rule can be a comprehensive score based on severity, tooth location, and the impact of the patient's own disease on the oral disease.

[0068] S130: Generate a personalized video based on the relevant data of the abnormal area of ​​the patient's oral cavity; the personalized video is used to interpret the relevant data of the abnormal area of ​​the patient's oral cavity.

[0069] For example, regarding dental caries: a 3D animation is used to show the position of the upper left first molar (26), and the animation is used to demonstrate the formation process of shallow dental caries and the harm of dental caries.

[0070] For periodontal disease: Use animation to demonstrate the symptoms of red and swollen gums and bleeding on probing, explain the causes of periodontal pockets, and the dangers of gingivitis.

[0071] Regarding dental tartar: Use pictures or animations to show the shape of dental tartar in the lower front teeth area, explain the harm of dental tartar, and how to remove dental tartar through teeth cleaning.

[0072] For oral hygiene: Use animations to demonstrate the correct brushing and flossing techniques, and provide personalized oral hygiene recommendations based on the patient's plaque index.

[0073] Conclusion: Patients are advised to have regular checkups (e.g., every 6 months).

[0074] The embodiment of the present application generates personalized videos to interpret the relevant data of abnormal areas of the patient's oral cavity, making it easier for patients to understand the professional terms in the oral health examination report. The personalized videos can enable patients to understand their own oral health status more easily and accurately, thereby improving patients' acceptance and understanding of oral health information.

[0075] As an optional implementation, S130: generating a personalized video based on relevant data of the abnormal area of ​​the patient's oral cavity, including S131-S132.

[0076] S131: Obtain a lookup table, which records the correspondence between the oral abnormality area and the causes of the oral abnormality area.

[0077] Optionally, a lookup table is stored in the electronic device or in the cloud, and the lookup table contains the correspondence between abnormal oral areas and their causes.

[0078] For example, a partial lookup table is as follows:

[0079]

[0080] S132: Generate a first sub-segment of a personalized video based on the cause of the abnormal oral area corresponding to the relevant data of the abnormal oral area of ​​the patient; the first sub-segment is used to provide scientific knowledge on the cause of the abnormal oral area of ​​the patient.

[0081] Exemplarily, the first sub-segment includes:

[0082] The "Causes of Tooth Decay" sub-segment uses animation to demonstrate how bacteria form plaque on tooth surfaces. It explains how sugar promotes bacterial growth and how structural defects in teeth increase the risk of tooth decay. This segment also personalizes the information based on the patient's age and lifestyle, such as "You enjoy sugary drinks, which may increase your risk of tooth decay."

[0083] The "Gingivitis Causes" segment uses animation to illustrate the irritation of plaque and tartar on gums and emphasizes the importance of oral hygiene. It also provides personalized reminders based on the patient's oral hygiene status, such as "Your high plaque index indicates you need to improve oral hygiene."

[0084] The reason why dental tartar is formed is shown in the animation. The bacteria in the dental plaque produce acidic substances, which destroy the minerals on the surface of the teeth. At the same time, they also cause calcium, phosphorus and other minerals in the mouth to be deposited on the dental plaque, gradually forming dental tartar.

[0085] Compared to existing oral health examination reports that simply inform patients of certain oral abnormalities, this embodiment can help patients understand the causes of the disease, thereby gaining a more comprehensive understanding of their oral health issues. By understanding the causes of the disease, patients can more specifically change their unhealthy lifestyle habits, effectively preventing the disease from occurring. Furthermore, understanding the causes of the disease helps patients better cooperate with the doctor's treatment plan, thereby improving treatment effectiveness.

[0086] As an optional implementation, the lookup table also records the correspondence between the abnormal oral area and the treatment plan; S130: generating a personalized video based on the relevant data of the patient's abnormal oral area, also including S133.

[0087] S133: Generate a second sub-segment of the personalized video based on the treatment plan corresponding to the relevant data of the abnormal area of ​​the patient's oral cavity; the second sub-segment is used to introduce the treatment plan.

[0088] For example, a partial lookup table is as follows:

[0089]

[0090] Exemplarily, the second sub-segment includes:

[0091] Caries treatment plan segment: Introduces the treatment plan for shallow caries, namely filling treatment, and demonstrates the filling treatment process through animation.

[0092] Gingivitis treatment plan segment: Introducing supragingival scaling and demonstrating the ultrasonic scaling process through animation.

[0093] Dental tartar treatment plan segment: This segment explains the location of supragingival and subgingival tartar and demonstrates the supragingival and subgingival scaling processes through animation. It also provides advice on regular teeth cleaning.

[0094] In this example, by introducing the treatment plan through a video, patients have a clearer understanding of the treatment process and can better understand the doctor's treatment recommendations, thereby improving treatment compliance. Patients are more willing to follow the treatment plan and reduce resistance caused by lack of understanding of the treatment.

[0095] As an optional implementation, when there are multiple treatment plans corresponding to the relevant data of the abnormal oral area of ​​the patient, S133: generate a second sub-segment of the personalized video according to the treatment plans corresponding to the relevant data of the abnormal oral area of ​​the patient, including S1331-S1332.

[0096] S1331: Issue an inquiry instruction, which is used to ask the doctor to select a treatment plan suitable for the patient from multiple treatment plans.

[0097] S1332: Receive a treatment plan suitable for the patient selected by the doctor, and generate a second sub-segment of the personalized video based on the treatment plan suitable for the patient.

[0098] When multiple oral abnormality areas affect each other, resulting in multiple treatment plans, it may not be possible to provide the most suitable treatment plan for the patient through the lookup table alone. For example, in the case of a patient with both dental calculus and gingival hyperplasia, the lookup table will provide an unclear treatment plan, such as "gingivectomy may be required". At this time, it is necessary to use the doctor's experience and judgment to select a treatment plan suitable for the patient. It should be noted that in this embodiment, for areas with oral abnormalities of different degrees, such as caries, which can be divided into shallow caries, medium caries and deep caries according to the severity, and the lookup table has treatment plans corresponding to different severity levels, there is no need to issue a query instruction. In another embodiment, for the accuracy of the treatment plan, a confirmation instruction may also be issued. The confirmation instruction is used to confirm with the doctor whether the treatment plan is correct. The doctor will review it and then use it as the generated data for the second sub-segment.

[0099] As an optional embodiment, the lookup table also records the correspondence between the oral abnormality area and the results of taking the treatment plan and the consequences of not taking the treatment plan. Accordingly, S130: generating a personalized video based on the relevant data of the patient's oral abnormality area also includes S134.

[0100] For example, a partial lookup table is as follows:

[0101]

[0102]

[0103] S134: Generate a third sub-segment of the personalized video based on the results of adopting the treatment plan and the consequences of not adopting the treatment plan corresponding to the relevant data of the abnormal area of ​​the patient's oral cavity; the third sub-segment is used to explain and demonstrate the results of the patient adopting the treatment plan and the consequences of the patient not adopting the treatment plan.

[0104] Exemplarily, the third sub-segment includes:

[0105] Caries sub-segment: An animation shows the appearance of teeth after caries treatment; another shows how untreated caries can worsen, leading to pulpitis and ultimately requiring extraction. The animations are accompanied by audio commentary.

[0106] Gingivitis sub-segment: An animation shows how gum inflammation subsides, bleeding stops, and plaque decreases in the mouth. Another animation shows how gum inflammation worsens and develops into periodontitis, leading to loose teeth and tooth loss. The animations are accompanied by audio commentary.

[0107] Dental tartar sub-clips: An animation showing how gum inflammation subsides and gum bleeding stops after dental tartar is removed; and scenes showing how the continuous accumulation of dental tartar leads to gum atrophy, alveolar bone absorption, loose teeth until they fall out, and causes bad breath and periodontal abscesses.

[0108] This embodiment integrates the results of adopting the treatment plan and the consequences of not adopting the treatment plan into a third sub-segment, which allows patients to more intuitively compare the differences between the two, enhances patients' awareness of the necessity of treatment, and thus increases patients' willingness to receive treatment.

[0109] As an optional embodiment, the oral health examination report also includes a three-dimensional scanning image of the patient's teeth and jaws and a three-dimensional scanning image of the face; when the relevant data of the abnormal area of ​​the patient's mouth includes incorrect occlusion of the patient, S130: generate a personalized video based on the relevant data of the abnormal area of ​​the patient's mouth, including: S135-S136.

[0110] S135: Determine the patient's jaw movement trajectory and occlusal relationship based on the three-dimensional dental and maxillary scan images and the three-dimensional facial scan images.

[0111] Optionally, the three-dimensional dental scan image is obtained by scanning the patient's oral cavity with an oral scanner, and the three-dimensional facial scan image is obtained by scanning the patient's face with a facial scanner.

[0112] S136: Generate a fourth sub-segment of the personalized video based on the patient's jaw movement trajectory and occlusion relationship; the fourth sub-segment is used to explain and demonstrate the patient's jaw movement trajectory and occlusion relationship, as well as the correct jaw movement trajectory and occlusion relationship.

[0113] For example, the screen displays a three-dimensional scan image of the patient's jaws and a three-dimensional scan image of the face, and uses animation to simulate the movement trajectory of Ms. Wang's jaw to show her incorrect occlusion, that is, the mandible is retracted and the upper front teeth excessively cover the lower front teeth. In addition, the correct or corrected jaw movement trajectory is simulated through animation to show the correct occlusion, including: even contact between the upper and lower teeth and smooth movement of the jaw. In the process of showing the animation, the video explains that the patient has a deep overbite, commonly known as "buck teeth", and the dangers of deep overbite (such as deep overbite will lead to restricted mandibular movement, increased pressure on the temporomandibular joint, which may cause temporomandibular joint disorder in the long term, and will also affect the patient's facial beauty).

[0114] This embodiment uses animations and videos to explain the patient's jaw movement trajectory and occlusion, allowing patients to more intuitively and clearly see their problems, making it easier to understand than traditional text or image descriptions. Because the fourth sub-segment is generated based on the patient's scan image, the content of each patient's fourth sub-segment is unique, accurately reflecting the patient's actual situation and meeting their personalized needs.

[0115] As an optional implementation, S130: generating a personalized video based on relevant data of the abnormal area of ​​the patient's oral cavity, including: S137-S139.

[0116] S137: Obtain a video database; the video database contains multiple video clips, and the video clips have corresponding relationships with the causes of the abnormal oral area, treatment plans, results of taking the treatment plan, consequences of not taking the treatment plan, jaw movement trajectories, and occlusal relationships.

[0117] Exemplarily, each video clip in the video database has a unique identifier, or can be searched by keywords. For example, the keyword "shallow caries" corresponds to the first video clip in the video database, the keyword "medium caries" corresponds to the second video clip in the video database, the keyword "deep caries" corresponds to the third video clip in the video database, the keyword "shallow caries-treatment plan" corresponds to the fourth video clip in the video database, the keyword "shallow caries-treatment plan-treatment results" corresponds to the fifth video clip in the video database, the keyword "shallow caries-treatment plan-consequences of no treatment" corresponds to the sixth video clip in the video database, the keyword "slightly red and swollen gums" corresponds to the seventh video clip in the video database, and so on.

[0118] S138: Determine one or more video segments corresponding to data related to the abnormal area of ​​the patient's oral cavity.

[0119] For example, if the patient's oral abnormal areas include shallow caries and slightly red and swollen gums, then the video clips corresponding to the patient's oral abnormal areas can be determined to include the first video clip, the fifth video clip, the sixth video clip, and the seventh video clip.

[0120] S139: Generate a personalized video based on one or more video clips.

[0121] Exemplarily, the first video clip, the fifth video clip, the sixth video clip, and the seventh video clip are spliced ​​together to obtain a personalized video.

[0122] This embodiment utilizes a video database to efficiently generate personalized videos, providing patients with easy-to-understand oral health information, improving their treatment compliance and oral health awareness, and thus improving their oral health. This method can significantly reduce the production cost of personalized videos, making them easier to promote and apply.

[0123] As an optional implementation, existing video generation technology can also be used to generate personalized videos based on the semantic information of relevant data of the patient's oral abnormal area.

[0124] As an optional implementation, the personalized video generation method further includes: S140-S150.

[0125] S140: Get the patient's age.

[0126] Specifically, the oral health examination report includes the patient's age information.

[0127] S150: Determine a target video template according to the patient's age; the target video template is one of multiple video templates, and different video templates correspond to different styles.

[0128] For example, the electronic device may pre-store multiple video templates, or the cloud may include multiple video templates, each corresponding to a different age group and style. For example:

[0129] Children's template (0-12 years old): Animation style, bright colors, lively dubbing, simple and easy-to-understand content, and no images that may make children feel uncomfortable.

[0130] Teen template (13-18 years old): cartoon style, fast pace, fashionable dubbing, content focusing on beauty and social interaction.

[0131] Youth template (19-35 years old): simple style, soft colors, professional dubbing, and content focusing on practicality and scientificity.

[0132] Middle-aged template (36-55 years old): mature style, steady colors, calm voice-over, and content focusing on health and prevention.

[0133] Senior template (over 56 years old): traditional style, simple colors, friendly voice-over, and content emphasizing comfort and safety.

[0134] If the target video template is a youth template, use the youth template's color scheme and fonts, transition effects and animation effects, and professional dubbing.

[0135] Exemplarily, there are multiple video templates corresponding to each video clip in the video database. For example, the first video clip corresponding to "shallow caries" has a child template, a teenager template, a youth template, a middle-aged template, and an elderly template.

[0136] Correspondingly, S130 generates a personalized video based on the relevant data of the abnormal oral area of ​​the patient, including: generating a personalized video based on the relevant data of the abnormal oral area of ​​the patient and a target video template.

[0137] This embodiment selects different video templates according to the patient's age, which can make the style of personalized videos more in line with the patient's preferences, improve the attractiveness and acceptance of the video, thereby more effectively conveying oral health information and improving the patient's oral health status.

[0138] For example, if the patient is a child, a cartoon-style personalized video corresponding to the patient can be generated based on the patient's three-dimensional dental and maxillary scan image and / or three-dimensional facial scan image and the corresponding target video template.

[0139] As an optional implementation, the personalized video generation method further includes: S160-S170.

[0140] S160: Recording behavioral data of the patient watching the personalized video, where the behavioral data includes one or more of: fast forward, skip, slow motion, replay, questioning, and screenshot.

[0141] S170: Determine the patient's treatment intention and / or retrieve a corresponding sub-segment of the personalized video based on the behavioral data.

[0142] Specifically, when a patient watches a personalized video, if the patient replays a clip about a treatment method for a certain oral abnormal area in the personalized video multiple times, and does not fast-forward or skip during the playback process, this may indicate that the patient is more concerned about the treatment method and has a higher willingness to treat. If the patient frequently fast-forwards or skips while watching the video, especially skipping treatment-related content, it may indicate that the patient is not very interested in the treatment and has a lower willingness to treat. In addition, if the patient asks detailed questions about the treatment plan, such as the cost, course of treatment, side effects, etc., this can also serve as a reference that the patient has a strong willingness to treat. The electronic device will comprehensively analyze these behavioral data according to preset rules and algorithms, and ultimately determine the patient's willingness to treat. It can also present the treatment willingness in a quantitative form (such as a treatment willingness index).

[0143] During the video tutorial, the electronic device can also capture the patient's voice questions and use semantic recognition to conduct consultations and recommendations. The electronic device uses medical semantic algorithms, such as semantic dictionaries and similarity matching, to determine the patient's intent.

[0144] In addition, the corresponding sub-segment of the personalized video can be retrieved based on the patient's behavioral data. For example, the title of the content pointed to in the screen or the type of disease corresponding to the abnormal area of ​​the oral cavity in the three-dimensional scan image of the jaw can be determined based on the position where the finger or stylus is hovering, and then the corresponding sub-segment of the personalized video can be retrieved. This involves capturing the user's touch points and the current screen content being explained, locating the touch points from the screen content, and retrieving the corresponding content for explanation. During the explanation process, if the electronic device detects that the user stays on a certain screen for a long time, a pop-up window can be popped up to prompt the user to explain the content corresponding to the stopped screen (which can be a text explanation or a video explanation).

[0145] By recording patients' video viewing behavior and analyzing their treatment preferences, this embodiment allows doctors to more accurately understand their attitudes and needs for treatment. This helps doctors provide more personalized treatment recommendations, avoiding the potential blindness of traditional treatment plans.

[0146] In order to enable patients to intuitively understand the evolution of the disease and enhance their understanding and cooperation with the treatment plan, the evolution of the oral condition can be predicted based on the patient's dental and maxillary 3D scanning images and / or facial 3D scanning images, and an evolution video can be generated to enable patients to understand the necessity of treatment.

[0147] As an optional implementation, the method also includes S181-S184.

[0148] S181: Obtain oral health examination reports of the patient at different times, where each of the multiple oral health examination reports includes a first three-dimensional scan image.

[0149] Specifically, the first three-dimensional scanning image is a three-dimensional model obtained by scanning the patient's oral surface with an oral three-dimensional scanner, and the first three-dimensional scanning image is in color. The first three-dimensional scanning image can reflect the specific condition of the patient's oral cavity, such as whether there is tooth loss, whether there is mucosal abnormality, whether there is dentition, whether there is dental calculus, whether there is periodontitis, whether there is tooth occlusal surface wear, whether there is gum atrophy, etc.

[0150] S182: Extracting one or more characteristic parameters for characterizing the abnormal area of ​​the oral cavity from the plurality of first three-dimensional scan images.

[0151] S183: Predicting the evolution information of the oral state through a prediction model based on one or more characteristic parameters of the oral abnormality area.

[0152] S184: Generate an evolution video of the abnormal area of ​​the oral cavity based on the evolution information of the oral cavity state and the first three-dimensional scanning image.

[0153] Evolutionary videos can intuitively display the changing process of oral conditions, helping doctors and patients better understand the evolutionary information of the disease. They can also enhance patients' attention to their oral conditions and increase their willingness to receive treatment.

[0154] As an optional implementation, when the oral health examination report includes tooth loss, S182 includes S1821-S1822.

[0155] S1821: Determine the time interval between adjacent first three-dimensional scan images.

[0156] Specifically, the time interval between adjacent first 3D scan images is the time interval between two temporally adjacent oral health examination reports. For example, assuming there are three first 3D scan images acquired at times t0, t1, and t2, the time intervals between adjacent first 3D scan images are ΔT1 and ΔT2, where ΔT1 = t1 - t0 and ΔT2 = t2 - t1.

[0157] S1822: Extracting one or more characteristic parameters for characterizing the missing tooth from the plurality of first three-dimensional scan images; the characteristic parameters of the missing tooth include: the type and position of the missing tooth, the long axis of the tooth adjacent to the missing tooth, and the height and shape of the alveolar bone surrounding the missing tooth.

[0158] If a missing tooth is not replaced for a long time, the adjacent teeth will move closer to the gap and the position of the adjacent teeth will change. The speed of the adjacent teeth's tilting will vary significantly depending on the type of missing tooth.

[0159] By analyzing multiple first three-dimensional scan images, the type and position of the missing teeth can be identified. Optionally, the type and position of the missing teeth can be identified in the following manner: each tooth in the three-dimensional scan image is segmented to form an independent individual. The tooth position number and position of each tooth are identified to obtain the patient's dentition. Based on the dentition data of a normal person, a standard dentition model is established. The patient's dentition is compared with the normal dentition model to identify the type and position of the missing teeth, wherein the type of tooth can be determined based on the tooth position number.

[0160] The adjacent teeth of a missing tooth include the teeth on either side of the missing tooth. This may be one tooth, such as a third molar at the back of the dentition, which has only one adjacent tooth. Alternatively, there may be two adjacent teeth, such as a third molar, which has two adjacent teeth. The long axis of a tooth is the geometric axis running longitudinally through the tooth and passing through its center.

[0161] By analyzing multiple first three-dimensional scanning images, using a regional segmentation model or a geometric feature recognition model to identify the alveolar bone area, then measuring the alveolar bone area, measuring the height of the alveolar bone, and analyzing its morphological characteristics, it can be determined whether the patient has bone absorption, bone defects, etc.

[0162] The corresponding S183 includes S1831-S1832.

[0163] S1831: Determine change information of characteristic parameters around the missing tooth based on the time interval between adjacent first three-dimensional scanning images and one or more characteristic parameters of the missing tooth; the change information of characteristic parameters around the missing tooth includes: at least one of the tilting speed of the adjacent teeth of the missing tooth, the displacement speed of the adjacent teeth of the missing tooth, and the absorption speed of the alveolar bone around the missing tooth.

[0164] For the adjacent tooth of a missing tooth, by comparing the long axis of the adjacent tooth in two adjacent first 3D scan images (assuming the time interval is ΔT1), the change in the angle of the long axis of the tooth within ΔT1 can be calculated. This change in angle is the tilt angle of the adjacent tooth within ΔT1. By combining ΔT1 and the tilt angle of the long axis of the tooth, the tilt speed of the adjacent tooth within ΔT1 can be accurately calculated. If there are more than three first 3D scan images based on the time series, it can also be determined whether the tilt speed of the adjacent tooth is uniform, accelerating, or decelerating.

[0165] By marking specific points of adjacent teeth in multiple first 3D scan images, comparing the position changes of these points in adjacent first 3D scan images, calculating the displacement, and then dividing it by the time interval, the displacement speed of the adjacent teeth can be obtained.

[0166] The height and morphological changes of the alveolar bone around the missing teeth in adjacent images were compared, and the height and morphological changes were divided by the time interval to obtain the alveolar bone resorption rate.

[0167] S1832: Based on the change information of the characteristic parameters around the missing tooth, the evolution information around the missing tooth is predicted by a prediction model; the evolution information around the missing tooth includes: at least one of the future tilting speed of the adjacent teeth of the missing tooth, the future displacement speed of the adjacent teeth of the missing tooth, and the future alveolar bone absorption speed around the missing tooth.

[0168] Since the prediction model learns the rules and patterns of tooth tilting in the oral cavity, it uses the currently calculated tilting speed of the adjacent teeth of the missing teeth, the displacement speed of the adjacent teeth of the missing teeth, and the alveolar bone absorption speed around the missing teeth as input. The prediction model can predict the future tilting speed of the adjacent teeth, the displacement speed of the adjacent teeth of the missing teeth, and the future alveolar bone absorption speed around the missing teeth, helping doctors to formulate treatment plans in advance and avoid more serious oral problems caused by excessive tilting of adjacent teeth.

[0169] This embodiment, targeting the common oral problem of missing teeth, extracts one or more characteristic parameters of the missing tooth and calculates the changes in the surrounding characteristic parameters. This accurately assesses the impact of the missing tooth on adjacent teeth and alveolar bone, providing a scientific basis for developing personalized treatment plans. For patients who have not prioritized missing teeth, learning about the future tendency of their teeth to tilt will increase their focus on oral health and encourage them to actively cooperate with their doctor's treatment and oral care recommendations, thereby improving the quality of their oral health management.

[0170] As an optional embodiment, if the oral health examination report also includes mucosal abnormalities, the method further includes S185-S1187.

[0171] S185: Determine the location and area of ​​the abnormal mucosal region in the plurality of first three-dimensional scan images.

[0172] Healthy gums appear smooth, continuous, and closely aligned with the teeth in 3D scans. However, when the gums are abnormal, they may appear swollen, red, or have white or red spots. Images may show thickened and uneven gum margins, blunted gingival papillae, and even gum recession, partially exposing the tooth roots. The color and shape of the gums can be used to determine the location and extent of oral inflammation.

[0173] Mucosal abnormalities usually mean that the patient has oral inflammation, including gingivitis, periodontitis, periodontal abscess, apical periodontitis, etc.

[0174] Specifically, by analyzing the mucosal area of ​​the first three-dimensional scan image through analysis software, the abnormal mucosal area can be determined by color and shape, and the classification model can be used to determine whether the abnormal mucosal area is oral inflammation, as well as the location and area of ​​the oral inflammation.

[0175] S186: Determine evolution information of the abnormal mucosal region according to the time interval between adjacent first three-dimensional scan images and the position and area of ​​the abnormal mucosal region.

[0176] Compare the location and area of ​​the mucosal abnormality between two adjacent first 3D scan images. If the location of the abnormality changes, record its direction and distance of movement. If the area changes, calculate the area difference. Divide the area change by the time interval between the adjacent images to determine the rate of change in the area of ​​the abnormality.

[0177] The rate of change in area and location can be used to determine the evolution of the mucosal abnormality. If the area continues to increase and shows signs of spreading, the abnormality is considered to be in the developing stage; if the area gradually decreases, the abnormality is considered to be in the improving stage.

[0178] S187: Determine the timing for dental implantation based on the evolutionary information of the abnormal mucosal area and the evolutionary information around the missing tooth.

[0179] Dental implant surgery requires a stable oral environment. The development of mucosal abnormalities and structural changes surrounding missing teeth can affect the success rate of implant surgery. Taking these two factors into consideration can help determine the optimal implant placement time, improve the success rate, and reduce the occurrence of postoperative complications.

[0180] Comprehensively consider the evolutionary information of mucosal abnormalities and the evolutionary information around the missing teeth. If the mucosal abnormality is in the development stage, and the adjacent teeth of the missing teeth are tilting faster and the alveolar bone absorption rate is also faster, it means that the oral environment is unstable and it is not suitable for dental implant surgery at this time. The mucosal abnormality needs to be treated first. For example, if the mucosal inflammation is gingivitis, it is necessary to control the development of the inflammation first, and wait for the oral inflammation to enter the stable period before considering dental implant surgery. When oral inflammation enters the stable period, that is, the area no longer increases or even has a decreasing trend, and the adjacent teeth tilting rate and alveolar bone absorption rate around the missing teeth slow down to a certain extent (for example, the adjacent teeth tilting rate is less than 1° / month, and the alveolar bone absorption rate is less than 0.5 mm / month), it can be considered that the oral environment is relatively stable, and dental implant surgery can be considered at this time.

[0181] Based on the evolution of mucosal abnormalities and the surrounding area of ​​the missing tooth, a predictive model is used to determine the specific time for dental implant placement. For example, an implant surgery is expected to be performed one month after gingivitis has stabilized. In another embodiment, the doctor can also determine the specific time for dental implant placement based on the evolution of gingivitis and the surrounding area of ​​the missing tooth.

[0182] This embodiment accurately assesses the evolution of mucosal abnormalities and the surrounding area of ​​missing teeth, allowing the implant procedure to be performed when the oral environment is stable. This reduces surgical risk and improves implant stability and success rates. Furthermore, this embodiment tailors the timing of implant placement to each patient's specific medical condition and oral condition, enabling personalized treatment plans that better meet their needs.

[0183] As an optional implementation, the method also includes S188-S190.

[0184] S188: Before implanting missing teeth, determine the three-dimensional model of the implant effect of the missing teeth.

[0185] Specifically, before a patient receives a dental implant, adjustments are made to the first 3D scan image. This includes filling in missing teeth (i.e., implants) in the first 3D scan image, adjusting the position of adjacent teeth, and abrading adjacent teeth based on occlusion to create a 3D model of the implanted effect. Furthermore, the implant is designed to match the adjacent teeth based on their size, shape, and color.

[0186] S189: Obtain a second three-dimensional scan image of the patient's oral cavity after implantation of missing teeth.

[0187] During dental implant surgery, the surgeon first cuts the gums to expose the alveolar bone. A socket is then prepared in the alveolar bone, and the implant is placed. The cut gum tissue is then repositioned and sutured. Immediately after the missing tooth implant surgery is complete, or after a healing period, the patient's oral cavity is scanned again using an oral scanner to obtain a second 3D scan.

[0188] S190: Determine the degree of restoration of the missing tooth after implantation based on the three-dimensional model of the implantation effect and the second three-dimensional scan image.

[0189] Exemplarily, the three-dimensional model of the implant effect and the second three-dimensional scanned image are accurately registered so that the two are optimally aligned in space. A three-dimensional comparison algorithm is used to perform comparative analysis on the registered model and image. For example, the deviation between the position, angle, and height of the implant and the adjacent teeth in the second three-dimensional scanned image and the three-dimensional model of the implant effect is calculated, the similarity between the shape and color of the implant and the three-dimensional model of the implant effect is calculated, and the similarity between the actual wear volume and morphology of the adjacent teeth and the wear volume and morphology of the adjacent teeth in the three-dimensional model of the implant effect is calculated. Based on the results of the comparative analysis, the degree of restoration of the missing teeth after implantation is quantified, and the degree of conformity of the implant effect to the ideal model is expressed as a percentage.

[0190] This embodiment determines the three-dimensional model of the implant effect before the implant surgery, which can provide doctors with a visual reference to help them plan the position and direction of the implant more accurately during the operation. At the same time, it can also allow patients to have a clear understanding of the implant effect before the operation, thereby enhancing their willingness to receive treatment. After the implantation of missing teeth, doctors can judge whether the implant surgery is successful and whether further adjustments are needed based on the degree of restoration; patients can also intuitively understand the implant effect and improve their satisfaction with the treatment.

[0191] As an optional implementation, each oral health examination report also includes a third three-dimensional scanning image; the method also includes S191-S193.

[0192] S191: splicing the third 3D scan image and the first 3D scan image in the same oral health examination report to obtain a comprehensive model.

[0193] S192: Predicting the patient's facial change parameters through a prediction model based on the change information of the characteristic parameters around the missing teeth and the comprehensive model.

[0194] S193: Generate a facial evolution video of the patient based on the comprehensive model and facial change parameters.

[0195] Specifically, after tooth loss, especially when multiple teeth are missing, the cheek muscles lose the support of the teeth and will gradually sink inward. This is because the alveolar bone around the teeth will gradually be absorbed as the teeth are lost, causing changes in the facial bone structure, making the cheeks look less full, with obvious depressions, the facial contours become less smooth, and people will appear older. In addition, after tooth loss, the chewing function will be affected, and the patient will not be able to fully use the chewing muscles when chewing food as normally. If this continues for a long time, the chewing muscles will gradually atrophy due to lack of sufficient exercise and stimulation. The atrophy of the chewing muscles will make the contours on both sides of the face less full, and the cheeks will appear smaller, thereby changing the appearance of the face.

[0196] This embodiment splices the third 3D scan image with the first 3D scan image to obtain a comprehensive model that can reflect the user's facial features. By capturing the changes in facial features at different times, the patient's facial change parameters can be predicted and presented through video, making the patient more willing to cooperate with the doctor to receive treatment.

[0197] As an optional embodiment, when the oral condition includes gum atrophy, dental calculus, tooth cracks, tooth occlusal surface wear or periodontitis, S182 includes S1823-S1824.

[0198] S1823: Determine the time interval between adjacent first three-dimensional scan images.

[0199] S1824: Extract one or more characteristic parameters for characterizing gum recession, dental calculus, tooth cracks, tooth occlusal surface wear or periodontitis from multiple first three-dimensional scanning images; wherein, the characteristic parameters of gum recession include: gum margin line, gum volume; the characteristic parameters of dental calculus include: at least one of calculus coverage area and average calculus thickness; the characteristic parameters of tooth cracks include: at least one of crack length, crack depth and crack direction; the characteristic parameters of tooth occlusal surface wear include: at least one of cusp height reduction, occlusal surface depression area / depth and tooth volume loss; the characteristic parameters of periodontitis include: at least one of periodontal pocket depth, clinical attachment loss and alveolar bone absorption height.

[0200] Correspondingly, S183 includes S1833-S1834.

[0201] S1833: Determine the change information of the characteristic parameters of gum atrophy, dental calculus, tooth cracks, tooth occlusal surface wear or periodontitis based on the time interval between adjacent first three-dimensional scanning images and one or more characteristic parameters of gum atrophy, dental calculus, tooth cracks, tooth occlusal surface wear or periodontitis; wherein, the change information of the characteristic parameters of gum atrophy includes: at least one of the movement speed of the gum edge line and the reduction speed of the gum volume; the change information of the characteristic parameters of dental calculus includes: at least one of the expansion speed of the calculus coverage area and the growth speed of the average calculus thickness; the change information of the characteristic parameters of tooth cracks includes: at least one of the extension speed of the crack length and the deepening speed of the crack depth; the change information of the characteristic parameters of tooth occlusal surface wear includes: at least one of the reduction speed of the tooth cusp height, the expansion speed / deep deepening speed of the occlusal surface depression area and the tooth volume loss speed; the change information of the characteristic parameters of periodontitis includes: at least one of the deepening speed of the periodontal pocket, the increase rate of clinical attachment loss and the acceleration rate of alveolar bone absorption.

[0202] S1834: Based on the change information of the characteristic parameters of gum recession, the evolution information of gum recession, dental calculus, tooth cracks, tooth occlusal surface wear or periodontitis is predicted by a prediction model; wherein, the evolution information of gum recession includes: at least one of the future movement speed of the gum edge line and the future reduction speed of the gum volume; the evolution information of dental calculus includes: at least one of the future expansion speed of the calculus coverage area, the future growth speed of the average thickness of the calculus, and the risk of calculus accumulation in a specific part; the evolution information of tooth cracks includes: the future extension speed of the crack length, the future crack depth increase rate, and the future crack length increase rate. The information on the evolution of tooth occlusal wear includes: at least one of the future rate of cusp height reduction, the future rate of expansion of the occlusal depression area / deep deepening, the future rate of tooth volume loss, the probability of increased risk of dentin sensitivity, the probability of increased risk of tooth cracks, and the prediction of a decrease in the vertical distance of occlusion; the information on the evolution of periodontitis includes: at least one of the future rate of periodontal pocket deepening, the future rate of attachment loss growth, the future rate of bone resorption acceleration, the prediction of active lesion sites, and the probability of tooth mobility risk.

[0203] As an optional implementation, the method also includes S194.

[0204] S194: Obtain at least one of the patient's diet data, oral hygiene habit data, age data, gender data, bad habit data, systemic disease data, and genetic data.

[0205] Factors such as a patient's diet (e.g., how many times per week they consume sweets, colored beverages, and coffee), oral hygiene habits (e.g., how many times per day they brush their teeth and whether they floss), age, gender, unhealthy habits (e.g., smoking, alcoholism, biting hard objects), systemic diseases (e.g., diabetes, hypertension, cardiovascular disease), and genetics (e.g., the genetic history of oral conditions) may all influence the onset, development, and evolution of oral conditions. Obtaining this data can provide a more comprehensive understanding of individual patients' circumstances and provide a richer basis for accurately predicting the evolution of oral conditions.

[0206] The above data can be obtained by asking patients or designing questionnaires for them to fill out.

[0207] Correspondingly, S183 includes S1835 and S1836.

[0208] S1835: Adjust the weight parameters of the prediction model based on at least one of the patient's diet data, oral hygiene habit data, age data, gender data, bad habit data, systemic disease data, and genetic data.

[0209] For example, since the patient's diet data, oral hygiene habit data, and bad habit data can lead to the deposition of some pigments, if the frequency of drinking colored beverages (such as coffee, tea, and red wine) is too high, the prediction model will increase the weight of pigment deposition and dental calculus. If the oral hygiene habit data shows that the brushing frequency is too low or the method is inappropriate, the prediction model will increase the weight of dental plaque accumulation, gingival inflammation (such as redness, swelling, bleeding on probing), and interproximal caries. If the age data is too old, the prediction model will increase the weight of gum atrophy and alveolar bone resorption, dental caries, and tooth wear. If the gender data shows that the patient is male, the prediction model will increase the weight of dental calculus deposition rate and periodontal pocket depth. If the bad habit data shows that the smoking frequency is too high, the prediction model will increase the weight of dental pigment deposition, dental calculus formation rate, and oral mucosal abnormalities (such as white spots / erythema). If the bad habit data shows that the patient has nocturnal grinding or clenching of teeth, the prediction model will increase the weight of tooth tilt, tooth wear, tooth cracks, and periodontal tissue trauma. If the systemic disease data shows that the patient has diabetes, the recognition weight of the degree of oral inflammation, periodontal pocket depth and alveolar bone absorption rate in the prediction model will be increased. If the systemic disease data shows that the patient has a blood disease (such as leukemia) or takes anticoagulants, the recognition weight of abnormal gingival swelling in the prediction model will be increased. If the systemic disease data shows that the patient has gastroesophageal reflux disease, the recognition weight of caries or lingual erosion of teeth in the prediction model will be increased. If the genetic data shows that there is a family history of caries, the recognition weight of caries in the prediction model will be increased. If the genetic data shows that there is a family history of periodontal disease, the recognition weight of signs related to aggressive periodontitis or oral gingival inflammation in the prediction model will be increased.

[0210] S1836: Predicting the evolution information of the oral state based on the adjusted prediction model and one or more characteristic parameters of the oral state.

[0211] One or more characteristic parameters of a single oral condition may not fully and accurately reflect the evolution of a disease. This embodiment combines various relevant patient data to adjust the weight parameters of the prediction model. This adjusted prediction model can then comprehensively consider the impact of various factors on oral conditions, enabling the adjusted prediction model to more accurately predict the evolution of oral conditions, thereby providing strong support for doctors to develop more reasonable treatment and prevention plans.

[0212] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0213] Corresponding to the personalized video generation method of the above embodiment, Figure 2 A structural block diagram of a personalized video generation device provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0214] Reference Figure 2 , the device comprises:

[0215] An acquisition module 210 is used to obtain an oral health examination report of a patient;

[0216] Extraction module 220, for extracting relevant data of abnormal areas of the patient's oral cavity from the oral health examination report;

[0217] The personalized video generation module 230 is used to generate a personalized video based on the relevant data of the patient's oral abnormal area; the personalized video is used to interpret the relevant data of the patient's oral abnormal area.

[0218] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of this application. Their specific functions and technical effects can be found in the method embodiment section and will not be repeated here.

[0219] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0220] An embodiment of the present application also provides an electronic device, which includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor implements the steps of any of the above-mentioned method embodiments when executing the computer program.

[0221] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned various method embodiments can be implemented.

[0222] An embodiment of the present application provides a computer program product. When the computer program product is run on an electronic device, the electronic device can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0223] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program, when executed by the processor, can implement the steps of the above-mentioned various method embodiments. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include at least: any entity or device capable of carrying the computer program code to an electronic device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electric carrier signal, a telecommunication signal and a software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, a computer-readable medium cannot be an electric carrier signal or a telecommunication signal.

[0224] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0225] The computer program code for performing the operation of the embodiment of the application can be written with one or more programming languages ​​or their combination, and the programming language comprises an object-oriented programming language, such as python, Java, Smalltalk, C++, and also comprises conventional procedural programming language, such as " C " language or similar programming language.Program code can be executed completely on the user's computer, partially on the user's computer, executed as an independent software package, partly on the user's computer and partly on the remote computer, or executed completely on the remote computer or server. In the case of relating to the remote computer, the remote computer can include a local area network (LAN) or a wide area network (WAN)--connected to the user's computer by the network of any type, or, can be connected to an external computer (such as utilizing an Internet service provider to connect by the Internet).

[0226] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0227] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0228] In the embodiments provided in the present application, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are merely schematic. For example, the division of the modules or units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0229] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0230] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A personalized video generation method, characterized in that: include: Obtain oral health examination reports from patients; Extracting relevant data of the patient's oral abnormal area from the oral health examination report; generating a personalized video based on the relevant data of the abnormal area of ​​the patient's oral cavity; The personalized video is used to interpret relevant data of the abnormal area of ​​the patient's oral cavity.

2. The personalized video generation method according to claim 1, wherein: Generating a personalized video based on the relevant data of the patient's oral abnormal area includes: Obtaining a lookup table, wherein the lookup table records the correspondence between the oral abnormality area and the cause of the oral abnormality area; A first sub-segment of the personalized video is generated based on the cause of the abnormal oral area corresponding to the relevant data of the abnormal oral area of ​​the patient; the first sub-segment is used to provide scientific knowledge on the cause of the abnormal oral area of ​​the patient.

3. The personalized video generation method according to claim 2, wherein: The lookup table also records the correspondence between the oral abnormality area and the treatment plan; and generating a personalized video based on the relevant data of the patient's oral abnormality area also includes: A second sub-segment of the personalized video is generated based on the treatment plan corresponding to the relevant data of the abnormal area of ​​the patient's oral cavity; the second sub-segment is used to introduce the treatment plan.

4. The personalized video generation method according to claim 3, wherein: In a case where there are multiple treatment plans corresponding to the data related to the abnormal oral area of ​​the patient, generating the second sub-segment of the personalized video according to the treatment plans corresponding to the data related to the abnormal oral area of ​​the patient includes: issuing an inquiry instruction, wherein the inquiry instruction is used to inquire the doctor to select a treatment plan suitable for the patient from the multiple treatment plans; The treatment plan suitable for the patient selected by the doctor is received, and a second sub-segment of the personalized video is generated according to the treatment plan suitable for the patient.

5. The personalized video generation method according to claim 2, wherein: The lookup table also records the corresponding relationship between the abnormal oral region and the results of taking the treatment plan and the consequences of not taking the treatment plan; The generating of a personalized video based on the relevant data of the abnormal oral area of ​​the patient further includes: generating a third sub-segment of the personalized video based on the results of adopting the treatment plan and the consequences of not adopting the treatment plan corresponding to the relevant data of the abnormal area of ​​the patient's oral cavity; The third sub-segment is used to explain and demonstrate the results of the patient taking the treatment plan and the consequences of the patient not taking the treatment plan.

6. The personalized video generation method according to claim 1, wherein: The oral health examination report also includes a three-dimensional scan image of the patient's jaws and a three-dimensional scan image of the face; when the relevant data of the abnormal area of ​​the patient's oral cavity includes an incorrect occlusion relationship of the patient, generating a personalized video based on the relevant data of the abnormal area of ​​the patient's oral cavity includes: Determining the patient's jaw movement trajectory and the occlusal relationship based on the three-dimensional tooth and jaw scan image and the three-dimensional facial scan image; A fourth sub-segment of the personalized video is generated based on the patient's jaw movement trajectory and the occlusion relationship; the fourth sub-segment is used to explain and demonstrate the patient's jaw movement trajectory and the occlusion relationship, as well as the correct jaw movement trajectory and the occlusion relationship.

7. The personalized video generation method according to any one of claims 1 to 6, characterized in that: Generating a personalized video based on the relevant data of the patient's oral abnormal area includes: Obtaining a video database; the video database contains a plurality of video clips, each of which corresponds to the cause of the abnormal oral area, the treatment plan, the result of adopting the treatment plan, the consequence of not adopting the treatment plan, the jaw movement trajectory, and the occlusal relationship; determining one or said video segments corresponding to data related to an abnormal area of ​​said patient's oral cavity; The personalized video is generated according to the one or more video clips.

8. The personalized video generation method according to any one of claims 1 to 6, characterized in that: The method further comprises: Obtain the patient's age; Determining a target video template according to the age of the patient; the target video template is one of a plurality of video templates, and different video templates correspond to different styles; Generate a personalized video based on the relevant data of the patient's oral abnormal area, including: The personalized video is generated based on the relevant data of the abnormal area of ​​the patient's oral cavity and the target video template.

9. The personalized video generation method according to any one of claims 1 to 6, characterized in that: The method further comprises: Recording behavioral data of the patient watching the personalized video, wherein the behavioral data includes one or more of: fast forward, skip, slow play, replay, questioning, and screenshot; Based on the behavioral data, the patient's treatment intention is determined and / or a corresponding personalized video sub-segment is retrieved.

10. The personalized video generation method according to any one of claims 1 to 6, characterized in that: The method further comprises: Obtaining oral health examination reports of the patient at different times, wherein the plurality of oral health examination reports each include a first three-dimensional scan image; Extracting one or more characteristic parameters for characterizing the abnormal area of ​​the oral cavity from the plurality of the first three-dimensional scan images; Predicting the evolution information of the oral state through a prediction model based on one or more characteristic parameters of the oral abnormality area; An evolution video of the abnormal area of ​​the oral cavity is generated based on the evolution information of the oral cavity state and the first three-dimensional scanning image.

11. A personalized video generation device, characterized in that: include: An acquisition module is used to obtain the patient's oral health examination report; An extraction module, configured to extract relevant data of the patient's oral abnormal area from the oral health examination report; A personalized video generation module, configured to generate a personalized video based on the relevant data of the patient's oral abnormality area; The personalized video is used to interpret relevant data of the abnormal area of ​​the patient's oral cavity.

12. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 10 is implemented.

13. A computer program product, characterized in that When the computer program product is run on an electronic device, the electronic device is caused to execute the method according to any one of claims 1 to 10.

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