Generating a 3D digital representation of a jaw

Abstract

The present disclosure relates to a computer-implemented method for identifying a jaw type in a dental scan of a jaw (110). The method comprises obtaining (1102) scan data (204A) of the dental scan from an intraoral scanner (104), analysing (1104) the scan data to identify the jaw type of at least a portion of the dental scan, and generating (1106) a first 3D digital representation of at least a part of the jaw based on the scan data and the identified jaw type associated with at least the portion of the dental scan. The scan data comprises at least one of: gyroscopic data (204B), image data, accelerometer data (204C), compass data, or orientation data. The identified jaw type is associated with one of: a first jaw, a second jaw or a bite scan.

Description

[0001] GENERATING A 3D DIGITAL REPRESENTATION OF A JAW

[0002] TECHNICAL FIELD

[0003] The disclosure relates to intraoral scanners and more particularly relates to a computer-implemented method and a dental scanning system for generating a 3D digital representation of at least a part of a jaw based on jaw type.

[0004] BACKGROUND

[0005] An intraoral scanner is an electronic device that may be used for, for example, capturing digital images of an oral cavity of a patient. The intraoral scanner may be a handheld device used to directly create digital images of the oral cavity, thereby optimizing treatment accuracy. Such digital images may be utilized in dental procedures, for example, but are not limited to, restorative procedures, orthodontic treatment planning, implantology, prosthodontics, and periodontics. The intraoral scanners have become indispensable tools for modem dental practices, contributing to improved treatment outcomes, patient comfort, and overall efficiency.

[0006] The components of the intraoral scanner include a handheld camera wand, a computer, and software. The handheld camera wand comprises a small, smooth wand that is connected to a computer and runs custom software. The computer runs the custom software that processes digital data sensed by the camera. The software processes the data to create a detailed digital impression of the oral cavity. A scanning process or a scanning session may include scan steps, such as scanning a lower arch of a jaw of the patient, then scanning an upper arch of the jaw, and scanning a bite of the patient.

[0007] Typically, a user, such as a dentist or a user of the hand-held intraoral scanner may provide input to the computer so as to enable the software to identify different parts, i.e., the upper arch, the lower arch and the bite of the jaw being scanned. For example, once the user is finished with a first scanning step, such as scanning the upper arch of the jaw, they user may have to provide input to the computer, such as using I / O devices to indicate an end of the first scanning step and start of a second scanning step. For example, the user may have to click on a mouse, or engage with a trackpad or a touchscreen to provide the input to the computer.

[0008] However, the providing such input to the computer is inconvenient and may subject the user and the patient to hygiene-related challenges. The interaction of the user with surfaces of, for example, the mouse, keyboard, the trackpad or the touchscreen, lead to hygiene challenges. Therefore, there is a need for automatically identifying which part of the jaw is being scanned to ensure high hygiene standards while operating the intraoral scanners and improve experience of the patient and the user.

[0009] SUMMARY A dental scanning system and a method for identifying a jaw type for a part of a jaw being scanned and generating a 3D digital representation of the jaw is provided.

[0010] It is an objective of the present disclosure to provide techniques for accurate and real-time identification of a jaw type of at least a part of the jaw being scanned by an intraoral scanner.

[0011] In one aspect, a computer implemented method for identifying a jaw type in a dental scan of a jaw of a patient during a scanning session is provided. The method includes obtaining scan data of the dental scan from an intraoral scanner, analysing the scan data to identify the jaw type of at least a portion of the dental scan, and generating a first three-dimensional (3D) digital representation of at least a part of the jaw based on the scan data and the identified jaw type associated with at least the portion of the dental scan. The scan data includes at least one of: gyroscopic data, image data, accelerometer data, compass data, or orientation data. Further, the identified jaw type is associated with one of: a first jaw, a second jaw or a bite scan.

[0012] In accordance with some example embodiments, the scan data further includes geometry information associated with the jaw.

[0013] In accordance with some example embodiments, the computer-implemented method further includes inputting the scan data and the geometry information into a trained first machine learning (ML) model, and identifying the jaw type of at least the portion of the dental scan based on an output of the trained first ML model. The jaw type of at least the portion of the dental scan is one of the first jaw or the second jaw.

[0014] In accordance with some example embodiments, the scan data further includes colour data. Further, analysing the scan data includes using the gyroscopic data to determine an orientation of the intraoral scanner, using the geometry information to determine an orientation of each of one or more landmarks in the dental scan, and combining the determined orientation of the intraoral scanner and the orientation of each of the one or more landmarks to identify the jaw type of at least the portion of the dental scan.

[0015] In accordance with some example embodiments, the computer-implemented method further includes recognizing, using a second ML model, the one or more landmarks in the dental scan based on the scan data.

[0016] In accordance with some example embodiments, the one or more landmarks comprises at least one of: a tooth -gingiva line, a tongue, a palate, a specific candidate tooth, lips, cusps, or fissures. n accordance with some example embodiments, the computer-implemented method further includes receiving scanning motion pattern data from the intraoral scanner, inputting the received scanning motion pattern data and the gyroscopic data into a third ML model, receiving an output from the third ML model, determining at least the portion of the dental scan of the jaw to be associated with one of: an upper jaw or a lower jaw based on the received output, and assigning the jaw type for at least the portion of the dental scan of the jaw based on the determination. The third ML model is trained to recognize one or more scanning motion patterns indicative of scanning of at least one of: the upper jaw, or the lower jaw.

[0017] In accordance with some example embodiments, the computer-implemented method further includes assigning the jaw type to be the first jaw for at least the portion of the dental scan based on determining at least the portion of the dental scan to be associated with the upper jaw. Alternatively, the computer-implemented method further includes assigning the jaw type to be the second jaw for at least the portion of the dental scan based on determining at least the portion of the dental scan to be associated with the lower jaw.

[0018] In accordance with some example embodiments, the computer-implemented method further includes identifying a jaw type for a first portion of the dental scan to be associated with the first jaw, analysing the gyroscopic data to detect an orientation change value of the intraoral scanner, comparing the orientation change value and a threshold value, and identifying a jaw type for a second portion of the dental scan to be associated with the second jaw in response to determining the orientation change value to be greater than the threshold value. The method further includes generating the first 3D digital representation associated with the first portion of the dental scan and a second 3D digital representation associated with the second portion based on the scan data and the identified jaw type for each of the first portion and the second portion.

[0019] In accordance with some example embodiments, the identified jaw type for the first portion of the dental scan is associated with a first part of the jaw and the second portion of the dental scan is associated with a second part of the jaw. In an example, the first 3D digital representation is associated with the first jaw of the first part of the jaw and the second 3D digital representation is associated with the second jaw of the second part of the jaw.

[0020] In accordance with some example embodiments, the computer-implemented method further includes determining an orientation of the intraoral scanner based on the gyroscopic data, obtaining user interaction data indicating a pointing direction of the intraoral scanner, and calibrating a direction of an internal compass of the intraoral scanner based on the orientation and the pointing direction of the intraoral scanner. The internal compass is operable to generate the compass data.

[0021] In accordance with some example embodiments, the calibrated direction of the internal compass is used to determine the jaw type of at least the portion of the dental scan during the scanning session.

[0022] In accordance with some example embodiments, the computer-implemented method further includes displaying an indication of the identified jaw type of at least the portion of the dental scan, and receiving a user feedback based on the displayed identified jaw type for at least the portion of the dental scan of the jaw.

[0023] In accordance with some example embodiments, the computer-implemented method further includes receiving user input data from the intraoral scanner, determining an orientation of the intraoral scanner based on the gyroscopic data, and combining the user input data and the determined orientation of the intraoral scanner to identify the jaw type of at least the portion of the dental scan of the jaw.

[0024] In accordance with some example embodiments, the user input data comprises one or more user interactions with at least one of: a button, or touch sensor, on the intraoral scanner.

[0025] In accordance with some example embodiments, the one or more user interactions comprises a predetermined pattern of shaking the intraoral scanner to indicate the jaw type of at least the portion of the dental scan, double clicking the button on the intraoral scanner while holding the intraoral scanner in a predefined orientation to indicate the jaw type of at least the portion of the dental scan, a button activation pattern indicative of the jaw type of at least the portion of the dental scan, a voice control to indicate the jaw type of at least the portion of the dental scan, a swipe pattern on the touch sensor indicative of the jaw type of at least the portion of the dental scan, and / or an interaction with a dedicated button on the intraoral scanner to indicate the jaw type of at least the portion of the dental scan. In some embodiments, a gesture tracking device may be employed, allowing user interactions to be accomplished through tracking the hand motions of the user. Gestures may also be used to navigate a workflow. For example, the gesture tracking device may determine that a user has performed a right swipe gesture by moving their hand from left to right in front of the gesture tracking device, thereby moving the workflow to the next step. Similarly, a left swipe gesture i.e. the user moving their hand from right to left in front of the tracking device could be used to move back one step in the workflow. Other hand gestures such as pinching fingers together, moving a hand up or down etc. may be employed to navigate the workflow or interact with the 3D digital representation on the screen, for example by zooming or panning the view. The position of the gesture tracking device with respect to the dental chair should normally be known and constant. In this case, the gesture tracking device may be used as a reference point for compass calibration. That is, the gesture tracking device may be used to determine the orientation of the scanner for example with respect to the dental chair, by determining the position and orientation of the user’s hands while holding the scanner in front of the tracking device.

[0026] In accordance with some example embodiments, the computer-implemented method further includes detecting a pause in the scanning session of the patient, receiving new scan data after the pause, and performing, in parallel, a first operation and a second operation. The first operation is performed to register the new scan data into the first 3D digital representation of at least the part of the jaw of the patient, and the second operation is performed to generate a new 3D digital representation based on the new scan data. The method further includes registering the new scan data in association with the first 3D digital representation of at least the part of the jaw of the patient in response to determining a match between the new scan data and the first 3D digital representation based on the first operation and the second operation. The method further includes identifying a jaw type associated with the new scan data to be different from the identified jaw type of at least the portion of the dental scan corresponding to the first 3D digital representation in response to determining the new scan data to be different from the first 3D digital representation based on the first operation and the second operation.

[0027] In another aspect, a dental scanning system for generating a 3D digital representation of a jaw of a patient is provided. The dental scanning system may include a handheld intraoral scanner configured to capture a dental scan of the jaw. The handheld intraoral scanner includes a plurality of sensors. The plurality of sensors includes a gyroscope configured to generate orientation data and / or an accelerometer configured to generate motion data. The dental scanning system may include one or more processors configured to determine an orientation of the handheld intraoral scanner and / or a motion of the handheld intraoral scanner based on the orientation data and / or the motion data, and analyse the orientation and / or the motion to identify a jaw type of at least a portion of the dental scan. The identified jaw type is associated with one of: a first jaw, or a second jaw. A bite scan or bite registration scan, may also be considered a jaw type. The dental scanning system may include a displaying unit configured to display in real-time the 3D digital representation of at least a part of the jaw of the patient based on the identified jaw type of at least the portion of the dental scan.

[0028] According to the present disclosure, a dental scanning system, and a method for identifying a jaw type in a dental scan of a jaw of a patient during a scanning session are provided. One of the purposes of the present disclosure is to provide an effective way to accurately determine which part of the jaw is currently being scanned. For example, during the scanning session a dental scan of the jaw may be captured. This dental scan may correspond to the complete jaw and / or oral cavity of a part of the jaw of the patient. Further, the embodiments of the present disclosure provide techniques to determine whether the dental scan or a portion of the dental scan corresponds to a first jaw or a second jaw. In particular, the embodiments of the present disclosure provide techniques to determine whether the dental scan or the portion of the dental scan corresponds to an upper jaw or a lower jaw of the patient.

[0029] The automated detection of jaw type for the dental scan or the portion of the dental scan of the jaw eliminates the need for interacting with a computer while using an intraoral scanner for providing input specifying jaw type being scanned. This may further ensure that hygiene standards are met during the scanning session. The automated detection of the jaw type for jaw further minimizes human error and provides consistent identification of the jaw being scanned, ensuring accurate dental records and treatment planning. In certain cases, the automated detection may speed up the scanning session and a process of generating the 3D digital representation of the scanned jaw, allowing dental professionals to focus on more critical tasks and improving overall workflow efficiency in the dental practice. Automated identification of the jaw type of the scanned jaw ensures that digital dental records are correctly labelled and organized, facilitating easy retrieval and analysis of patient data for future reference and ongoing care.

[0030] The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.

[0031] BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The present disclosure is illustrated by way of example and not by way of limitation in the figures of the accompanying drawings, in which the like reference numerals indicate like elements and in which:

[0033] FIG. 1 illustrates a network environment in which a dental scanning system for generating a 3D digital representation of a jaw of a patient is implemented, in accordance with an embodiment of the disclosure;

[0034] FIG. 2 illustrates a block diagram of the dental scanning system of FIG. 1, in accordance with an embodiment of the disclosure;

[0035] FIG. 3 illustrates a block diagram depicting operations for identifying a jaw type of at least a portion of a dental scan of the jaw of the patient, in accordance with an embodiment of the disclosure;

[0036] FIG. 4 is a diagram that illustrates the processing of scan data obtained from the intraoral scanner by utilizing the processing module of the processor, in accordance with an embodiment of the disclosure;

[0037] FIG. 5 is a diagram that illustrates exemplary operations for identification of different jaw types, in accordance with an embodiment of the disclosure;

[0038] FIG. 6 is a diagram that illustrates exemplary operations for an analysis of first data and second data for generation of the 3D digital representation associated with the first jaw and the second jaw, in accordance with an embodiment of the disclosure;

[0039] FIG. 7 is a diagram that illustrates analysis of scan data associated with an orientation of the intraoral scanner and an orientation of one or more landmarks for determination of jaw type, in accordance with an embodiment of the disclosure;

[0040] FIG. 8 is a diagram that illustrates exemplary operations for compass calibration for identifying a jaw type, in accordance with an embodiment of the disclosure; FIG. 9 is a diagram that illustrates exemplary operations for parallel reconstructions of the jaw, in accordance with an embodiment of the disclosure;

[0041] FIG. 10 is a diagram that illustrates an exemplary method for identifying a jaw type based on a user input and an orientation of the intraoral scanner, in accordance with an embodiment of the disclosure; and

[0042] FIG. 11 is a flowchart that illustrates an exemplary method for generating first 3D digital representation, in accordance with an embodiment of the disclosure.

[0043] DETAILED DESCRIPTION

[0044] In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure. It will be apparent, however, to one skilled in the art that the present disclosure may be practiced without these specific details. In other instances, systems and methods are shown in block diagram form only in order to avoid obscuring the present disclosure.

[0045] Some embodiments of the present disclosure will now be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all, embodiments of the disclosure are shown. Indeed, various embodiments of the disclosure may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will satisfy applicable legal requirements. Like reference numerals refer to like elements throughout. Also, reference in this specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. The appearance of the phrase “in one embodiment” in various places in the specification does not necessarily all refer to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Further, the terms “a” and “an” herein do not denote a limitation of quantity but rather denote the presence of at least one of the referenced items. Moreover, various features are described which may be exhibited by some embodiments and not by others. Similarly, various requirements are described which may be requirements for some embodiments but not for other embodiments.

[0046] The embodiments are described herein for illustrative purposes and are subject to many variations. It is understood that various omissions and substitutions of equivalents are contemplated as circumstances may suggest or render expedient but are intended to cover the application or implementation without departing from the spirit or the scope of the present disclosure. Further, it is to be understood that the phraseology and terminology employed herein are for the description and should not be regarded as limiting. Any heading utilized within this description is for convenience only and has no legal or limiting effect. As used in this specification and claims, the terms “for example” “for instance” and “such as”, and the verbs “comprising,” “having,” “including” and their other verb forms, when used in conjunction with a listing of one or more components or other items, are each to be construed as open ended, meaning that that the listing is not to be considered as excluding other, additional components or items. Other terms are to be construed using their broadest reasonable meaning unless they are used in a context that requires a different interpretation. Turning now to FIG. 1 - FIG. 11, a brief description concerning the various components of the present disclosure will now be briefly discussed. Reference will be made to the figures showing various embodiments of an intraoral scanner configured to perform an intraoral scanning of a dental object.

[0047] A dental scanning system and a method for automatically identifying a jaw type of at least a portion of a dental scan of a jaw of a patient and generating a 3D digital representation of the jaw of the patient are provided.

[0048] FIG. 1 illustrates a network environment 100 in which a dental scanning system 102 (referred to as system 102, hereinafter) for generating a 3D digital representation of a jaw 110 of a patient 112, in accordance with an embodiment of the disclosure. The network environment 100 includes an intraoral scanner 104 for scanning the jaw 110 of the patient 112. The network environment 100 includes a database 108, and a communication network 114. In an example, the system 102 may include the intraoral scanner 104, and a displaying unit 106.

[0049] The system 102 may include suitable logic, circuitry, interfaces, and / or code that may be configured to identify a jaw type of at least a portion of a dental scan of the jaw 110 the patient 112 being scanned during a scanning session. In an embodiment, the system 102 is configured to obtain scan data of a dental scan of the jaw 110 from the intraoral scanner 104. The system 102 is further configured to analyse the scan data to identify a jaw type of at least a portion of the dental scan. Further, the system 102 is configured to generate a first 3D digital representation of at least a part of the jaw being scanned. In an embodiment, the system 102 may further control the displaying unit 106 to display in real time, the 3D digital representation of the jaw 110 of the patient 112.

[0050] In an embodiment, the system 102 may include the intraoral scanner 104. The intraoral scanner 104 may be a device that may be used in dentistry that provides a digital alternative to traditional method of taking an analog impression of a dental object. The intraoral scanner 104 may capture 3D digital dental impressions and use the data to produce a highly detailed image of an oral cavity of the patient 112. The intraoral scanner 104 projects a light source onto scan objects, such as full dental arches of the patient 112. Further, the 3D digital representation of the dental object 110 is processed by a scanning software and images are displayed in real-time on the displaying unit 106. The light source may be, for example, but not limited to, a laser, or a structured light. Further, the intraoral scanner 104 may include one or more sensors. The one or more sensors may include, but are not limited to, a gyroscope, an accelerometer, a light sensor (or camera), and a geometry sensor. In an embodiment, the gyroscope in the intraoral scanner 104 is operable to generate or sense orientation data indicating an orientation of the intraoral scanner 104 at different time instants. Further, the accelerometer in the intraoral scanner 104 may is operable to generate or sense motion data of the intraoral scanner 104. In an exemplary embodiment, the system 102 may obtain scan data from the intraoral scanner 104. In an example, the scan data comprises gyroscopic data or orientation data generated or sensed by the gyroscope, image data captured by image sensors, accelerometer data or motion data generated or sensed by the accelerometer, or a combination thereof. In certain cases, the scan data received from the intraoral scanner 104 further includes compass data indicating an orientation of the intraoral scanner 104 with respect to an orientation of a dental chair at a dental clinic. For example, a direction of an internal compass of the intraoral scanner 104 may be calibrated based on an orientation of the intraoral scanner 104 and a pointing direction of the intraoral scanner 104. The pointing direction may be obtained from a user of the system 102 as part of user interaction data. The pointing direction of the intraoral scanner may be indicated with respect to, for example, a patients’ chair at a dental clinic. The pointing direction of the intraoral scanner 104 with respect to the patients’ chair and the real-time orientation of the intraoral scanner may be used to calibrate the internal compass for generating compass data of the intraoral scanner 104. The compass data may indicate true position or orientation of the intraoral scanner 104 with respect to the patients’ chair at the dental clinic. In an example, the scan data may also include geometry information associated with the jaw 110. For example, the geometry information of the jaw 110 may indicate, for example, shape, structure, and spatial relationships, including an arrangement and an orientation of anatomical features of the jaw 1 lOi. The position of the patient may also be used as a compass reference point. Other such reference points may include, but are not limited to, wifi points, computer screen, electrical outlet or any other permanent or semi-permanent feature of the room. Information about the orientation of the scanner may also be used to assist in more robust teeth segmentation and dental charting, since it is known which jaw is being scanned. The compass data may further be used to recognize left from right in the 3D digital representation, which can aid in recognizing if a specific tooth is in a certain quadrant.

[0051] In some embodiments, the hardware for the compass module may be placed on the same chip as the gyroscope. Other methods of finding the orientation of the scanner may include wifi triangulation i.e. with one or more antennae, camera images containing known reference points or other techniques. The scanner orientation data obtained from the compass module, or from one of the other techniques described above, may be used to inform other aspects of CAD work steps to improve on them. For example, scanner orientation data can be used to help in early segmentation of the 3D digital representation, help with soft tissue removal, trimming. Other algorithms in the reconstruction workflow, like stitching and tracking may also be improved by incorporating the scanner orientation data. In some embodiments, this may be accomplished using a trained neural network, or other machine learning techniques. Scanner orientation data may further help in creating a reference orientation for better capture of edentulous cases.

[0052] It may be noted, the jaw 110 may include an upper jaw (or maxilla) and a lower jaw (or mandible). The upper jaw or maxilla forms an upper part of the oral cavity or a mouth of the patient 112. The upper jaw or maxilla may have a somewhat pyramidal shape and contains an upper dental arch, which may be U- shaped. The upper jaw or maxilla may include, for example, palate, maxillary sinuses, alveolar ridge, infraorbital foramen, and / or zygomatic process. Moreover, the lower jaw or mandible may have a horseshoe-shaped bone that forms a lower part of a face of the patient 112. The lower jaw or mandible supports lower teeth of the patient 112. The lower jaw or mandible may include, for example, body, rami or ramus, alveolar ridge, mental foramen, condylar processes, and coronoid processes.

[0053] In an embodiment, the system 102 may further include the displaying unit 106. The display unit 106 may be utilized by the system 102 to display the 3D digital representation of the jaw 110 scanned by the intraoral scanner 104. The jaw type of the jaw 110 in the dental scan may correspond to an upper jaw of the patient 112 or a lower jaw of the patient 112. In an exemplary embodiment, the displaying unit 106 may include, but are not limited to, a display device, a desktop, a smartphone, or a tablet. In another exemplary embodiment, the displaying unit 106 may be associated with the user of the system 102. The user of the system 102 may be, for example, a dentist.

[0054] In an embodiment, the network environment 100 may include the database 108. The database 108 may be an organised collection of data that may be received from the system 102 over the network 114. Within the database 108, the data may be organised in form of one or more tables. The one or more tables may include rows, columns, and indexes to make the data more relevant. In an embodiment, the database 108 may be of a type such as, but not limited to, a cloud database, a centralized database, an operational database. Further, the database 108 may store the data that may be generated by and / or received from the system 102. The data may include scan data associated with the intraoral scanner 104. The data may further include geometry information associated with the jaw 110.

[0055] The network 114 may be wired, wireless, or any combination of wired and wireless communication networks, such as cellular, Wi-Fi, internet, local area networks, or the like. In some embodiments, the network 114 may include one or more networks such as a data network, a wireless network, a telephony network, or any combination thereof. It is contemplated that the data network may be any local area network (LAN), metropolitan area network (MAN), wide area network (WAN), a public data network (e.g., the Internet), short-range wireless network, or any other suitable packet-switched network, such as a commercially owned, proprietary packet-switched network, e.g., a proprietary cable or fibre-optic network, and the like, or any combination thereof. In addition, the wireless network may be, for example, a cellular network and may employ various technologies including enhanced data rates for global evolution (EDGE), general packet radio service (GPRS), global system for mobile communications (GSM), Internet protocol multimedia subsystem (IMS), universal mobile telecommunications system (UMTS), etc., as well as any other suitable wireless medium, e.g., worldwide interoperability for microwave access (WiMAX), Long Term Evolution (LTE) networks (e.g. LTE-Advanced Pro), 5G New Radio networks, ITU-International Mobile Communication (IMT) 2020 networks, code division multiple access (CDMA), wideband code division multiple access (WCDMA), wireless fidelity (Wi-Fi), wireless LAN (WLAN), Bluetooth, Internet Protocol (IP) data casting, satellite, mobile ad-hoc network (MANET), and the like, or any combination thereof.

[0056] In operation, a user, such as a dental practitioner of the system 102 may initiate the scanning session of the jaw 110 of the patient 112 by positioning the intraoral scanner 104 aligned with an oral cavity of the patient 112. In an exemplary embodiment, the scanning session may be performed in a dental clinic. In another exemplary embodiment, the scanning process may be performed at a home of the patient 112. During the scanning session of the jaw 110 or in real-time after a completion of the scanning session of the patient 112 by the intraoral scanner 104, the identification of which portion of the dental scans corresponds to which part of the jaw 110 is performed by the system 102. For example, the system 102 is configured to identify which of a first jaw (such as, upper jaw) or a second jaw (such as, lower jaw) of the patient 112 is being scanned, or which portion of the dental scan corresponds to the first jaw and the second jaw. Further, the system 102 may use the determination of which of the first jaw or the second jaw of the patient 112 is being scanned to generate the 3D digital representation of the jaw 110 of the patient 112.

[0057] In an embodiment, the system 102 is configured to obtain the scan data from the intraoral scanner 104. The intraoral scanner 104 may be equipped with the one or more sensors. The one or more sensors may capture the scan data associated with the jaw 110 of the patient 112. The scan data may include, for example, the gyroscopic data or the orientation data, the accelerometer data or the motion data, image data, compass data, or geometry information of the jaw 110. In an example, the image data may include the geometry information about the jaw 110 being scanned. The image data or the scan data may further include colour data and data associated with an orientation of one or more landmarks associated with the oral cavity of the patient 112. The one or more landmarks may be associated with, for example, a tooth-gingiva line, a tongue, a palate, or a specific candidate tooth, lips, cusps, and / or fissures. The specific candidate tooth may be associated with, for example, a nine, bi-cuspid, incisor, interior, premolar or molar.

[0058] Further, the system 102 may be configured to analyse the scan data to identify the jaw type of at least a portion of the dental scan. The identified jaw type is associated with the first jaw, or the second jaw. In an example, the first jaw may be associated with the upper jaw and the second jaw may be associated with the lower jaw, or vice-versa. In an example, for a portion of the dental scan that is currently being scanned, the system 102 is configured to determine whether the portion corresponds to or belongs to the first jaw or the second jaw.

[0059] In an embodiment, the system 102 may utilize a first machine learning (ML) model to analyse the scan data obtained from the intraoral scanner 104 to identify the jaw type of at least a portion, say a first portion of the dental scan of the jaw 110. In this regard, the scan data is provided or fed into a trained first machine learning (ML) model as an input. Further, the first ML model may be trained on scan data associated with plurality of patients and / or scan data associated with the patient 112. For example, the first ML model may be trained to process the gyroscopic data, the accelerometer data, the colour data, the geometry information, the image data, the compass data, or a combination thereof. Based on the processing, the first ML model may generate an output indicative of a jaw type associated with the first portion of the dental scan. Based on the output of the first ML model, the jaw type of at least the portion, such as the first portion of the dental scan. It may be noted that the jaw type may indicate that the first portion is associated with the first jaw or the second jaw, i.e., the upper jaw or the lower jaw.

[0060] In an embodiment, the system 102 may be configured to utilize data stored in the database 108 to train the first ML model. The stored data may have been captured during one or more historical scanning sessions. The historical scanning sessions may take place 1 day before the scanning session of the patient 112, 1 week before the scanning session of the patient 112, 1 month before the scanning session of the patient 112, and so forth. The system 102 may be configured to control the first ML model to access the data stored in the database 108 for the training of the first ML model. The system 102 may further identify which of the first j aw or the second j aw is the j aw type of the first portion of the dental scan that is being scanned. Further, the system 102 is configured to generate a first 3D digital representation of at least a part of the jaw 110 based on the scan data and the identified jaw type associated with at least the portion, i.e., the first portion of the dental scan.

[0061] Further, the system 102 may be configured to control the displaying unit 106 to display the generated 3D digital representation of at least the part of the jaw 110. For example, if a part of the jaw that is being scanned by the intraoral scanner 104 is determined to be associated with the jaw type of the first jaw, such as the upper jaw of the patient 112, then the system 102 may generate the 3D digital representation of the upper jaw of the patient 112 based on the scan data and the identified jaw type. Further, the system 102 may display the generated 3D digital representation of at least the part, such as the upper jaw of the jaw 110 on the displaying unit 106. The displaying unit 106 may be associated with, accessed by or operated by the user (such as a dentist) to determine clinical solutions for the patient 112.

[0062] FIG. 2 illustrates a block diagram 200 of the system 102 of FIG. 1, in accordance with an embodiment of the disclosure. FIG. 2 is explained in conjunction with FIG. 1. The system 102 may include one or more processors 202 (referred to as a processor 202, hereinafter), one or more non-transitory memory 204 (referred to as a memory 204, hereinafter), an input / output (I / O) interface 206, and a network interface 208. The processor 202 may include modules, depicted as, an input module 202A, a data generation module 202B, a processing module 202C, a machine learning (ML) module 202D, and an output module 202E. The processor 202 may be connected to the memory 204, and the I / O interface 206 through wired or wireless connections. Although in FIG. 2, it is shown that the system 102 includes the processor 202, the memory 204, and the I / O interface 206, however, the disclosure may not be so limiting and the system 102 may include fewer or more components to perform the same or other functions of the system 102. In an embodiment, the input module 202A, and the output module 202E may be integrated within the I / O interface 206. In some embodiments, the input module 202A may receive input data (such as scan data and / or user input data), and the output module 202E may output processed data (such as 3D digital representation(s) for the jaw 110), via the I / O interface 206.

[0063] In accordance with an embodiment, the system 102 may store data that may be generated by the modules while performing corresponding operations or may be retrieved from a database associated with the system 102, such as the database 108. For example, the data may include scan data 204A including gyroscopic data 204B, accelerometer data 204C, image data and / or compass data. The data may also include user input data 204D, and the 3D digital representation(s). The image data may include images of different orientations of the intraoral scanner 104 and images of different orientations of the jaw 110.

[0064] The processor 202 of the system 102 may be configured to analyse the obtained data and generate the first 3D digital representation of at least the part of the jaw 110 being scanned and further output the generated 3D digital representation. The processor 202 may be embodied as one or more of various hardware processing means such as a coprocessor, a microprocessor, a controller, a digital signal processor (DSP), a processing element with or without an accompanying DSP, or various other processing circuitry including integrated circuits such as, for example, an ASIC (application-specific integrated circuit), an FPGA (field programmable gate array), a microcontroller unit (MCU), a hardware accelerator, a special-purpose computer chip, or the like. As such, in some embodiments, the processor 202 may include one or more processing cores configured to perform independently. A multi-core processor may enable multiprocessing within a single physical package. Additionally, or alternatively, the processor 202 may include one or more processors configured in tandem via the bus to enable independent execution of instructions, pipelining, and / or multithreading. Additionally, or alternatively, the processor 202 may include one or more processors capable of processing large volumes of workloads and operations to provide support for big data analysis. In an example embodiment, the processor 202 may be in communication with the memory 204 via a bus for passing information among components of the system 102.

[0065] For example, when the processor 202 may be embodied as an executor of software instructions, the instructions may specifically configure the processor 202 to perform the algorithms and / or operations described herein when the instructions are executed. However, in some cases, the processor 202 may be a processor-specific device (for example, a mobile terminal or a fixed computing device) configured to employ an embodiment of the present disclosure by further configuration of the processor 202 by instructions for performing the algorithms and / or operations described herein. The processor 202 may include, among other things, a clock, an arithmetic logic unit (ALU), and logic gates configured to support the operation of the processor 202. The network environment, such as 100 may be accessed using the network interface 208 of the system 102. The network interface 208 may provide an interface for accessing various features and data stored in the system 102.

[0066] In some embodiments, the processor 202 may be configured to provide Intemet-of-Things (loT) related capabilities to users of the system 102 disclosed herein. The loT-related capabilities may in turn be used to provide smart solutions by providing real time digital representation generation, big data analysis, real time data generation and sensor-based data collection by using the cloud-based mapping system for providing accurate digital representations of the 3D digital representations of the jaw 110 of the patient 112. The I / O interface 206 may provide an interface for accessing various features and data stored in the system 102.

[0067] The input module 202A of the processor 202 may be configured to obtain the scan data associated with the intraoral scanner 104. In an embodiment, the scan data may be obtained from a button, keypad, touchpad, etc., using one or more sensors associated with the intraoral scanner. The one or more sensors may correspond to at least a gyroscope, an accelerometer, an internal compass, a camera sensor, a touch sensor, a media sensor, a motion sensor and a voice sensor.

[0068] In one or more embodiments, the obtained scan data may correspond to an initiation of a scanning session of the jaw 110 of the patient 112. For example, a user may use a touch sensor or a button of the system 102, specifically the intraoral scanner 104 to initiate the scanning session of the jaw 110 of the patient 112.

[0069] In an example, the system 102 or the input module 202A may receive user input data from the intraoral scanner 104. In an example, the obtained scan data may include the user input data. For example, the user input data may include one or more user interactions (or interaction data) with at least one of: a button, or touch sensor, on the intraoral scanner 104. The interaction data may correspond to an interaction of a user with the system 102 or the intraoral scanner 104. The interaction data may further include, but is not limited to, one or more gesture data, clicking data, a button activation pattern, voice data, a swipe pattern, and a button interaction.

[0070] The gesture data may correspond to an interaction of the user with the intraoral scanner 104, for example, by shaking the intraoral scanner 104 in a pre-determined pattern to indicate a jaw type of at least a portion of the dental scan or at least a part of the jaw 110 being scanned. In an example, the predetermined pattern may be an upward pattern, a downward pattern, a horizontal pattern, or a specific combination thereof. The clicking data may correspond to an interaction of the user with the intraoral scanner 104, such as by double clicking a buton on the intraoral scanner 104 while holding the intraoral scanner 104 in a predefined orientation. Such clicking data may indicate the jaw type for at least the portion of the dental scan or at least the part of the jaw 110 being scanned. In an example, the orientation may be an upward orientation, a downward orientation or a horizontal orientation.

[0071] The buton activation patern may correspond to an interaction of the user with the intraoral scanner 104 by using a buton in an activation patern. In an example, the activation patern may include a click, a double click, a click-and-hold patern, and the like. Further, the voice data may correspond to an interaction of the user with the system 102 or the intraoral scanner 104 via a voice control or a voice command. In an example, the voice control may include a “scan upper jaw” voice command to indicate that the jaw type being scanned is the upper jaw or the first jaw, a “scan lower jaw” voice command to indicate that the jaw type being scanned is the lower jaw or the second jaw, or a “bite scan” voice command to indicate that the jaw type being scanned is a bite of the jaw 110.

[0072] The swipe patern may correspond to an interaction of the user with the intraoral scanner 104 by using a swipe patern on a trackpad, a touchpad or a touch screen associated with the intraoral scanner 104 and / or the system 102. In an example the swipe patern may include a double click on the top of the trackpad, a double click on the botom of the trackpad, a horizontal swipe on the trackpad, etc. to indicate the jaw type of at least the portion of the dental scan. The buton interaction may correspond to an interaction of the user with the system 102 by using dedicated butons on the intraoral scanner 104. In an example, the butons may further include arrow butons, where an up arrow buton may indicate that the jaw type being scanned is the upper jaw and a down arrow buton may indicate that the jaw type being scanned is the lower jaw.

[0073] In an embodiment, the input module 202A may also obtain or receive user feedback based on the identified jaw type for at least the portion of the dental scan. The use feedback may correspond to a confirmation of the user on the identified jaw type for the dental scan or a portion of the dental, i.e., a part of the jaw 110. For example, the output module 202E may display an indication of the identified jaw type of at least the portion of the dental scan on the displaying unit 106. In certain cases, the indication may be displayed in association with the first 3D digital representation of at least the part of the jaw 110 of the patient 112. In an example, the identified jaw type may correspond to the first jaw or the upper jaw, and subsequently, the first 3D digital representation may be associated with the upper jaw. In response to generating and displaying a part of the jaw 110 corresponding to a portion of the dental scan as a 3D representation of the upper jaw, the user may provide the user feedback to verify that the identified jaw type to be the first jaw or the upper jaw is correct or not. Based on the user feedback, the identified jaw type may be updated or retained.

[0074] The data generation module 202B of the processor 202 may be configured to generate the orientation data and / or the motion data based on the obtained scan data 204A. In an embodiment, the obtained scan data 204A may include at least the gyroscopic data 204B, the accelerometer data 204C, colour data, image data, compass data and / or geometry information. The geometry information may indicate a geometry, such as shape, size, orientation, etc. of the jaw 110 being scanned. The gyroscopic data 204B may indicate a position, an angle and / or an orientation the intraoral scanner 104. Moreover, the accelerometer data 204C may indicate a movement speed of the intraoral scanner 104.

[0075] The processing module 202C of the processor 202 may be configured to analyse the orientation data, the motion data, the image data, the colour data, the geometry information and / or the compass data. Based on the analysis, the processing module 202C may be configured to identify whether the jaw type of a portion of the dental scan is the first jaw or the second jaw. In other words, based on processing the data, the processing module 202C identifies if the part of the jaw that is being scanned is related to upper jaw or lower jaw of the patient 112.

[0076] In an embodiment, the processing module 202C may be further configured to determine an orientation of the intraoral scanner 104 based on the gyroscopic data 204B, the accelerometer data 204C and / or the compass data. Further, processing module 202C may be configured to determine an orientation of each of one or more landmarks in the dental scan or a portion of the dental scan that has been captured. For example, the one or more landmarks are associated with a tooth-gingiva line, a tongue, a palate, a specific candidate tooth, lips, cusps, or fissures. The processing module 202C is further configured to combine the determined orientation of the intraoral scanner 104 and the orientation of each of the one or more landmarks to identify the jaw type of at least the portion of the dental scan. For example, based on the orientation of the intraoral scanner 104 and the orientation of one or more landmarks, a distance, a position and / or a viewing direction of the intraoral scanner 104 with respect to the jaw is identified. Subsequently, based on the identified distance, position and / or viewing direction, the jaw type of the portion of the dental scan is identified.

[0077] The ML module 202D of the processor 202 may be configured to execute the ML model(s) 204D to carry out operations of the system 102. In an example, the ML module 202D may execute a trained first ML model to identify the jaw type of at least the portion of the dental scan. In an example, the scan data 204A and data generated by the data generation module 202B and / or the processing module 202C may be input to the trained first ML model. The first ML model may be trained on historical scan data of jaw scans of plurality of patients to identify jaw types for each of one or more portions of the different jaw scans. Subsequently, the trained first ML model is configured to first ML identify the jaw type of at least the portion of the dental scan of the jaw 110 of the patient 112.

[0078] In an example, the ML module 202D may execute a trained second ML model to recognize the one or more landmarks in the dental scan or the portion of the dental scan based on the scan data 204A. In an example, the second ML model may be trained to perform image processing techniques to identify candidate elements corresponding to the one or more landmarks. For example, the second ML model may be trained of multiple jaw images of plurality of patients, such as by providing labels for the one or more landmarks. In an example, the trained second ML model may process the image data from the scan data 204A along with other data (such as accelerometer data 204C, gyroscopic data 204B, geometry information, etc.) in the scan data 204A to identify the orientation of the one or more landmarks in the dental scan or the portion of dental scan. Based on the orientation of the one or more landmarks in the dental scan or the portion of dental scan and the orientation of the intraoral scanner 104, the jaw type of the dental scan or the portion of dental scan is identified, for example, using the trained first ML model.

[0079] In another example, the ML module 202D may execute a trained third ML model to recognize one or more scanning motion patterns indicative of scanning of an upper jaw and / or a lower jaw. Based on an output from the third ML model, the jaw type of at least the portion of the dental scan is identified. The one or more scanning motion patterns may indicate a pattern in which the intraoral scanner 104 is moving, projecting light, etc. The scanning motion patterns may indicate a pattern associated with the scanning session.

[0080] The output module 202E of the processor 202 may be configured to generate the first 3D digital representation of at least a part of the jaw 110 being scanned based on the scan data and the identified jaw type associated with at least the portion of the dental scan. For example, based on the output of the first ML model indicating that a first portion of the dental scan is associated with the first jaw, the first 3D digital representation of a first part of the jaw 110 is generated. The first 3D digital representation of the first part may be associated with, for example, the upper jaw of the patient 112. Thereafter, scan data corresponding to a second part of the jaw or a second portion of the dental scan is processed to identify the jaw type to be the second jaw for the second part of the jaw 110. For example, the jaw 110 comprises the first part having the jaw type of the first jaw and the second part having the jaw type of the second jaw. Subsequently, the output module 202E may output the first 3D digital representation for the first jaw corresponding to the first part of the jaw 110 and a second 3D digital representation for the second jaw corresponding to the second part of the jaw 110.

[0081] The memory 204 of the system 102 may be configured to store the scan data 204A, the ML model(s) 204D, the generated first 3D digital representation and the generated second 3D digital representation of the jaw 110. The memory 204 may be non-transitory and may include, for example, one or more volatile and / or non-volatile memories. In other words, for example, the memory 204 may be an electronic storage device (for example, a computer readable storage medium) comprising gates configured to store data (for example, bits) that may be retrievable by a machine (for example, a computing device like the processor 202). The memory 204 may be configured to store information, data, content, applications, instructions, or the like, for enabling the system 102 to carry out various functions in accordance with an example embodiment of the present disclosure. For example, the memory 204 may be configured to buffer input data for processing by the processor 202. As exemplarily illustrated in FIG. 2, the memory 204 may be configured to store instructions for execution by the processor 202. As such, whether configured by hardware or software methods, or by a combination thereof, the processor 202 may represent an entity (for example, physically embodied in circuitry) capable of performing operations according to an embodiment of the present disclosure while configured accordingly. Thus, for example, when the processor 202 is embodied as an ASIC, FPGA, or the like, the processor 202 may be specifically configured hardware for conducting the operations described herein.

[0082] The scan data 204A may include at least the geometry information and the landmark information. The geometry information may include information about geometry of the jaw being scanned. In an example, the geometry may include at least an orientation of the upper jaw and an orientation of the lower jaw. In another example, the geometry may include at least a size of the upper jaw and a size of the lower jaw. The landmark information may include information about one or more landmarks associated with dental objects. In an embodiment, the landmark information may include at least one or more tooth-gingiva line, tongue, palate, distinctive teeth, specific tooth such as canine, bicuspid, incisor, pre-molar or molar, lips, cusps and fissures.

[0083] The gyroscopic data 204B may include gyroscope measurements. The gyroscope measurements may correspond to the orientation of the intraoral scanner 104 in one or more scanning steps of the scanning session. The scanning steps may include an upper jaw scan, a lower jaw scan and a bite scan.

[0084] The accelerometer data 204C may include accelerometer measurements. The accelerometer measurements may correspond to the movement of the intraoral scanner 104 in one or more scanning steps of the scanning session. The scanning steps may include an upper jaw scan, a lower jaw scan and a bite scan.

[0085] In an embodiment, the system 102 may be configured to provide, as an input, the scan data captured by the intraoral scanner 104 to the first ML model. The first ML model may be stored in the system 102. The machine learning model 204D may process the scan data and determine which jaw of the patient is being scanned. The jaw may be, for example, an upper jaw, or a lower jaw.

[0086] . In an exemplary embodiment, the machine learning model 204D may be used for various tasks such as, but not limited to, classification, regression, pattern recognition, and decision-making.

[0087] In an embodiment, the machine learning model(s) 204D may correspond to a neural network-based classifier. The neural network may be a computational network or a system of artificial neurons, arranged in a plurality of layers, as nodes. The plurality of layers of the neural network may include an input layer, one or more hidden layers, and an output layer. Each layer of the plurality of layers may include one or more nodes (or artificial neurons). Outputs of all nodes in the input layer may be coupled to at least one node of the hidden layer(s). Similarly, inputs of each hidden layer may be coupled to outputs of at least one node in other layers of the neural network. Outputs of each hidden layer may be coupled to inputs of at least one node in other layers of the neural network. Node(s) in the final layer may receive inputs from at least one hidden layer to output a result.

[0088] The number of layers and the number of nodes in each layer may be determined from hyper-parameters of the neural network. Such hyper-parameters may be set before or while training the neural network on a training dataset. Each node of the neural network may correspond to a mathematical function (e.g., a sigmoid function or a rectified linear unit) with a set of parameters, tuneable during training of the neural network. The set of parameters may include, for example, a weight parameter, a regularization parameter, and the like. Each node may use the mathematical function to compute an output based on one or more inputs from nodes in other layer(s) (e.g., previous layer(s)) of the neural network. All or some of the nodes of the neural network may correspond to the same or a different mathematical function.

[0089] In the training of the ML model(s) 204D, one or more parameters of each node of the neural network may be updated based on whether an output of the final layer for a given input (from a training dataset) matches a correct result based on a loss function for the neural network. The above process may be repeated for the same or a different input until a minimum loss function may be achieved, and a training error may be minimized. Several methods for training are known in the art, for example, gradient descent, stochastic gradient descent, batch gradient descent, gradient boost, meta-heuristics, and the like.

[0090] The ML model(s) 204D may include electronic data, such as, for example, a software program, code of the software program, libraries, applications, scripts, or other logic or instructions for execution by a processing device, such as circuitry. The ML model(s) 204D may be implemented using hardware including a processor, a microprocessor (e.g., to perform or control the performance of one or more operations), a field-programmable gate array (LPGA), or an application-specific integrated circuit (ASIC). Alternatively, in some embodiments, the ML model(s) 204D may be implemented using a combination of hardware and software. Although in PIG. 2, the machine ML model(s) 204D are shown integrated within the system 102, the disclosure is not so limited. Accordingly, in some embodiments, the ML model(s) 204D may be a separate entity in the system 102, without deviation from the scope of the disclosure. In some embodiments, the machine learning model may be stored in a server. Examples of the machine learning model 204D may include, but are not limited to, an artificial neural network (ANN), a deep neural network (DNN), a convolutional neural network (CNN), a fully connected neural network, and / or a combination of such networks.

[0091] In some example embodiments, the I / O interface 206 may communicate with the system 102 and display the input and / or output of the system 102. As such, the I / O interface 206 may include a display and, in some embodiments, may also include a keyboard, a mouse, a joystick, a touch screen, touch areas, soft keys, one or more microphones, a plurality of speakers, or other input / output mechanisms. In one embodiment, the system 102 may include a user interface circuitry configured to control at least some functions of one or more I / O interface elements such as a display and, in some embodiments, a plurality of speakers, a ringer, one or more microphones and / or the like. The processor 202 and / or I / O interface 206 circuitry comprising the processor 202 may be configured to control one or more functions of one or more I / O interface 206 elements through computer program instructions (for example, software and / or firmware) stored on the memory 204 accessible to the processor 202.

[0092] The network interface 208 may include an input interface and output interface for supporting communications to and from the system 102 or any other component with which the system 102 may communicate. The network interface 208 may be any means such as a device or circuitry embodied in either hardware or a combination of hardware and software that is configured to receive and / or transmit data to / from a communications device in communication with the system 102. In this regard, the network interface 208 may include, for example, an antenna (or multiple antennae) and supporting hardware and / or software for enabling communications with a wireless communication network. Additionally, or alternatively, the network interface 208 may include the circuitry for interacting with the antenna(s) to cause transmission of signals via the antenna(s) or to handle receipt of signals received via the antenna(s). In some environments, the network interface 208 may alternatively or additionally support wired communication. As such, for example, the network interface 208 may include a communication modem and / or other hardware and / or software for supporting communication via cable, digital subscriber line (DSL), universal serial bus (USB), or other mechanisms. In some embodiments, the network interface 208 may enable communication with a cloud-based network to enable deep learning, such as using the machine learning model 204D (that may be hosted on the cloud-based network).

[0093] FIG. 3 illustrates a block diagram 300 depicting operations for identifying a jaw type of at least a portion of a dental scan of the jaw 110 of the patient 112 during a scanning session, in accordance with an embodiment of the disclosure. FIG. 3 is explained in conjunction with elements from FIG. 1 and FIG. 2. The operations may start at 302.

[0094] At 302, data acquisition operation may be executed. In an embodiment, the system 102 may be configured to execute the data acquisition operation. The system 102 may obtain the scan data 204A from the intraoral scanner 104. The scan data 204A may include the image data, the gyroscopic data 204B, and the accelerometer data 204C.

[0095] In an embodiment, the scan data 204A may include the geometry information of the jaw 110 being scanned. In an embodiment, during the scanning session performed by utilizing the intraoral scanner 104, the intraoral scanner 104 may capture the images associated with one or more landmarks of the oral cavity of the patient 112. In another embodiment, the scan data may include the orientation of the one or more landmarks associated with the oral cavity or the dental scan of the patient 112. In yet another embodiment, the intraoral scanner 104 may capture the colour data associated with the oral cavity of the patient 112. The scan data 204A may include the data about the one or more landmarks of the oral cavity of the patient 112, the data about the orientation of the one or more landmarks associated with the oral cavity of the patient 112, and the colour data associated with the oral cavity of the patient 112.

[0096] In an exemplary embodiment, a user (such as, a dentist) may initiate the scanning session by positioning the intraoral scanner 104 aligned with the patient’s oral cavity. The intraoral scanner 104 may start the scanning and capturing the scan data associated with the oral cavity or the dental scan of the jaw 110 of the patient 112. The scan data may be generated by using one or more sensors associated with the intraoral scanner 104.

[0097] At 304, data analysis operation may be executed. In an embodiment, the system 102 may be configured to execute the data analysis operation. In the data analysis operation, the system 102 may provide as an input, the data to the ML model(s) 204D. The third ML model may analyse the scan data to recognize a scanning motion pattern of the intraoral scanner 104, the second ML model may analyse the scan data to recognize the one or more landmarks and the orientation data of the intraoral scanner 104. Moreover, the first ML model may analyse the scan data to identify the jaw type of at least the portion of the dental scan. The identified jaw type may indicate one of the upper jaw or the lower jaw of the patient 112.

[0098] In an exemplary embodiment, once the system 102 may obtain the scan data from the intraoral scanner 104, the system 102 may provide the obtained scan data as input to the first ML model for the data analysis. The obtained scan data may include, at least the orientation of the intraoral scanner 104, the colour data associated with the dental scan of the patient 112, and the one or more landmark information associated with the dental scan of the patient 112.

[0099] At 306A, a first jaw determination operation may be executed. In an embodiment, the system 102 may be configured to execute the first jaw determination operation. In an embodiment, the system 102 may be configured to receive output from the ML model(s) 204D. Further, based on the received output, the system 102 may be configured to determine which of the first j aw or the second j aw of the patient 112 is being scanned, i.e., the jaw type of a portion of the dental scan is which of the first jaw or the second jaw. The first jaw may either be the upper jaw or the lower jaw.

[0100] In an exemplary embodiment, based on the recognition made by the system 102 by utilizing the ML model(s) 204D, a jaw type of another portion of the dental scan of the jaw 110 being scanned may be determined. In an exemplary scenario, if the orientation of the intraoral scanner 104 and the recognized one or more landmarks for a first portion of the dental scan indicates to be associated with the first jaw and may be associated with the upper jaw, then the system 102 may determine that the first jaw for the first portion of the dental scan corresponds to the upper jaw.

[0101] At 306B, a second jaw determination operation may be executed. In an embodiment, the system 102 may be configured to execute the second jaw determination operation based on the identified jaw type of the first portion of the dental scan, i.e., the first jaw.

[0102] In an exemplary embodiment, if the orientation of the intraoral scanner 104 and the recognized one or more landmarks for a second portion of the dental scan indicates to be associated with the second jaw and may be associated with the lower jaw, then the system 102 may determine that the second jaw for the second portion of the dental scan corresponds to the lower jaw.

[0103] In an example, the jaw type for a first portion of the dental scan is identified to be associated with the first jaw, say the first jaw being the upper jaw. Thereafter, the gyroscopic data 204B is analyses to detect an orientation change value of the intraoral scanner 104. For example, after the identification of the jaw type of the first portion of the dental scan, the orientation changes value of the intraoral scanner 104 may be determined. Further, a determination is made whether the orientation change value is above a threshold value or not based on a comparison between the orientation change value and the threshold value. In response to determining the orientation change value to be greater than the threshold value, a jaw type for the second portion of the dental scan is identified to be associated with the second jaw, say the lower jaw. The threshold value may be, for example, 120 degrees. In a scenario, where the change in orientation of the intraoral scanner 104 may be above the threshold value, the system 102 may determine that the second jaw is being scanned. For example, if the first portion corresponds to the first jaw (such as the upper jaw) being scanned at a first timestamp (such as 12:00:00), and then there was a change in orientation of the intraoral scanner 104 greater than the threshold value, then the system 102 may determine that the second portion of the dental scan at a second timestamp (such as 12: 10:00) corresponds to the second jaw (or lower jaw) is being scanned.

[0104] At 308A, a first 3D digital representation generation operation may be executed. In an embodiment, the system 102 may be configured to generate the first 3D digital representation associated with the first portion of the dental scan corresponding to the first jaw.

[0105] In an exemplary embodiment, once the system 102 may have determined the jaw type that is being scanned, the system 102 may assign the determined jaw type as the first jaw for the first portion. In a scenario, when the user initiated the scanning session, the system 102 may obtain the scan data from the intraoral scanner 104 and the system 102 may identify which jaw of the patient 112 is being scanned based on the analysis of the scan data captured by the intraoral scanner 104. The scan data may correspond to the data captured by the intraoral scanner at the first time stamp. In an embodiment, if the determined jaw type may be the upper jaw, the system 102 may assign the first jaw as the upper jaw of the patient 112. Further, the system 102 may generate 3D digital representation of the first jaw. In an embodiment, the system 102 may display the generated 3D digital representation of the first jaw on the displaying unit 106. In another scenario, if the determined jaw may be the lower jaw, then the system 102 may assign the first jaw as the lower jaw of the patient 112. Further, the system 102 may generate 3D digital representation of the first jaw. In an embodiment, the system 102 may display the generated 3D digital representation of the first jaw on the displaying unit 106.

[0106] At 308B, a second 3D digital representation generation operation may be executed. In an embodiment, the system 102 may be configured to generate the second 3D digital representation associated with the second jaw.

[0107] In an exemplary embodiment, once the system 102 may have determined the first jaw type that is being scanned, the system 102 may obtain and analyse second data at the second timestamp. Based on the analysis of the second data, the system 102 may determine the second jaw that is being scanned at the second timestamp. In a scenario, upon the determination of the first jaw, the system 102 may obtain second data from the intraoral scanner 104 and the system 102 may start to determine which jaw of the patient 112 is being scanned based on the analysis of the second data captured by the intraoral scanner 104. The second data may correspond to the data captured by the intraoral scanner 104 at the second timestamp. In an embodiment, if the determined jaw may be the upper jaw, the system 102 may assign the second jaw as the upper jaw of the patient 112. Further, the system 102 may generate 3D digital representation of the second jaw. In an embodiment, the system 102 may display the generated 3D digital representation of the second j aw on the displaying unit 106. In another scenario, if the determined jaw may be the lower jaw, then the system 102 may assign the second jaw as the lower jaw of the patient 112. Further, the system 102 may generate 3D digital representation of the second jaw. In an embodiment, the system 102 may display the generated 3D digital representation of the second jaw on the displaying unit 106.

[0108] FIG. 4 is a diagram 400 that illustrates the processing of the scan data 204A obtained from the intraoral scanner 104 by utilizing the processing module 202C of the processor 202, in accordance with an embodiment of the disclosure. FIG. 4 is explained in conjunction with elements from FIG. 1 - FIG.3.

[0109] At 402, the system 102 may be configured to obtain the scan data from the intraoral scanner 104. The system 102 may process the obtained scan data by utilizing the processing module 202C of the processer 202. The processing module 202C may receive as input, the obtained scan data and perform processing operations to determine processed data. In an example, the scan data may include the gyroscopic data 204B, accelerometer data 204C, compass data, image data, colour data, and geometry information.

[0110] At 404, the system 102 may be configured to utilize the processing module 202C to generate an output. The generated output may include at least an orientation 404A of the intraoral scanner 104, an orientation 404B of one or more landmarks, and one or more scanning motion patterns 404C. In an embodiment, during the scanning session the intraoral scanner 104 may scan the jaw 110 of the patient 112. During the scanning session, the intraoral scanner 104 may capture, using the one or more sensors, the scan data associated with the jaw 110 of the patient 112. The captured scan data may be then processed by the system 102 by utilizing the processing module 202C.

[0111] In one embodiment, the gyroscope associated with the intraoral scanner 104 may generate orientation data associated with the orientation 404A of the intraoral scanner 104. The determined orientation 404A of the intraoral scanner 404A may ensure accurate alignment of the intraoral scanner 104. The determined orientation 404A of the intraoral scanner 104 may be further used to register scanned surface data and compute position and orientation of the intraoral scanner 104, which is essential for generating a precise 3D digital representation of at least the part of the jaw 110 that is being scanned.

[0112] In another embodiment, the intraoral scanner 104 may generate orientation data 404B of one or more landmarks. During the scanning session, the intraoral scanner 104 may constantly check for the one or more landmarks in the dental scan associated with the oral cavity of the patient 112. The captured one or more landmarks may include at least the one or more of the tooth-gingiva line, the tongue, the palate, the specific tooth such as canine, the bi-cuspid, the incisor, the interior, the pre-molar or molar, the lips, the cusps, and / or the fissures.

[0113] Further, the system 102 may be configured to provide as input the captured one or more landmarks to the processing module 202C of the processor 202. The processing module 202C may process the captured one or more landmarks to determine the orientation 404B of the one or more landmarks.

[0114] In another embodiment, the accelerometer associated with the intraoral scanner 104 may be configured to capture scanning motion pattern data. The processor 202 may receive the scanning motion pattern data from the accelerometer of the intraoral scanner 104. The received scanning motion pattern data may be processed using the third ML model. The accelerometer may measure acceleration and deceleration of the intraoral scanner 104 as it may move around or within the oral cavity of the patient 112, while the gyroscope may measure the orientation and rotation of the intraoral scanner 104. To this end, the scanning motion pattern data from the accelerometer and the gyroscopic data 204B from the gyroscope may be input into a third ML model. The third ML model is trained to recognize one or more scanning motion patterns 404C indicative of scanning of an upper jaw and / or a lower jaw.

[0115] This data may be used to align the image data captured by the intraoral scanner 104 properly, ensuring accurate registration and motion sensing during the scanning session. The scanning motion patterns 404C may indicate specific movements of the intraoral scanner 104 to capture detailed images of the jaw 110 and surrounding tissues. This movement typically includes a combination of linear and rotational motions, which are tracked by the accelerometer and the gyroscope to ensure precise alignment of the images. Based on an output received from the third ML model, the processor 202 may be configured to determining whether at least the portion of the dental scan of the jaw is be associated with the upper jaw or the lower jaw. Subsequently, the jaw type for at least the portion of the dental scan of the jaw is assigned to be the upper jaw or the lower jaw. For example, if the portion of the dental scan corresponds to the first jaw and the processor 202 determines that the portion of the dental scan of the jaw 110 is associated with the upper jaw, then a jaw type of the first jaw is assigned as the first jaw.

[0116] In yet another embodiment, the system 102 may be configured to control the intraoral scanner 104 to capture the geometry information of the jaw 110. The geometry information of the jaw may include position, shape and orientation of teeth and surrounding structure inside the oral cavity of the patient 112. Further, the system 102 may be configured to provide, as input, the captured geometry information of the jaw 110, to the processing module 202C. The processing module 202C may process the received geometry information of jaw 110 with orientation 404A of the intraoral scanner 104 to determine the orientation 404B of the one or more landmarks.

[0117] Further, the output 404 from the processing module 202C that may include the determined orientation 404A of the intraoral scanner 104, the determined orientation 404B of one or more landmarks, and the determined scanning motion patterns 404C. These output 404 may be provided as input, to the ML model(s) 204D for identifying the jaw type for the portion(s) of the dental scan of the jaw 110.

[0118] FIG. 5 is a diagram 500 that illustrates exemplary operations for identification of jaw types, in accordance with an embodiment of the disclosure. FIG. 5 is explained in conjunction with elements from FIG. 1 - FIG.4. The exemplary operations illustrated in the block diagram 500 may start at 502 and may be performed by the system 102 of FIG. 1 or the processor 202 of FIG. 2. Although illustrated with discrete blocks, the exemplary operations associated with one or more blocks of the block diagram 500 may be divided into additional blocks, combined into fewer blocks, or eliminated, depending on the particular implementation.

[0119] At 502, the scan data 204A may be obtained from the intraoral scanner 104. In an embodiment, the system 102 may be configured to receive the scan data 204A from one or more sensors of the intraoral scanner 104. The one or more sensors may include at least camera sensors, motion sensors, touch sensors and voice sensors.

[0120] At 504, the obtained scan data 204A may be processed. In an embodiment, the system 102 may be configured to determine orientation data and the scanning motion patterns 404C based on the obtained scan data 204A. The scanning motion pattern 404C may be determined based on the obtained scan data 204A.

[0121] At 506, the processed scan data is analysed by the ML model(s) 204D to generate an output. The ML model(s) 204D may analyse the processed scan data to determine the scanning motion patterns 404C, the orientation 404A of the intraoral scanner 104 and the orientation 404B of the one or more landmarks. In an exemplary embodiment, the scanning motion patterns 404C may be recognized by the third ML model based on comparing motion patterns of the intraoral scanner 104 with pre-determined motion patterns. The third ML model 204D may be trained on the pre-determined motion patterns. The predetermined motion patterns may be associated with the upper jaw and the lower jaw.

[0122] At 508, a determination is made to check whether a portion of the dental scan of the jaw 110, i.e., a first jaw, being scanned is the upper jaw, based on the recognized scanning motion patterns 404C and the orientation 404A and 404B. For the first jaw, i.e., a first portion of the dental scan of a first part of the jaw 110, the determination is made whether the first jaw is upper jaw or not.

[0123] If the first jaw is identified to be the upper jaw, then, at 510, the first jaw is assigned to be the upper jaw. In other words, the first portion of the dental scan corresponding to the first part of the jaw 110 is assigned to be the upper jaw of the patient 112.

[0124] Thereafter, at 512, a second portion of the dental scan of the jaw 110, i.e., a second jaw, is identified to be the lower jaw. For the second jaw, i.e., the second portion of the dental scan of a second part of the jaw 110, is assigned to be the lower jaw of the patient 112.

[0125] Alternatively, if at 508, the first jaw is not identified to be the upper jaw, then, at 514, the first jaw is identified to be the lower jaw. In this regard, the first portion of the dental scan corresponding to the first part of the jaw 110 is assigned to be the lower jaw of the patient.

[0126] Thereafter, at 516, the second portion of the dental scan of the jaw 110, i.e., the second jaw, is identified to be the upper jaw.

[0127] FIG. 6 is a diagram 600 that illustrates exemplary operations for an analysis of first data and the second data for generation of the 3D digital representation associated with the first jaw and the second jaw, in accordance with an embodiment of the disclosure. FIG. 6 is explained in conjunction with elements from FIG. 1 - FIG.5. The operations may start at 602.

[0128] At 602, the system 102 may associate the first jaw with the first data. In an embodiment, the first data may be obtained by the system 102 from the intraoral scanner 104 when the user of the system 102 may initiate the scanning session of the jaw 110 of the patient 112. For example, if the scanning process is initiated at a first timestamp (such as 12:00:00), then the data that may be received from the first time stamp until a change in an orientation of the intraoral scanner 104 is detected may be identified as the first data. For example, the first data is associated with the scanning of the first portion of the dental scan or the first part of the jaw 110.

[0129] Further, the system 102 may be configured to analyse the first data by utilizing the ML model(s) 204D to determine which jaw type is being scanned after the first timestamp. The ML model(s) 204D may process the first data and determine whether the upper jaw or the lower jaw is being scanned. For example, based on the analysis of the first data, the ML model(s) 204D may determine that the jaw type that is being scanned is the upper jaw, then the first jaw may be associated with the upper jaw. In an alternate example, based on the analysis of the first data, if the ML model(s) 204D may determine that the jaw type that is being scanned by the intraoral scanner 104 may be the lower jaw, then the system 102 may associate the first jaw with the lower jaw.

[0130] At 604, the system 102 may be configured to detect a change in an orientation of the intraoral scanner 104. The change may indicate a start of a change in degrees of an orientation of the intraoral scanner 104. Based on detecting the change in the orientation, the system 102 is configured to generate second data. For example, the second data is a part of the scan data 204A that is received after the change in the orientation is detected.

[0131] At 606, the second data is analysed.

[0132] At 608, a determination is made whether an orientation change value is greater than a threshold value or not. The orientation change value may indicate an extent, such as a degree of change in the orientation of the intraoral scanner 104. In an example, the system 102 may be configured to compare the orientation change value with the threshold value.

[0133] If the orientation change value is greater than the threshold value, at 610, the second data is identified to be associated with the second jaw, i.e., the second portion of the dental scan or the second part of the jaw 110. Subsequently, the system 102 may be configured to generate a second 3D digital representation based on the second data. In this case, the first data is identified to be associated with the first data of the first jaw. Subsequently, the system 102 may be configured to generate a first 3D digital representation based on the first data.

[0134] In an exemplary embodiment, at a first timestamp, the orientation of the intraoral scanner 104 may be between the range of, for example, but not limited to, 45 degrees Northeast and 45 degrees Northwest, and at a second timestamp, the orientation of the intraoral scanner 104 may be between the range of, for example, but not limited to, 45 degrees Southwest and 45 degrees Southeast. The threshold value may be, for example, but not limited to, 120 degrees. In a scenario, where the change in the orientation of the intraoral scanner 104 maybe above 120 degrees, then the system 102 may determine, based on the orientation change, that the second jaw is being scanned.

[0135] If the orientation change value is not greater than the threshold value, at 612, the second data is identified to be associated with the first data of the first jaw, i.e., the first portion of the dental scan or the first part of the jaw 110. Subsequently, the system 102 may be configured to generate the first 3D digital representation based on the first data and / or the second data.

[0136] FIG. 7 is a diagram 700 that illustrates analysis of scan data associated with an orientation of the intraoral scanner 104 and an orientation of one or more landmarks for determination of a jaw type, in accordance with an embodiment of the disclosure. FIG. 7 is explained in conjunction with elements from FIG. 1 - FIG.6.

[0137] At 702, the system 102 may be configured to analyse the scan data received from the intraoral scanner 104. The system 102 may provide, as an input, the orientation 404A of the intraoral scanner 104, and the orientation 404B of one or more landmarks to the ML model(s) 204D. In an embodiment, the system 102 may use the gyroscopic data 204B to determine the orientation 404A of the intraoral scanner 104. The system 102 may provide the orientation 404A ofthe intraoral scanner 104 to the processing module 202C. In an example, the orientation 404A of the intraoral scanner 104 may be provided as input to the ML model(s) 204D for the analysis.

[0138] Further, the system may use the scan data 204A, specifically, the geometry information of the jaw, the image data and the colour data associated with the jaw 110, to determine the orientation 404B of one or more landmarks. Further, the orientation 404B of the one or more landmarks may be provided as input to the ML model(s) 204D for the analysis.

[0139] At 704, the system 102 may be configured to identify a jaw type of a portion of a dental scan of the jaw that is being scanned. The system 102 may input the determined orientation 404A of the intraoral scanner 104 and the determined orientation 404B of the one or more landmarks in the ML model(s) 204D. The ML model(s) 204D may combine information about the determined orientation 404A of the intraoral scanner 104 and the recognized orientation 404B of the one or more landmarks to identify which of the first or second jaw is being scanned.

[0140] In an exemplary embodiment, if the determined orientation 404A of the intraoral scanner 104 may indicate that the first portion of the dental scan corresponds to the upper jaw (such as, orientation may be towards 45 degrees Northeast), and the determined orientation 404B of the one or more landmarks may be recognized as the one or more landmarks associated with the upper jaw (such as palate), then the ML model(s) 204D may determine that the first portion of the dental scan that is being scanned may correspond to the upper jaw.

[0141] FIG. 8 is a diagram 800 that illustrates exemplary operations for compass calibration for identifying a jaw type, in accordance with an embodiment of the disclosure. FIG. 8 is explained in conjunction with elements from FIG. 1 - FIG.7. The exemplary operations illustrated in the block diagram 800 may start at 802 and may be performed by the system 102 of FIG. 1 or the processor 202 of FIG. 2. Although illustrated with discrete blocks, the exemplary operations associated with one or more blocks of the block diagram 800 may be divided into additional blocks, combined into fewer blocks, or eliminated, depending on the particular implementation.

[0142] At 802, the scan data 204A obtained from the intraoral scanner 104 may be analysed. In an embodiment, the system 102 may be configured to analyse the scan data 204A obtained from the intraoral scanner 104 to determine the orientation 404A of the intraoral scanner 104. The scan data 204A obtained from the intraoral scanner 104 may include at least the gyroscopic data 204B. The gyroscopic data 204B may be used to determine the orientation 404A of the intraoral scanner 104.

[0143] In an exemplary embodiment, the gyroscopic data 204B obtained from the intraoral scanner 104 may be analysed by the ML model(s) 204D to determine the orientation 404A of the intraoral scanner 104. A detailed explanation of the analysis operation is provided in conjunction with FIG.7, and a detailed explanation of a steps for determining the orientation 404A of the intraoral scanner 104 is provided in conjunction with FIG. 4.

[0144] At 804, a user interaction data reception operation may be performed. In an embodiment, the system 102 may be configured to retrieve the user interaction data associated with the intraoral scanner 104. The user interaction data may indicate a pointing direction of the intraoral scanner 104. The pointing direction of the intraoral scanner 104 may be used to determine whether at least a part of the jaw 110 being scanned by the intraoral scanner 104 is the first jaw or the second jaw. The user interaction data may further correspond to an initiation of a compass calibration operation for jaw type identification.

[0145] In an exemplary embodiment, the patient 112 may lie down in a clinic during the scanning session in at least, but not limited to, a north direction, or a south direction. The pointing direction of the intraoral scanner 104 in that case may be at least one of the north direction or the south direction. The user interaction data in that case may include an indication of a positioning or holding of the intraoral scanner 104 in the north direction or the south direction.

[0146] In another exemplary embodiment, the patient 112 may lie down in the clinic during the scanning session in at least, but not limited to, an east direction or a west direction. The pointing direction of the intraoral scanner 104 in that case may be the east direction or the west direction. The user interaction data in that case may include an indication of a positioning or holding the intraoral scanner 104 in the east direction or the west direction.

[0147] In yet another exemplary embodiment, at a first timestamp, the pointing direction of the intraoral scanner 104 may be between a range of, for example, but not limited to, 30 degrees Northeast and 30 degrees Northwest. Further, at a second timestamp, the pointing direction of the intraoral scanner 104 may be between a range of, for example, but not limited to, 30 degrees Southwest and 30 degrees Southeast.

[0148] Further, an orientation determination operation may be performed. In an embodiment, the system 102 may be configured to cause the ML model(s) 204D to analyse the gyroscopic data 204B to determine the orientation 404A of the intraoral scanner 104. The ML model(s) 204D may analyse the gyroscopic data 204B. A detailed explanation of the orientation determination operation is provided in FIG.5. In an exemplary embodiment, at a first timestamp, the orientation of the intraoral scanner 104 may be between a range of, for example, but not limited to, 30 degrees Northeast and 30 degrees Northwest, and at a second timestamp, the orientation of the intraoral scanner 104 may be between a range of, for example, but not limited to, 30 degrees Southwest and 30 degrees Southeast.

[0149] At 806, a compass calibration operation may be performed. In an embodiment, the system 102 may be configured to calibrate a direction of an internal compass of the intraoral scanner 104 based on the determined orientation 404A of the intraoral scanner 104 and the pointing direction. The calibrated compass direction of the internal compass is used to identify the jaw type of at least the portion of the dental scan during the scanning session. The calibrated compass direction may indicate the pointing direction of the patient 112. The calibrated compass direction may be further used to determine which jaw is being scanned at during the scanning session.

[0150] In an exemplary embodiment, at a first timestamp, the internal compass direction may be between a range of, for example, but not limited to, 45 degrees Northeast and 45 degrees Northwest, and at a second timestamp, the internal compass direction may be between a range of, for example, but not limited to, 45 degrees Southwest and 45 degrees Southeast.

[0151] The ML model(s) 204D may be further configured to analyse the calibrated direction of the internal compass. In an embodiment, the calibrated direction is used to determine whether at least the portion of the dental scan of the part of the jaw being scanned is the first jaw or the second jaw. The ML model(s) 204D may be configured to analyse the calibrated compass direction and generate an output based on the analysis. The output may be indicative of the jaw type being scanned is the first jaw or the second jaw.

[0152] In additional embodiments, the ML model(s) 204D may determine the calibrated direction at the first timestamp and the second timestamp. The ML model(s) 204D may further compare a difference between the calibrated direction at the first timestamp and the calibrated direction at the second timestamp with a pre-determined threshold value. The ML model(s) 204D may generate the output when the difference is greater than the pre-determined threshold. Similarly, the difference in orientations of the intraoral scanner 104 may be compared with the threshold value to determine whether the jaw types being scanned is the first jaw or the second jaw, which is explained in FIG. 7.

[0153] In an example embodiment, at the first timestamp the calibrated direction may be for example, but not limited to, 45 degrees Northeast and at a second timestamp, the calibrated direction may be for example, but not limited to, 45 degrees Southwest. The pre-determined threshold may be, for example, but not limited to, 120 degrees. The difference between the calibrated directions at the first timestamp and the second timestamp in that case is 180 degrees which is greater than the threshold value. The ML model(s) 204D may generate the output indicative of the jaw type being scanned to be the second jaw owing to the downward pointing direction of the intraoral scanner 104 with respect to a patients’ chair in the dental clinic.

[0154] To an end, at 808, the jaw type determination operation may be performed. In an embodiment, the system 102 may be configured to determine whether the part of the jaw 110 being scanned is the first jaw or the second jaw based on the output of the ML model(s) 204D. The ML model(s) 204D may generate an output based on when the difference is greater than the pre-determined threshold. The output may be indicative of the jaw type being scanned. Once the jaw type of the part of the jaw 110 being scanned is identified to be the second jaw, the system 102 may continue to assume the portion of the dental scan for the part of the jaw to be the second jaw until a change in calibrated direction is determined or sensed. A detailed explanation of the jaw type determination operation is provided in FIG.7.

[0155] FIG. 9 is a diagram 900 that illustrates exemplary operations for parallel reconstructions of the j aw 110, in accordance with an embodiment of the disclosure. FIG. 9 is explained in conjunction with elements from FIG. 1 - FIG.8. The exemplary operations illustrated in the block diagram 900 may start at 902 and may be performed by the system 102 of FIG. 1 or the processor 202 of FIG. 2. Although illustrated with discrete blocks, the exemplary operations associated with one or more blocks of the block diagram 900 may be divided into additional blocks, combined into fewer blocks, or eliminated, depending on the particular implementation.

[0156] At 902, a first 3D digital representation of the first jaw being scanned may be generated. In an embodiment, the system 102 may be configured to generate the first 3D representation of the first jaw corresponding to a first portion of the dental scan or a first part of the jaw 110 being scanned based on the obtained scan data. The ML model(s) 204D may determine whether the first jaw being scanned may correspond to the upper jaw or the lower jaw. The system 102 may generate the first 3D digital representation of the first jaw being scanned based on the determination.

[0157] In an example embodiment, the ML model(s) 204D may analyse the orientation 404A of the intraoral scanner 104 and the orientation 404B of the one or more landmarks to identify whether the first jaw being scanned correspond to the upper jaw or the lower jaw.

[0158] At 904, a pause may be detected in the scanning session of the patient. In an embodiment, the system 102 may be configured to detect a pause in the scanning session when no scan data is obtained or received for a period of time, say 10 seconds, 30 seconds, 1 minute, etc. The pause may be indicative of a break in the scanning session. The pause in the scanning session may correspond to a break in the retrieval of the scan data 204A from the intraoral scanner 104.

[0159] At 906, a new scan data may be received after the pause. Based on receiving the new scan data, the system 102 may be configured to perform two operations in parallel. In this regard, at 908, the system 102 may be configured to perform a first operation to register the new scan data into the first 3D digital representation of the first jaw of the patient 112. In an embodiment, the system 102 may be configured to continuously attempt to register the new scan data into the existing first 3D digital representation of the first jaw of the patient 112 after the restarting of the scanning session after the pause. The new scan data may correspond to a part of the scan data 204A received after the pause. The existing first 3D digital representation may correspond to a 3D model of the first jaw.

[0160] In an exemplary embodiment, the first jaw being scanned corresponds to the upper jaw. The user may take a pause or a break during the scanning process. The system 102 may completely or partially construct the first 3D digital representation corresponding to the upper jaw of the patient before the pause. The user may continue the scanning process after a pause or a break. Subsequently, the first 3D digital representation may be updated based on the new scan data.

[0161] At 910, the system 102 may be configured to perform a second operation in parallel to the firstoperation to generate a new 3D digital representation based on the new scan data. In an example, a separate 3D model, i.e., the new 3D digital representation may be constructed based on the new scan data. In an embodiment, the system 102 may be configured to generate the new 3D digital representation in parallel to construction of the first 3D digital representation based on the new scan data.

[0162] Thereafter, at 912, a determination is made whether the new scan data matches the first 3D digital representation of the first jaw. In an example, the new 3D digital representation generated based on the new scan data may be compared with the first 3D digital representation as well as the constructed update first 3D digital representation based on the new scan data are analysed to check whether the new scan data is associated with the first jaw or not.

[0163] At 914, the new scan data is registered in association with the first 3D digital representation of the first part of the jaw of the patient 112 based on determining a match between the new scan data or the new 3D digital representation and the first 3D digital representation based on the first operation and / or the second operation. In this regard, the new scan data is considered to be a part of the construction of the first jaw. Subsequently, a second 3D digital representation of the second jaw or the lower jaw may be constructed based on second scan data that may be received at a later stage, such as when a change in the orientation of the intraoral scanner 104 is greater than the threshold value.

[0164] Alternatively, at 916, when the new scan data does not match with the first 3D digital representation, a jaw type associated with the new scan data is identified to be different from the identified jaw type of at least the portion of the dental scan corresponding to the first 3D digital representation. In other words, the jaw type for the new scan data is identified to be the second jaw based on identifying that the new scan does not match with the first 3D digital representation of the first jaw. Subsequently, the new 3D digital representation generated during the second operation is identified to be associated with the second jaw that corresponds to the lower jaw of the patient 112. As a result, new 3D digital representation may form a second 3D digital representation corresponding to the second jaw of the patient.

[0165] FIG. 10 is a diagram 1000 that illustrates an exemplary method for identifying a jaw type based on a user input and an orientation of the intraoral scanner 104, in accordance with an embodiment of the disclosure. FIG. 10 is explained in conjunction with elements from FIG. 1- FIG.9.

[0166] In an embodiment, the system 102 may be configured to identify whether the part of the jaw 110 that the first jaw or the second jaw. The jaw 110 of the patient 112 may be scanned based on the one or more sensors of the intraoral scanner 104. The scan data 204A or input received by the system 102 from a user and / or the intraoral scanner 104 is analysed to identify the jaw type of the part of the jaw being scanned.

[0167] At 1002, a user input reception operation is performed. The user input received from the user may be user input data. In an example, the user input data is received from the user via the intraoral scanner. The user input data may include one or more interactions with a button or touch sensor on the intraoral scanner 104. Further, the one or more interactions that may be obtained by the system 102 through the intraoral scanner 104 may be, for example, but not limited to, shaking the intraoral scanner 104 in a predetermined pattern to indicate the jaw type of the part of the jaw being scanned, double clicking the button on the intraoral scanner 104 while holding the scanner in an orientation indicative of the jaw type of the part of the jaw being scanned, a button activation pattern indicative of the jaw type of the part of the jaw being scanned, a voice control indicating the jaw type of the part of the jaw being scanned, a swipe pattern on touch sensor indicative of the jaw type of the part of the jaw being scarmed, and an interaction with a dedicated button on the intraoral scanner such as an arrow button or the touchpad to indicate the jaw type of the part of the jaw being scanned.

[0168] Further, at 1004, the system 102 is configured to analyse the scan data. In an example, the system 102 is configured to combine the user input data and the determined orientation 404A of the intraoral scanner 104 to determine which of the first jaw or the second jaw is being scanned. In an exemplary embodiment, if the system 102 may analyse the determined orientation 404A of the intraoral scanner and determined that the jaw type that is being scanned corresponds to the upper jaw, the system 102 may display a result of the analysis of the determined orientation of the intraoral scanner 404A on the displaying unit 106. In an example, the result may be displayed as a first 3D digital representation of upper jaw based on identifying the jaw type for the part of the jaw being scanned to be the upper jaw. The system 102 may receive the user input data from the user via the intraoral scanner 104 to confirm if the identified jaw type for the received scan data corresponding to a portion of the dental scan is correct or not. The user may provide the user input data as the input by performing one or more interactions with the button or the touch sensor on the intraoral scanner 104. In a scenario, where the system 102 determines that the jaw that is being scanned corresponds to the upper jaw, the system 102 may receive the user input indicating that the identification of the jaw type to be the upper jaw is correct or not.

[0169] In an exemplary embodiment, if the system 102 may analyse the determined orientation 404A of the intraoral scanner 104 and identifies that the jaw type of the part of the jaw that is being scanned corresponds to the lower jaw, the system 102 may display the result of the analysis of the determined orientation of the intraoral scanner 404A on the displaying unit 106. The system 102 may receive the user input data from the user via the intraoral scanner 104 to confirm if the identified jaw type to be the lower jaw is correct or not. The user may provide the user data as the input by performing one or more interactions with the button or the touch sensor on the intraoral scanner 104. In a scenario, where the system 102 determines that the part of the jaw that is being scanned corresponds to the lower jaw, the system 102 may receive the user input indicating that the determination made is correct.

[0170] At 1006, the jaw type of at least a part of the jaw 110 is identified based on the orientation 404A of the intraoral scanner 104 and the user input data. In an embodiment, the system 102 may be configured to receive as the input the user input to cause the system to move to a next step in a workflow, or move to the previous step in the workflow, or move to a specific step in the workflow depending on the user input. In an embodiment, the workflow may be the scanning process of the dental object 110 of the patient 112. The dental object 110 may include the upper jaw or the lower jaw.

[0171] For example, during the scanning process, the user can provide the user input as to which jaw (the upper jaw or the lower jaw) is being scanned. If at the first timestamp, the user may be scanning the upper jaw and wants to move on the scanning process of the lower jaw, then the user may provide input to the system 102 via the intraoral scanner 104 causing the system 102 to move to the next step in the workflow. The next step in the workflow may be the scanning process of the lower jaw. Further, if at a third timestamp, the user may want to scan the upper jaw again, the user may provide the user input via the intraoral scanner 104 that may cause the system 102 to move to previous step in the workflow. The previous step may correspond to the scanning process of the upper jaw. Similarly, if the user may want to perform the bite scan, the user may provide as the user input to move to the specific step in the workflow. The specific step may correspond to the bite scan.

[0172] FIG. 11 is a flowchart 1100 that illustrates an exemplary method for generating first three-dimensional digital representation, in accordance with an embodiment of the disclosure. FIG. 11 is explained in conjunction with elements from FIG. 1- FIG.10. The operations of the exemplary method may be executed by the system 102 of FIG. 1 or the processor 202 of FIG. 2. The operations of the flowchart 1100 may start at 1102. At 1102, the scan data 204A of a dental scan may be obtained from the intraoral scanner 104. In an embodiment, the system 102 may be configured to obtain the scan data 204A from the one or more sensors associated with the intraoral scanner 104. The scan data 204A may include the gyroscopic data 204B, image data, the accelerometer data 204C and / or compass data. The scan data 204A may further include geometry information, landmark information and colour data associated with the jaw 110 to be scanned.

[0173] In an exemplary embodiment, the one or more sensors may include at least the camera sensors, the touch sensors, the motion sensors, the media sensors or the voice sensors. The one or more sensors may be configured to generate or sense the scan data 204A which may be obtained by the system 102.

[0174] At 1104, the scan data 204A of the dental scan may be analysed to identify a jaw type of at least a portion of the dental scan. In an embodiment, the system 102 may be configured to control the ML model(s) 204D to identify the jaw type of a portion of the dental scan. The identified jaw type is one of a first jaw, or a second jaw. The ML model(s) 204D may determine the orientation 404A of the intraoral scanner 104 based on the gyroscopic data 204B. The ML model(s) 204D may further determine the orientation 404B of one or more landmarks of the jaw based on the landmark information.

[0175] At 1106, a first 3D digital representation of at least the part of the jaw 110 being scanned may be generated based on the scan data and the identified jaw type associated with at least the portion of the dental scan. In an embodiment, the system 102 may be configured to generate the first 3D digital representation of at least the part of the jaw 110 being scanned, based on the identification whether the first jaw or the second jaw is being scanned. The displaying unit 106 of the system 102 may be further configured to output the first 3D digital representation of the jaw 110 being scanned. After the scanning of the first jaw, the second jaw may be scanned. As a result, a second 3D digital representation may be generated. The first 3D digital representation and the second 3D digital representation may form a 3D model of the jaw of the patient 112.

[0176] In an exemplary embodiment, the system 102 may determine that the part of the jaw 110 being scanned corresponds to the upper jaw based on the analysis of the obtained scan data. Further, the system 102 may generate the first 3D representation of the upper jaw. In an alternate exemplary embodiment, the system 102 may determine that the jaw being scanned corresponds to the lower jaw based on the analysis of the data and generate the first 3D representation of the lower jaw.

[0177] Accordingly, blocks of the flowchart 1100 support combinations of means for performing the specified functions and combinations of operations for performing the specified functions. It will also be understood that one or more blocks of the flowchart 1100 and can be implemented by special -purpose hardware -based computer systems which perform the specified functions, or combinations of specialpurpose hardware and computer instructions. Alternatively, the system 102 may include means for performing each of the operations described above. In this regard, according to an example embodiment, examples of means for performing operations may include, for example, the processor 202 and / or a device or circuit for executing the computer program instructions or executing an algorithm for processing information as described above.

Claims

CLAIMS1. A computer-implemented method (1100) for identifying a jaw type in a dental scan of a jaw (110) of a patient (112) during a scanning session, comprising: obtaining (1102) scan data (204A) of the dental scan from an intraoral scanner (104), wherein the scan data comprises at least one of: gyroscopic data (204B), image data, accelerometer data (204C), or compass data; analysing (1104) the scan data to identify the jaw type of at least a portion of the dental scan, wherein the identified jaw type is associated with one of: a first jaw, or a second jaw; and generating (1106) a first three-dimensional (3D) digital representation of at least a part of the jaw based on the scan data and the identified jaw type associated with at least the portion of the dental scan.

2. The computer-implemented method according to claim 1, wherein the scan data (204A) further comprises geometry information (404D) associated with the jaw (110).

3. The computer-implemented method according to claim 2, further comprising: inputting the scan data (204 A) into a trained first machine learning (ML) model; and identifying the jaw type of at least the portion of the dental scan based on an output of the trained first ML model, wherein the jaw type of at least the portion of the dental scan is one of the first jaw or the second jaw.

4. The computer-implemented method according to claim 2 or 3, wherein the scan data (204 A) further comprises colour data, and wherein analysing the scan data comprises: using the gyroscopic data (204B) to determine an orientation (404A) of the intraoral scanner (104); using the geometry information (404D) to determine an orientation (404B) of each of one or more landmarks in the dental scan; and combining the determined orientation of the intraoral scanner and the orientation of each of the one or more landmarks to identify the jaw type of at least the portion of the dental scan.

5. The computer-implemented method according to claim 4, further comprising: recognizing, using a second ML model, the one or more landmarks in the dental scan based on the scan data (204 A).

6. The computer-implemented method according to claim 4 or 5, wherein the one or more landmarks comprises at least one of: a tooth-gingiva line, a tongue, a palate, a specific candidate tooth, lips, cusps, or fissures.

7. The computer-implemented method according to any of previous claims, further comprising: receiving scanning motion pattern data from the intraoral scanner (104); inputting the received scanning motion pattern data and the gyroscopic data (204B) into a third ML model, wherein the third ML model is trained to recognize one or more scanning motion patterns (404C) indicative of scanning of at least one of: an upper jaw, or a lower jaw; receiving an output from the third ML model; based on the received output, determining at least the portion of the dental scan of the jaw (110) to be associated with one of: the upper jaw or the lower jaw; and based on the determination, assigning the jaw type for at least the portion of the dental scan of the jaw.

8. The computer-implemented method according to claim 7, further comprising at least one of: based on determining at least the portion of the dental scan to be associated with the upper jaw, assigning the jaw type to be the first jaw for at least the portion of the dental scan; or based on determining at least the portion of the dental scan to be associated with the lower jaw, assigning the jaw type to be the second jaw for at least the portion of the dental scan.

9. The computer-implemented method according to any of previous claims, further comprising: identifying a jaw type for a first portion of the dental scan to be associated with the first jaw; analysing the gyroscopic data (204B) to detect an orientation change value of the intraoral scanner (104); comparing the orientation change value and a threshold value; in response to determining the orientation change value to be greater than the threshold value, identifying a jaw type for a second portion of the dental scan to be associated with the second jaw; and generating the first 3D digital representation associated with the first portion of the dental scan and a second 3D digital representation associated with the second portion of the dental scan based on the scan data and the identified jaw type for each of the first portion and the second portion.

10. The computer-implemented method according to claim 9, wherein the identified jaw type for the first portion of the dental scan is associated with a first part of the jaw and the second portion of the dental scan is associated with a second part of the jaw, and wherein the first 3D digital representation is associated with the first jaw of the first part of the jaw and the second 3D digital representation is associated with the second jaw of the second part of the jaw.

11. The computer-implemented method according to any of previous claims, further comprising: determining an orientation of the intraoral scanner (104) based on the gyroscopic data (204B); obtaining user interaction data indicating a pointing direction of the intraoral scanner; and calibrating a direction of an internal compass of the intraoral scanner based on the orientation and the pointing direction of the intraoral scanner, wherein the internal compass is operable to generate the compass data.

12. The computer-implemented method according to claim 11, wherein the calibrated direction of the internal compass is used to identify the jaw type of at least the portion of the dental scan during the scanning session.

13. The computer-implemented method according to any of previous claims, further comprising: displaying an indication of the identified jaw type of at least the portion of the dental scan; and receiving a user feedback based on the displayed identified jaw type for at least the portion of the dental scan of the jaw (110).

14. The computer-implemented method according to any of previous claims, further comprising: receiving user input data from the intraoral scanner (104); determining an orientation (404A) of the intraoral scanner based on the gyroscopic data (204B); and combining the user input data and the determined orientation of the intraoral scanner to identify the jaw type of at least the portion of the dental scan of the jaw (110).

15. The computer-implemented method according claim 14, wherein the user input data comprises one or more user interactions with at least one of: a button, or touch sensor, on the intraoral scanner (104).

16. The computer-implemented method according to claim 15, wherein the one or more user interactions comprises at least one of: a predetermined pattern of shaking the intraoral scanner (104) to indicate the jaw type of at least the portion of the dental scan, double clicking the button on the intraoral scanner while holding the intraoral scanner in a predefined orientation to indicate the jaw type of at least the portion of the dental scan, a button activation pattern indicative of the jaw type of at least the portion of the dental scan, a voice control to indicate the jaw type of at least the portion of the dental scan,a swipe patern on the touch sensor indicative of the jaw type of at least the portion of the dental scan, or an interaction with a dedicated buton on the intraoral scanner to indicate the jaw type of at least the portion of the dental scan.

17. The computer-implemented method according to any of previous claims, further comprising: detecting a pause in the scanning session of the patient (112); receiving new scan data after the pause; performing, in parallel, a first operation to register the new scan data into the first 3D digital representation of at least the part of the jaw of the patient (112), and a second operation to generate a new 3D digital representation based on the new scan data; and in response to determining a match between the new scan data and the first 3D digital representation based on the first operation and the second operation, registering the new scan data in association with the first 3D digital representation of at least the part of the jaw (110) of the patient (112); or in response to determining the new scan data to be different from the first 3D digital representation based on the first operation and the second operation, identifying a jaw type associated with the new scan data to be different from the identified jaw type of at least the portion of the dental scan corresponding to the first 3D digital representation.

18. A dental scanning system (102) for generating a 3D digital representation of a jaw (110) of a patient (112), the dental scanning system comprising: a handheld intraoral scanner ( 104) configured to capture a dental scan of the j aw, the handheld intraoral scanner comprising a plurality of sensors, wherein the plurality of sensors comprises at least one of: a gyroscope configured to generate orientation data, or an accelerometer configured to generate motion data; one or more processors (202) configured to: determine at least one of: an orientation (404A) of the handheld intraoral scanner, or a motion of the handheld intraoral scanner based on at least one of: the orientation data, or the motion data, and analyse at least one of: the orientation, or the motion to identify a jaw type of at least a portion of the dental scan, wherein the identified jaw type is associated with one of: a first jaw, or a second jaw; and a displaying unit (106) configured to display in real-time the 3D digital representation of at least a part of the jaw of the patient based on the identified jaw type of at least the portion of the dental scan.

19. The dental scanning system (102) according to claim 18, wherein the one or more processors (202) are further configured to: identify the jaw type of at least the portion of the dental scan based on user input data from the intraoral scanner (104), and wherein the user input data is associated with at least one of: a user interaction with one or more buttons on the handheld intraoral scanner, a voice control, or a swipe pattern on a touch sensor on the intraoral scanner.

20. The dental scanning system (102) according to claim 18 or 19, wherein the one or more processors are further configured to: input at least one of: the orientation data, or the motion data into a trained first machine learning (ML) model; and identify the jaw type of at least the portion of the dental scan based on an output of the trained first ML model, wherein the jaw type of at least the portion of the dental scan is one of the first jaw and the second jaw.

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