KR20230075177A - Method, device and recording medium for displaying analysis results regarding the problem expected items according to analysis method for orthodontic diagnosis - Google Patents

Abstract

According to an embodiment, by determining the possibility of abnormality in measurement values for a plurality of analysis items based on the locations of a plurality of landmarks, and displaying problem expected measurement values or problem expected items according to the possibility of abnormality, it is out of the normal range. A method capable of providing a user-intuitive interface for a problematic item is disclosed.

Description

Method, device, and recording medium for displaying analysis results for expected items according to the analysis method used for calibration diagnosis

The present disclosure relates to a method, a device, and a recording medium for displaying analysis results related to calibration diagnosis.

In general, various radiographic images, facial photographs, etc. clinically taken are used to diagnose a patient's problem during orthodontic treatment. In addition, image analysis using various analysis methods designed for efficient diagnosis by dentists is being performed.

Conventionally, when analyzing various images required for orthodontic treatment, the user has a disadvantage in that user convenience is reduced because cumbersome procedures are required for the user, such as finding and using an analysis tool and comparing and confirming the analysis results one by one.

Accordingly, there is a demand for a technique for solving the above-mentioned problems and improving user convenience throughout the calibration diagnosis process.

Korean Patent Publication No. 10-2006-0100737 (2006.09.21) Dental patient treatment service method and system using the Internet

An embodiment of the present disclosure is to solve the above-described problems of the prior art, and provides a method, device, and recording medium capable of improving user convenience throughout the process of providing an analysis result for calibration diagnosis based on an image. I want to do it.

The technical problem to be solved is not limited to the technical problem as described above, and various technical problems may be further included within a range obvious to those skilled in the art.

A method of displaying an analysis result according to an analysis method according to a first aspect of the present disclosure includes determining locations of a plurality of landmarks with respect to an object; determining a plurality of measurement values for each of a plurality of analysis items provided by a plurality of analysis methods, based on locations of the plurality of landmarks; determining an abnormality possibility for the plurality of measured values based on statistical information on the plurality of analysis items; determining problem expected measurement values indicating some measurement values expected to have a problem among the plurality of measurement values based on the possibility of an abnormality; and displaying the problem prediction measurement value or a problem prediction item corresponding to the problem prediction measurement value.

The method may further include obtaining a user input for selecting one of the plurality of analysis methods; and displaying a plurality of measurement values for a plurality of analysis items provided by an analysis method corresponding to the user input.

In addition, the possibility of abnormality may be determined based on the average and/or standard deviation of the analysis items.

In addition, the step of displaying the problem prediction measurement value or the problem prediction item corresponding to the problem prediction measurement value may include displaying the problem prediction item corresponding to the problem prediction measurement value in a separate window distinct from a window in which the measurement value is displayed. can be displayed.

The method may further include displaying an image of the object in which the locations of the plurality of landmarks are displayed in a first window; and displaying the plurality of measurement values in a second window, wherein the problem prediction measurement value or a problem prediction item corresponding to the problem prediction measurement value is displayed in a third window, the first window and the problem prediction item. The second windows may be simultaneously displayed in regions separated from each other.

In addition, the first window overlaps and displays an image of a first view and a second view of the object, and the third window displays a measurement value of the problem prediction item at the first view and the second view. The measurement value of the viewpoint can be displayed together.

In addition, the method further includes displaying the plurality of measurement values, and the displaying of the plurality of measurement values corresponds to the degree of deviation of the plurality of measurement values from the average, respectively. Marking a point on a straight line; and displaying a first graph indicating a degree of deviation of the plurality of measurement values from an average based on the position of a point corresponding to each of the plurality of measurement values.

In addition, the displaying of the plurality of measurement values may further include displaying a second graph representing standard deviations corresponding to each of the plurality of items by overlapping the first graph with a second graph.

A device for displaying analysis results according to an analysis method according to a second aspect of the present disclosure determines locations of a plurality of landmarks with respect to an object, and measures a plurality of analysis items respectively provided by a plurality of analysis methods. A value is determined based on the locations of the plurality of landmarks, an abnormality possibility for the plurality of measurement values is determined based on statistical information on the plurality of analysis items, and a problem expected measurement value among the plurality of measurement values a processor that determines based on the probability of abnormality; and a display configured to display the problem prediction measurement value or a problem prediction item corresponding to the problem prediction measurement value.

The processor may obtain a user input for selecting one of the plurality of analysis methods, and the display may display a plurality of measurement values for a plurality of analysis items provided by an analysis method corresponding to the user input. there is.

Also, the processor may determine the abnormality probability based on the average and/or standard deviation of the analysis items.

Also, the display may display a problem prediction item corresponding to the problem prediction measurement value in a separate window distinct from a window in which the measurement value is displayed.

In addition, the display displays an image of the object in which the positions of the plurality of landmarks are displayed in a first window, displays the plurality of measurement values in a second window, and displays the problem expected measurement value or the problem expected measurement value. The third window, the first window, and the second window, in which the problem prediction item corresponding to the value is displayed, may be simultaneously displayed in areas separated from each other.

A third aspect of the present disclosure may provide a computer readable recording medium recording a program for executing the method according to the first aspect in a computer. Alternatively, the fourth aspect of the present disclosure may provide a computer program stored in a recording medium to implement the method according to the first aspect.

According to one embodiment, by providing problem expected measurement values or deviations or problem expected items that are out of the normal range through analysis of the measured values, the user can intuitively determine which part and in which aspect the problem item is related. interfaces can be provided.

In addition, user convenience can be improved by simultaneously providing an image with landmark locations, a plurality of measurement values, and problem prediction items in separate areas.

The effects of the present disclosure are not limited to the above effects, and should be understood to include all effects that can be inferred from the configuration of the disclosure described in the detailed description or claims of the present disclosure.

1 is a block diagram illustrating an example of a configuration of a device according to an exemplary embodiment.
2 is a flowchart illustrating a method of displaying an analysis result according to an analysis method by a device according to an exemplary embodiment.
3 is a view for explaining an operation in which a device determines locations of a plurality of landmarks in a lateral projection image of an object and provides analysis results for a plurality of analysis items based on the determined locations, according to an exemplary embodiment; am.
4 is a diagram illustrating problem prediction items according to an embodiment.
5 is a diagram for explaining an operation in which a device determines locations of a plurality of landmarks in a PA projection image of an object and provides analysis results for a plurality of analysis items based on the determined locations, according to an exemplary embodiment; .
6 is a diagram for explaining an operation in which a device determines locations of a plurality of landmarks in a model image of an object and provides analysis results for a plurality of analysis items based on the determined locations, according to an exemplary embodiment.
7 is a diagram for explaining an operation of a device providing a first view image and a second view image of an object, according to an exemplary embodiment.
8 is a flowchart illustrating a method of displaying an analysis result according to an analysis method by a device according to an exemplary embodiment.

The terms used in the embodiments have been selected from general terms that are currently widely used as much as possible while considering the functions in the present invention, but they may vary according to the intention of a person skilled in the art or precedent, the emergence of new technologies, and the like. In addition, in a specific case, there is also a term arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the description of the invention. Therefore, the term used in the present invention should be defined based on the meaning of the term and the overall content of the present invention, not simply the name of the term.

In the entire specification, when a part is said to "include" a certain component, it means that it may further include other components, not excluding other components unless otherwise stated. In addition, as described in the specification, "... Terms such as “unit” refer to a unit that processes at least one function or operation, which may be implemented as hardware or software, or a combination of hardware and software.

Hereinafter, with reference to the accompanying drawings, embodiments of the present invention will be described in detail so that those skilled in the art can easily carry out the present invention. However, the present invention may be implemented in many different forms and is not limited to the embodiments described herein.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

1 is a block diagram illustrating an example of a configuration of a device 100 according to an embodiment. 2 is a flowchart illustrating a method of displaying an analysis result according to an analysis method by the device 100 according to an exemplary embodiment.

Referring to FIG. 1 , a device 100 may include a processor 110 and a display 120 .

Referring to FIG. 2 , in step S210, the processor 110 may obtain an image of the object. Here, the object may include a body part (eg, head) of the patient. In an embodiment, the image of the object may include at least one of a lateral projection image, a posterior, anterior (PA) projection image, and a model image. Here, the lateral projection image represents a projection image (eg, an image of the patient's right face while the patient is looking to the right) taken from the side of the object. Also, throughout the specification, a projected image refers to an image (eg, a computed tomography (CT) image, a panoramic image, an X-ray, etc.) obtained using light rays transmitted through an object, such as X-rays. Also, the PA projection image represents a projection image taken from the front. In addition, the model image may represent a plaster model image modeled on the object or an image obtained through scanning from the plaster model or the object.

In an embodiment, the processor 110 may receive an image captured of an object from another device (eg, an image capture device). In another embodiment, the processor 110 may capture an image of an object by controlling an image capture device (not shown) included in the device 100 . In another embodiment, the processor 110 may load an image of an object stored in memory.

In step S220, the processor 110 may determine the locations of a plurality of landmarks with respect to the object. Here, the landmark represents an anatomical point on the image, and the location of the landmark can be expressed based on two-dimensional (x, y) or three-dimensional (x, y, z) location coordinates representing the location coordinate system for the image. can In one embodiment, the landmark 10 is a sella, a nasion, a pterygoid, an orbitale, a basion, and a porion used for orthodontic diagnosis. ), corpus, pogonion, anterior nasal spine (ANS), posterior nasal spine (PNS), maxillary anterior #1 root (e.g. maxilla 1 root), mandibular anterior #1 crown (e.g. mandible 1 crown), etc., but is not limited thereto, and various other anatomical points may be used. Details regarding this will be further described with reference to FIG. 3 .

FIG. 3 is a diagram in which the device 100 according to an embodiment determines projection positions representing 2D position coordinates of a plurality of landmarks 10 in a lateral projection image of an object, and analyzes a plurality of projection positions based on the determined projection positions. It is a diagram for explaining the operation of providing analysis results for items.

Referring to FIG. 3 , upon receiving a request for analysis based on a lateral projection image, the processor 110 provides a lateral projection image of an object to the display 120, and the display 120 displays the lateral projection image. It can be displayed in the first window 310. Also, the processor 110 may determine a projection position of the landmark 10 according to a user input for the landmark 10 received through the lateral projection image. For example, the processor 110 provides a message inquiring about the projection location of one or more pre-set landmarks 10 (eg, select a landmark location) to the display 120 together with a lateral projection image, , the display 120 may display the message and the lateral projection image. Subsequently, when a user input (eg, a selection input, a location coordinate value input, etc.) for a specific location on the lateral projection image is received, the processor 110 may determine the projection location of the landmark 10 according to the selected location. there is. Throughout the specification, user input may broadly mean a user's selection input, text input, and the like applied using a mouse, keyboard, joystick, or the like.

In another embodiment, the processor 110 may determine projection positions of the plurality of landmarks 10 with respect to the object by performing landmark tracing on the lateral projection image. In an embodiment, the processor 110 may detect the projection position of each of the plurality of landmarks 10 in the lateral projection image by using a position determination model previously acquired through image-based machine learning. In one embodiment, the processor 110 may receive a position determination model from an external device (eg, a server), input a projection image to the position determination model, and position each of the plurality of landmarks 10 within the projection image. Coordinates can be traced. In one embodiment, the location determination model may be obtained from an external device that performs machine learning based on a Convolutional Neural Network (CNN), a Generative Adversarial Net (GAN), or the like.

In step S230 , the display 120 may display an image of an object in which the projection positions of the plurality of landmarks 10 are displayed on the first window 310 . For example, the display 120 may display the projected position of each landmark 10 as a circular mark on the lateral projection image, and may additionally display a name, coordinates, and the like. In one embodiment, step S230 may be performed after step S270.

The processor 110 may obtain a guide line 20 indicating a positional relationship between the plurality of landmarks 10 . The processor 110 may obtain one or more guide lines 20 by connecting some or all of the plurality of landmarks 10 to each other. Here, the line may include a straight line, a curve, or those obtained by connecting two or more points represented on a two-dimensional (or three-dimensional) image, and may include a boundary of a specific body part (eg, teeth, soft tissue, etc.) It may include lines of a predetermined shape formed to correspond to each other. The processor 110 uses algorithms (eg, Bezier curve, spline interpolation method) capable of defining a curve on 2D (or 3D) using one or more landmarks 10 represented in 2D (or 3D). , polynomial regression, etc.) can be used to determine the positional information of the line.

In one embodiment, the guideline 20 is a first guideline connecting the porion, the lateral pterygoid muscle, and the inferior orbital margin among the plurality of landmarks 10, beige among the plurality of landmarks 10, according to the set criteria. A second guide line connecting the on, lateral pterygoid muscle, and nazion may be included, but is not limited thereto. In one embodiment, the guide line 20 may further include a plurality of third guide lines indicating the shape of the soft tissue of the object. In one embodiment, the guide line 20 may include a straight line, a curved line, or a line having a shape including these obtained through a combination of at least some of the plurality of landmarks 10 .

The display 120 may display on the first window 310 an image of an object in which the projection positions of the plurality of landmarks 10 and the guide line 20 are displayed together. A plurality of measurement values for a plurality of analysis items may be determined based on the projection positions of the dog landmarks 10 . In one embodiment, the processor 110 may determine a plurality of measurement values for a plurality of analysis items based on the projection positions of the plurality of landmarks 10 and the guide line 20 . Here, the analysis item represents a target item (eg, facial convexity, facial prominence meaning a degree of convexity) requiring analysis according to a set analysis method. For example, the analysis item is an item specifying the degree to which the difference in distance between landmarks 10 differs from the reference value, the degree to which the vertical distance difference or slope between the landmark 10 and the guide line 20 differs from each reference value, and the like. can include In addition, the measurement value represents a value (eg, 10.52) measured at the projection position of the corresponding landmark 10 with respect to the analysis item.

Here, a plurality of analysis items may be provided by a plurality of analysis methods. A plurality of analysis methods may be pre-stored in the device 100, or may be prepared in a method received from another device (eg, server) prior to step S240. Each of the plurality of analysis methods represents an analysis technique for performing an analysis on orthodontic diagnosis based on a 2D or 3D image. In one embodiment, the plurality of analysis methods may include a Ricketts analysis method, a Steiner analysis method, a Downs analysis method, an Integra by CJH analysis method, and the like. In one embodiment, each of the plurality of analysis methods may include a plurality of analysis items defined according to the type of image and information about a measurement method for each analysis item.

In step S250, the display 120 may display a plurality of measured values in the second window 320. For example, the processor 110 provides information such as names of a plurality of analysis methods, names of a plurality of analysis items, and measured values for each analysis item to the display 120, and the display 120 displays the provided information. It can be displayed on a second window 320 distinct from the first window 310 . In one embodiment, step S250 may be performed after step S270.

The processor 110 may obtain a user input for selecting one of a plurality of analysis methods, and the display 120 may display a plurality of measurement values for a plurality of analysis items provided by an analysis method corresponding to the user input. there is. For example, the display 120 may display an analysis method selection menu 321 on an upper area of the first window 310 as an interface for selecting an analysis method. When a user input for selecting one of a plurality of analysis methods is received through the analysis method selection menu 321, the processor 110 may determine an analysis method corresponding to the user input. If the analysis method selected by the user is 'Integra by CJH', the processor 110 determines the anterior-posterior position of the lower jaw based on the saddle angle (eg, normal value), which is a plurality of analysis items provided by 'Integra by CJH' A plurality of measurement values for a plurality of analysis items can be calculated according to the measurement method defined in 'Integra by CJH' for Bjork Sum, Articular angle, etc.

The processor 110 may provide statistical information on a plurality of analysis items to the second window 320 along with a plurality of measurement values. In one embodiment, the statistical information on the analysis item may include at least one of a mean, a standard deviation, and a median of pre-collected samples for each analysis item, In addition, various statistical representative values such as variance, mode, and percentile for the sample may be included. Statistical information on the analysis item may be pre-stored in the device 100, or may be prepared in a manner received from another device (eg, server) prior to step S250.

In one embodiment, the processor 110 determines a difference representing the degree to which the measurement value of each analysis item deviate from the average based on the average of each analysis item, and determines the difference together with a plurality of measurement values in a second window 320 may be provided. For example, as shown in FIG. 3, the processor 110 includes the name of the analysis method (eg Integra by CJH), the name of the analysis item (eg Facial Convexity), the average for the corresponding sample (eg 3.60), An analysis result including a standard deviation (eg, 4.60), a measured value (eg, -6.92), and a deviation (eg, 10.52) may be provided to the second window 320 (see identification number 322).

The display 120 may display on the second window 320 a first graph 30 including a plurality of deviations indicating degrees of deviation of a plurality of measured values from the average. Here, the first graph 30 means a graph that visually shows how much deviation the measurement value has for each analysis item within a standard deviation range. In an embodiment, the display 120 may display a first graph 30 indicating a degree of deviation of a plurality of measurement values from an average in the graph area 323 of the second window 320 .

Specifically, in the graph area 323, the x-axis represents the value of each analysis item, and the y-axis represents each analysis item. In addition, the x-axes of each analysis item are arranged on the y-axis so that the average value of each analysis item is located. Each x-axis can be scaled to indicate a specified range of observations or standard deviations for each analysis item. The processor 110 may obtain the first graph 30 by displaying the deviation of the measured value for each analysis item on each x-axis and connecting the respective deviations.

In this way, as the average value of each analysis item is scaled to be located at the center of the x-axis, the user can intuitively understand that the greater the degree of deviation of the first graph 30 from the center of the x-axis, the greater the degree of deviation of the corresponding measurement value from the average. You can check.

The display 120 may overlap and display the second graph 40 representing the standard deviation corresponding to each of the plurality of analysis items on the first graph 30. For example, the processor 110 may display each analysis item. Two points corresponding to a standard deviation of 1σ for can be displayed on each x-axis. Subsequently, the processor 110 calculates a 2-1 graph connecting standard deviation 1σ points located on one side (eg, left half) of the y-axis bisector and a standard deviation 1σ point located on the other side (eg, right half) of the y-axis. It is possible to obtain a second graph 40 including the 2-2 graph connecting them. Also, the display 120 may overlap the 2-1 graph and the 2-2 graph on the first graph 30 and display them.

In this way, as the first graph 30 and the second graph 40 are overlapped and provided, the user can determine whether the measured value of each analysis item is statistically within the standard deviation range, and if it is out of the standard deviation range, what the deviation is. You can intuitively check whether or not the level is high.

The processor 110 may scale the second graph 40 to be a straight line. For example, by adjusting the value range of the x-axis for each analysis item so that each of the 2-1 and 2-2 graphs becomes a vertical line passing through a specific x-axis coordinate, the second graph 40 and the first graph (30) can be updated. For example, the 2-1 graph passes through the x-axis coordinate of the first point in the graph area 323, and for each analysis item, each analysis item is a first vertical line passing through a point on the left half of the y-axis. The observed value range visualized in the graph area 323 may be adjusted for . In addition, the 2-2 graph passes through the x-axis coordinate of the second point in the graph area 323, and for each analysis item, each analysis item is a second vertical line passing through a point on the right half of the y-axis. The observed value range visualized in the graph area 323 may be adjusted for . In this way, as the range of observation values visualized in the graph area 323 is scaled so that the standard deviation range becomes a vertical line on the left half and right half of the y-axis, respectively, the user can determine whether the measured value is statistically acceptable for all analysis items. You can intuitively see how much of a difference there is.

In step S260, the processor 110 may determine the possibility of anomaly with respect to a plurality of measurement values based on the statistical information on the analysis item. In one embodiment, the processor 110 may determine the possibility of abnormality for a plurality of measurement values based on the mean and/or standard deviation of the analysis item. For example, the processor 110 may calculate a deviation by comparing the measured value for each analysis item with an average, and calculate the possibility of abnormality as a numerical value in proportion to the calculated deviation. For another example, the processor 110 may determine whether or not the calculated deviation is abnormal according to whether or not the calculated deviation is out of a standard deviation range for each analysis item.

In step S270, the processor 110 may determine a problem prediction measurement value representing some measurement values expected to have a problem among a plurality of measurement values based on the possibility of an abnormality. Here, determining the expected problem item means deriving a value out of the normal range through analysis of the measured value. For example, when the probability of abnormality determined for the measurement value of the analysis item Facial Convexity is greater than the reference value, the measurement value of the analysis item Facial Convexity may be included in the problem prediction measurement value.

In an embodiment, the processor 110 may determine a problem prediction measurement value according to whether the probability of abnormality for each analysis item is greater than or equal to a reference value. In another embodiment, the processor 110 may determine a problem prediction measurement value based on the degree of possibility of an abnormality, the directionality of the difference (eg, positive (+) difference, negative (-) difference), and the like.

The processor 110 may determine a problem estimation item corresponding to the problem estimation measurement value. For example, the problem prediction item Convex Profile, which has a correspondence relationship with the analysis item Facial Convexity determined as the problem prediction measurement value, can be detected. Details regarding this will be further described with reference to FIG. 3 .

4 is a diagram illustrating problem prediction items according to an embodiment.

Referring to FIG. 4 , each problem prediction item corresponds to one or more analysis items, and each analysis item may correspond to one or more different problem prediction items. Accordingly, when a problem prediction measurement value that is expected to have a problem is determined, a problem prediction item corresponding to an analysis item of the problem prediction measurement value may be detected together. In one embodiment, the expected problem items include Convex Profile representing a protruding face, Concave Facial representing a depressed face (eg, protruding jaw), Protrusive Mx representing protruding occlusion, and Pretrusive Mx representing centrifugal occlusion. It may include, but is not limited thereto, and may include various medical terms used in the treatment process.

In one embodiment, different analysis methods and analysis items may be applied depending on the type of image (eg, lateral projection image, PA image, model image) and target part (eg, face, skeleton, dental), and accordingly, different problems Expected items can be determined. For example, the processor 110 calculates a measurement value for Facial Convexity, an analysis item classified as a facial profile category according to the Integra by CJH analysis method, and compares the measurement value with a statistical value (eg, male 6.6 or higher, female 8.2 or higher). Thus, the possibility of an anomaly can be calculated. If the problem prediction measurement value is determined based on the probability of abnormality, the processor 110 may detect the problem prediction item Convex Profile corresponding to the analysis item Facial Convexity.

In step S280 , the display 120 may display a problem prediction measurement value or a problem prediction item corresponding to the problem prediction measurement value on the third window 330 . In one embodiment, the display 120 displays the name of the problem expected item (eg, Convex Profile), the name of the corresponding analysis item (eg, Facial Convexity), and the possibility of anomaly (eg, deviation, 10.52) in a second window 320. It can be displayed on the third window 330, which is an area distinct from (see identification number 331). For example, the display 120 may first display the name of the problem prediction item, and then display the analysis method along with parentheses. In the case of “Convex Profile (Facial Convexity: -6.92**)” shown in identification number 331, “Convexity: -6.96** means that the analysis item called Facial Convexity was measured at 10.52, and the Convex Profile is based on such a measurement value. This means that it is expected that there will be a problem with the protruding face shape when following. As such, having these measurements does not always result in a problem called the Convex Profile, but it can provide summary information on potential problem items that are highly relevant and recommended for users to check.

The display 120 may simultaneously display the first window 310, the second window 320, and the third window 330 in areas separated from each other. For example, as shown in FIG. 2, as steps S230, S250, and S280 are performed after step S270, the display 120 displays the projection positions of the plurality of landmarks 10 on the first window 310. A real projection image, a plurality of measurement values for a plurality of analysis items in the second window 320 and one or more problem prediction items determined from a plurality of measurement values in the third window 330 may be simultaneously displayed.

In the second window 320, the display 120 displays the color, size, display method, etc. of the name of the analysis item (eg, facial convexity), mean, standard deviation, measured value, deviation, etc. corresponding to the expected measurement value of the problem. It can be displayed differently from the measured values. In addition, the processor 110 may display different colors according to a range to which a deviation belongs to each of the measurement values expected to have problems. For example, when the processor 110 is analyzed to have a problem beyond the average value according to a corresponding analysis method (eg, Integra by CJH) for problem expected measured values, if the possibility of abnormality according to the deviation is greater than the reference value, red color is displayed. If it is less than the standard value, it can be displayed in orange.

In this way, the processor 110 derives a numerical value out of the normal range through analysis of the measured value and provides it as a problem prediction item, thereby providing a user-intuitive interface about which part and in what aspect the problem item is related. can provide.

In an embodiment, the processor 110 may group a plurality of expected problem items based on the classification category and the degree of possibility of abnormalities, and the display 120 may display the problem expected items in different colors according to the grouping. For example, as shown in FIG. 3, the processor 110 classifies problem prediction items into three groups according to the degree to which the problem prediction measurement value is large, and the display 120 displays a color (eg, red, yellow) corresponding to each group. , blue), information on problem prediction items of each group can be displayed on the third window 330 . For example, a first group in which the problem prediction measurement value is less than the first value and a slight problem may be displayed in orange color, and a third group in which the problem prediction value is more serious than the second value may be displayed in red color. Also, the display 120 may display information on an analysis item corresponding to a problem prediction measurement value among a plurality of analysis items displayed on the second window 320 in a color corresponding to a group of the corresponding problem prediction item. In addition, the display 120 may display the rest of the analysis items except for the problem prediction measurement value among the plurality of analysis items displayed on the second window 320 in a basic color (eg, black).

In an embodiment, the display 120 may display a plurality of measurement values on an image of an object. For example, the display 120 may overlap and display each measurement value in the same color as the color displayed on the second window 320 on the lateral projection image displayed on the first window 310 .

5 is a diagram in which the device 100 determines projection positions of a plurality of landmarks 10 in a PA projection image of an object and provides analysis results for a plurality of analysis items based on the determined projection positions. It is a drawing for explaining the operation.

5 may be understood with reference to all embodiments in which the device 100 disclosed in FIGS. 1 to 4 operates. Similar to the above-described embodiments, upon receiving a PA projection image-based analysis request, the display 120 displays the PA projection image of the object in the first window 310, and the processor 110 displays the PA projection image in the PA projection image. It is possible to determine the projection position of a plurality of landmarks (10). In addition, the processor 110 obtains a user input for selecting one of a plurality of analysis methods through the analysis method selection menu 321, and obtains a user input for selecting one of a plurality of analysis methods (eg, H ANALYSIS) corresponding to the user input. A plurality of measurement values for analysis items are provided to the display 120, and the display 120 may display the provided measurement values in the second window 320. In addition, the processor 110 may perform A problem prediction item is determined based on the possibility of abnormality, and the display 120 may display the problem estimation item in the third window 330 . Similarly, the processor 110 obtains a first graph 30 indicating the degree of deviation of a plurality of measured values from the average and a second graph 40 indicating a standard deviation corresponding to each of the plurality of measured values, and displaying 120 ) may display the first graph 30 and the second graph 40 in the graph area 323 .

6 is a device 100 according to an embodiment determines the projection positions of a plurality of landmarks 10 in a model image of an object and provides analysis results for a plurality of analysis items based on the determined projection positions. It is a drawing for explaining the operation.

6 may be understood with reference to all embodiments in which the device 100 disclosed in FIGS. 1 to 5 operates. Similar to the above-described embodiments, upon receiving a model image-based analysis request, the display 120 displays the upper jaw model image and the lower jaw model image of the object on the first window 310, and the processor 110 determines the upper jaw model image and the lower jaw model image. Positions of a plurality of landmarks 10 may be determined in the model image and the lower jaw model image. In addition, the processor 110 may provide a plurality of measurement values for a plurality of analysis items to the display 120, and the display 120 may display the provided measurement values in the second window 320. In addition, the processor ( 110 ) determines a problem prediction item based on the possibility of abnormality for a plurality of measurement values, and the display 120 may display the problem prediction item in the third window 330 . Similarly, the processor 110 obtains the first graph 30 and the second graph 40, and the display 120 displays the first graph 30 and the second graph 40 in the graph area 323. can do.

FIG. 7 is a diagram for explaining an operation in which the device 100 provides a first-view image 50 and a second-view image 60 of an object, according to an exemplary embodiment.

Referring to FIG. 7 , the processor 110 may obtain a first view image 50 and a second view image 60 of the object in the first window 310 .

In an embodiment, the image 50 of the first viewpoint is a line image obtained using the first lateral projection image among the plurality of lateral projection images acquired of the object, and the image 60 of the second viewpoint ) may be a line image obtained using the laterally obtained lateral projection image. The processor 110 determines projection positions of the landmarks 11 of the first viewpoint by using the lateral projection image of the first viewpoint obtained with respect to the object, and connects the landmarks 11 of the first viewpoint to each other. An image 50 of a first viewpoint including a plurality of first lines may be acquired. In addition, the processor 110 determines projection positions of the landmarks 12 of the second viewpoint by using the lateral projection image of the second viewpoint obtained with respect to the object, and connects the landmarks 12 of the second viewpoint to each other. An image 60 of a second viewpoint including a plurality of connected second lines may be acquired.

In another embodiment, the image 50 of the first view is a line image of the current view obtained using a projection image acquired last among a plurality of lateral projection images acquired of the object, and an image of the second view ( 60) may be a line image of a future view predicted through analysis of the image 50 of the first view. The processor 110 determines projection positions of the landmarks 11 of the first viewpoint by using the lateral projection image of the first viewpoint obtained with respect to the object, and connects the landmarks 11 of the first viewpoint to each other. An image 50 of a first viewpoint including a plurality of first lines may be acquired. Also, the processor 110 may obtain an image 60 of a second viewpoint including a plurality of second lines obtained by updating a plurality of first lines according to a plurality of criteria.

The processor 110 obtains an overlapping image by overlapping the image 50 of the first view and the image 60 of the second view of the object on the first window 310, and the display 120 displays the obtained overlapping image. can display. According to an embodiment, the processor 110 obtains an overlapped image by overlapping the image 50 of the first view and the image 60 of the second view in response to a request for analysis based on overlapping images, and displays the 120 ) may display overlapping images in the first window 310 . In an embodiment, the display 120 may display the image 50 of the first view and the image 60 of the second view in different colors.

The processor 110 obtains one or more overlapping line images by overlapping some of the plurality of first lines with some of the plurality of second lines, and the display 120 displays the obtained line overlapping image in the second window 320. can be displayed. In an embodiment, the processor 110 obtains a first line overlapping image in which a line connecting the tip of the nose and the tip of the chin of the first view and a line connecting the tip of the nose and the chin of the second view are overlapped, and displays the image. 120 may display the obtained first line overlapping image on a partial area of the second window 320 . In one embodiment, the processor 110 obtains a second overlapping line image in which a line connecting the maxilla bones of the first viewpoint and a line connecting the maxilla bones of the second viewpoint are overlapped, and the display 120 displays the desired first image. A two-line superimposed image may be displayed on a partial area of the second window 320 . In an embodiment, the processor 110 may generate a third line superposition image in which a line connecting the mandibular anterior teeth and the mandibular first molars at the first time point and a line connecting the mandibular anterior teeth and the mandibular first molar teeth at the second time point overlap. acquired, and the display 120 may display the obtained third overlapping line image on a partial area of the second window 320 . In an embodiment, the processor 110 obtains a fourth line overlapping image in which a line connecting the mandible of the first viewpoint and a line connecting the mandible of the second viewpoint overlap, and the display 120 displays the obtained fourth line overlapping image. A line overlapping image may be displayed on a partial area of the second window 320 . In an embodiment, the processor 110 may generate a fifth line overlapping image in which a line connecting the maxillary anterior teeth and the maxillary first molars at the first view point and a line connecting the maxillary anterior teeth and the maxillary first molar teeth at the second view overlap. acquired, and the display 120 may display the obtained fifth overlapping line image on a partial area of the second window 320 . In an embodiment, the processor 110 obtains a sixth line overlap image obtained by overlapping the first to fifth line overlap images, and the display 120 displays the obtained sixth line overlap image in a second window ( 320) can be displayed in some areas.

The processor 110 obtains measurement values of the first time point for a plurality of analysis items based on the projected positions of the landmarks 11 at the first time point, and based on the possibility of anomaly with respect to the measurement values at the first time point, the processor 110 obtains a first time measurement value. It is possible to determine the expected problem items at 1 point in time. In addition, the processor 110 obtains measurement values of the second viewpoint for a plurality of analysis items based on the projected positions of the landmarks 12 of the second viewpoint, and based on the possibility of abnormalities in the measurement values of the second viewpoint. Thus, it is possible to determine the expected problem items at the second point of view.

The processor 110 provides the measurement values of the first time and the measurement values of the second time of the problem prediction item to the display 120, and the display 120 displays the provided measurement values together in the third window 330. can do. In an embodiment, the display 120 may display information on the measurement value at the first time point, the measurement value at the second time point, and the analysis item together on the third window 330 with respect to the problem prediction item at the first time point. there is. For example, as shown in identification number 332, the processor 110 measures the measured value of the problem expected item 'Normal Lower Lip' and the corresponding analysis item 'Lower Lip EL' at the first time point, which was 1.8 at the first time point. may indicate that it changed to 1.42 at the second point in time.

In this way, as simplified line images are overlapped and provided, the user can more easily visually check line changes at different viewpoints. In addition, as the information on the difference between the first and second views is provided in a separate window, the user can intuitively check the numerical difference between the different views.

The processor 110 may also provide the third window 330 with information on whether a change in the measured value for the problem prediction item is desirable. In one embodiment, the processor 110 may provide information on whether an increase or decrease in a change from a measurement value at a first time point to a measurement value at a second time point is in a direction closer to an average for a corresponding analysis item or is within a standard deviation. It is provided to the display 120 along with the measurement value, and the display 120 may display the provided information. In one embodiment, the display 120 displays the expected problem item in a first color (eg, blue) when the change increase or decrease is in a direction closer to the average for the corresponding analysis item, and when the change is in a direction away from the average, The expected problem item may be displayed in a second color (eg, red).

In this way, the processor 110 may indicate a difference in line changes at different times and also provide information on whether such changes are desirable.

In one embodiment, the processor 110 may perform a series of operations for displaying analysis results according to the analysis method, and may be electrically connected to the display 120 and other components to control data flow between them. can To this end, the processor 110 may be implemented as a central processor unit (CPU) that controls overall operations of the device 100 . Also, the display 120 may display various pieces of information described throughout the specification under the control of the processor 110 . The display 120 may comprehensively mean an image output device that displays an image, and for example, a liquid crystal display, a thin film transistor-liquid crystal display, an organic light emitting diode (OLED) It may be an organic light-emitting diode, a flexible display, a 3D display, an electrophoretic display, and the like.

In addition, those of ordinary skill in the art may understand that other general-purpose components may be further included in the device 100 in addition to the components shown in FIG. 1 . According to an embodiment, the device 100 further includes a communication unit for communicating with other devices through a wired/wireless network, a user interface for receiving a user input, and a storage unit (eg, memory, database, cloud) for storing data. can include According to another embodiment, some of the components shown in FIG. 1 may be omitted.

8 is a flowchart illustrating a method of displaying, by the device 100, an analysis result according to an analysis method according to an exemplary embodiment.

In step S810, the processor 110 may determine the locations of the plurality of landmarks 10 relative to the object. In an embodiment, the processor 110 obtains an image including at least one of a lateral projection image of the object, a PA projection image, and a model image, and according to a user input for the lateral projection image, a plurality of landmarks ( 10) can determine the projection position.

In step S820, the processor 110 may determine a plurality of measurement values for each of a plurality of analysis items provided by a plurality of analysis methods based on the locations of the plurality of landmarks 10. In an embodiment, the processor 110 obtains a user input for selecting one of a plurality of analysis methods, and the display 120 performs a plurality of measurements on a plurality of analysis items provided by an analysis method corresponding to the user input. value can be displayed.

In step S830, the processor 110 may determine the possibility of anomaly in a plurality of measurement values based on statistical information on a plurality of analysis items. In one embodiment, the likelihood of an anomaly may be determined based on the average and/or standard deviation for the analyte.

In step S840, the processor 110 may determine problem expected measurement values representing some measurement values expected to have a problem among a plurality of measurement values based on the possibility of an abnormality. In an embodiment, the processor 110 may determine a measurement value of one or more analysis items having a greater probability of abnormality than a reference value as a problem prediction measurement value.

In step S850, the display 120 may display a problem prediction measurement value or a problem prediction item corresponding to the problem prediction measurement value. In one embodiment, the display 120 displays an image of the object in which the projection positions of the plurality of landmarks 10 are displayed in the first window 310 and displays a plurality of measurement values in the second window 320. A problem prediction measurement value or a problem prediction item corresponding to the problem prediction measurement value may be displayed in the third window 330 . In one embodiment, the first window 310, the second window 320, and the third window 330 may be simultaneously displayed in areas separated from each other.

According to an embodiment of the present disclosure, the device 100 provides a problem prediction measurement value or a problem prediction item that is out of the normal range through analysis of the measurement value, so that the problem item is related to which part and in what aspect. A user-intuitive interface can be provided for

The order and combination of the steps shown above is an embodiment, and the order, combination, branch, function, and subject of execution thereof may be added, omitted, or modified within the scope that does not deviate from the essential characteristics of each component described in the specification. It can be seen that this can be done. In addition, throughout the specification, 'providing' includes a process in which an object acquires specific information or directly or indirectly transmits/receives it to a specific object, and can be interpreted as comprehensively including the performance of related operations required in this process.

Various embodiments of the present invention are implemented as software comprising one or more instructions stored in a storage medium (eg, memory) readable by a machine (eg, a display device or a computer). It can be. For example, a processor (eg, processor 110 ) of the device may call at least one of one or more instructions stored from a storage medium and execute it. This enables the device to be operated to perform at least one function according to the called at least one instruction. The one or more instructions may include code generated by a compiler or code executable by an interpreter. The device-readable storage medium may be provided in the form of a non-transitory storage medium. Here, 'non-temporary' only means that the storage medium is a tangible device and does not contain signals (e.g., electromagnetic waves), and this term refers to the case where data is stored semi-permanently in the storage medium. It does not discriminate when it is temporarily stored.

According to one embodiment, the method according to various embodiments disclosed in the present invention may be included and provided in a computer program product. Computer program products may be traded between sellers and buyers as commodities. A computer program product is distributed in the form of a device-readable storage medium (e.g. compact disc read only memory (CD-ROM)), or through an application store (e.g. Play Store™) or on two user devices (e.g. It can be distributed (eg downloaded or uploaded) online, directly between smartphones. In the case of online distribution, at least part of the computer program product may be temporarily stored or temporarily created in a device-readable storage medium such as a manufacturer's server, an application store server, or a relay server's memory.

Those skilled in the art related to this embodiment will be able to understand that it can be implemented in a modified form within a range that does not deviate from the essential characteristics of the above description. Therefore, the disclosed methods are to be considered in an illustrative rather than a limiting sense. The scope of the present invention is shown in the claims rather than the foregoing description, and all differences within the equivalent scope will be construed as being included in the present invention.

100: device
110: processor 120: display
10: Multiple landmarks 20: Guidelines
30: first graph 40: second graph
50: image of the first viewpoint 60: image of the second viewpoint
310: first window 320: second window
330: third window

Claims (14)

In the method of displaying the analysis result according to the analysis method,
determining locations of a plurality of landmarks with respect to an object;
determining a plurality of measurement values for each of a plurality of analysis items provided by a plurality of analysis methods, based on locations of the plurality of landmarks;
determining an abnormality possibility for the plurality of measured values based on statistical information on the plurality of analysis items;
determining problem expected measurement values indicating some measurement values expected to have a problem among the plurality of measurement values based on the possibility of an abnormality; and
and displaying the problem prediction measurement value or a problem prediction item corresponding to the problem prediction measurement value.
According to claim 1,
obtaining a user input for selecting one of the plurality of analysis methods; and
The method further comprising displaying a plurality of measurement values for a plurality of analysis items provided by an analysis method corresponding to the user input.
According to claim 1,
The method of claim 1, wherein the probability of anomaly is determined based on a mean and/or standard deviation for the assay term.
According to claim 1,
The step of displaying the problem prediction measurement value or a problem prediction item corresponding to the problem prediction measurement value
A method of displaying a problem prediction item corresponding to the problem prediction measurement value in a separate window distinct from a window in which the measurement value is displayed.
According to claim 1,
displaying an image of the object in which the locations of the plurality of landmarks are displayed in a first window; and
Further comprising; displaying the plurality of measurement values in a second window,
A third window, the first window and the second window displaying the problem prediction measurement value or the problem prediction item corresponding to the problem prediction measurement value are simultaneously displayed in areas separated from each other.
According to claim 5,
The first window overlaps and displays an image of a first view and an image of a second view of the object,
The third window displays the measurement value of the first time point and the second time point measurement value for the problem prediction item together.
According to claim 1,
Further comprising; displaying the plurality of measurement values,
The step of displaying the plurality of measured values
displaying a degree of deviation of the plurality of measured values from an average as a point on a straight line corresponding to each of the plurality of measured values; and
Displaying a first graph indicating a degree of deviation of the plurality of measured values from the average based on the location of a point corresponding to each of the plurality of measured values;
According to claim 7,
The step of displaying the plurality of measured values
The method further includes displaying a second graph representing a standard deviation corresponding to each of the plurality of analysis items by overlapping the first graph.
In the device for displaying the analysis result according to the analysis method,
Determining the location of a plurality of landmarks with respect to the object,
Determine a plurality of measurement values for each of a plurality of analysis items provided by a plurality of analysis methods based on the locations of the plurality of landmarks;
Determining a possibility of abnormality for the plurality of measured values based on statistical information on the plurality of analysis items;
a processor that determines problem expected measurement values indicating some measurement values expected to have a problem among the plurality of measurement values based on the possibility of an abnormality; and
A device comprising a; display for displaying the problem prediction measurement value or a problem prediction item corresponding to the problem prediction measurement value.
According to claim 9,
The processor
Obtaining a user input for selecting one of the plurality of analysis methods;
the display
A device that displays a plurality of measurement values for a plurality of analysis items provided by an analysis method corresponding to the user input.
According to claim 9,
The processor
The device, wherein the probability of abnormality is determined based on the average and / or standard deviation for the analysis item.
According to claim 9,
the display
A device for displaying a problem prediction item corresponding to the problem prediction measurement value in a separate window distinct from a window in which the measurement value is displayed.
According to claim 9,
the display
Displaying an image of the object in which the locations of the plurality of landmarks are displayed in a first window;
displaying the plurality of measured values in a second window;
A third window in which the problem prediction measurement value or the problem prediction item corresponding to the problem prediction measurement value is displayed, and the first window and the second window are simultaneously displayed in areas separated from each other.
A computer-readable recording medium recording a program for executing the method of any one of claims 1 to 8 in a computer.

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