Method for producing a reprojection panoramic view aligned with the course of the mandibular canal

Description

TECHNICAL FIELD OF THE INVENTION

[0001] The present invention relates to a method for generating a reprojection panoramic view (RPA) from a dental CBCT volume of a patient. BACKGROUND OF THE INVENTION

[0002] The mandibular canal is an important anatomical structure on each side of the lower jaw. Among other things, it encloses the mandibular nerve, damage to which can lead to paralysis of one side of the face, for example. It therefore plays a key role in dental diagnostics and especially in the planning of surgical procedures in the lower jaw region. The mandibular canal is patient-specific and can vary greatly in shape and course. Its shape is roughly tubular, although its cross-section can exhibit considerable fluctuations in shape and size along its course. Its course can also vary considerably: It can be straight in places, but also locally very curved.

[0003] A CBCT is ideally used to assess the anatomy of the mandibular canal, as it allows for a geometrically accurate representation of the anatomical structures in three dimensions. The physician uses the CBCT to track the course of the mandibular canal and, for example, to assess its distance from other anatomical structures or potential implant positions. This allows the physician to plan procedures, such as wisdom tooth extraction or implant placement, precisely and reliably.

[0004] The difficulty in efficiently assessing the mandibular canal is its curved course, which is often oblique to the orthogonal slices of the multiplanar reformation (MPR) of standard radiology viewing programs. Accurately tracking the mandibular canal and assessing it in all three spatial dimensions is therefore often associated with increased navigation effort.

[0005] A state-of-the-art solution to this problem is the use of so-called tilted MPR views or "custom sections": In this case, a planar section is placed through the volume so that it runs as tangentially as possible to the mandibular canal, thus imaging a large part of the mandibular canal. However, due to the anatomically determined curvature of the mandibular canal, this is often not possible. Furthermore, the curvature means that the mandibular canal is only actually sectioned centrally in the center of the view, for example, while it runs out of the slice at the edges of the view and is therefore no longer optimally displayed. Furthermore, manually setting the correct slice view involves navigation and is time-consuming, and requires a certain amount of practice.

[0006] Reference is also made to the following documents: DE102010040096A1 discloses a method for creating an image from a 3D volume.

[0007] US2013022252A1 discloses the generation of panoramic images from CBCT dental images.

[0008] US2020175681A1 discloses a system and method for creating element of interest (EoI) focused panoramas of an oral complex.

[0009] Hingst V. et al, "Dental X-ray diagnostics with panoramic tomography - technique and typical image findings", RADIOLOGE, DER, SPRINGER, DE, vol. 60, no. 1, doi:10.1007 / S00117-019-00620-1, ISSN 0033-832X, (2020), pages 77 - 92, (20200109), XP036989877. DISCLOSURE OF THE INVENTION

[0010] The inventors are currently not aware of any technology that automatically generates a patient-specific view aligned to the mandibular canal, allowing the physician to efficiently assess the mandibular canal anatomy.

[0011] The aim of the present invention is a method for automatically generating a reprojection panoramic view from a dental DVT volume of a patient, which is aligned with the course of the left and right mandibular canals (hereinafter referred to jointly as mandibular canal).

[0012] This object is achieved by the method according to claim 1. The subject matters of the dependent claims relate to preferred embodiments or further developments.

[0013] The computer-assisted method according to the invention serves to automatically generate a reprojection panoramic view from a patient's dental DVT volume, which is aligned with the course of the mandibular canal. The method comprises the following steps: Localization of the mandibular canal, which occurs automatically or manually; Automatic definition of a projection area of ​​the RPA, which comprises the following substeps: Automatic determination of a guide curve in a plane perpendicular to the patient's longitudinal axis based on the localized mandibular canal; Automatic definition of a variable or constant thickness profile along the guide curve; Extrusion of the area defined by the guide curve and thickness profile along the patient's longitudinal axis; and Creation of the RPA by reprojecting the DVT volume in the defined projection area.

[0014] A beneficial effect of the invention is that it enables automatic alignment of the guide curve, which is optimized for applications involving the mandibular canal. This eliminates the need for the physician to adjust the guide curve themselves or work with a suboptimally aligned curve. This saves time and also improves quality.

[0015] The guide curve is determined in such a way that, on the one hand, it is aligned with the mandibular canal (for example, by minimizing a distance measurement) and, on the other hand, preferably preserves the aesthetics of the resulting RPA (particularly by avoiding local distortions and strong global asymmetries). The guide curve can be represented using, for example, interpolated curves with freely selectable support points, implicitly defined curves, or one of many predefined curve shapes (templates), which are then adapted through geometric transformations. Additional dental structures can be used to support the determination of the guide curve. Furthermore, the guide curve can be selected such that it does not follow the sharp bend of the mandibular canal at the mental foramen, but continues towards the anterior region. The thickness profile of the projection area can be selected in various ways: e.g.Proportional to the diameter and thickness of the mandibular canal, constant, or negligible. In the latter case, the RPA corresponds to a curved sectional view that intersects the mandibular canal approximately midway. Prior knowledge can optionally be used to locate the mandibular canal; a trained machine learning algorithm or conventional image processing methods can be used, or the mandibular canal can be drawn by the user. The RPA guidance curve can be used as a starting point for subsequent navigation through the CBCT volume, ensuring easy navigation along the mandibular canal in all 3D sectional views.The result of the mandibular canal localization can optionally be graphically displayed on the resulting RPA. Furthermore, those areas of the mandibular canal that are outside the projection area can be specifically marked on the RPA (this is done by back-projecting these areas onto the RPA). If a machine learning method is used to localize the mandibular canal, it can be trained, for example, using data pairs consisting of CBCT volumes and associated segmentation maps representing the mandibular canal, probability distributions, heat maps, center lines, point clouds, triangular grids, and bounding boxes. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In the following description, the present invention is explained in more detail using exemplary embodiments and with reference to the drawings, wherein Fig.1a - shows a typical state-of-the-art reprojection panoramic view, which is generated from the projection area consisting of the guide curve and thickness profile in Fig. 1b Fig.1b - shows the guide curve from which the projection area for generating the reprojection panoramic view in Fig. 1a derived, in a sectional plane perpendicular to the patient's longitudinal axis according to the state of the art; Fig. 2 - shows a projection area determined by linear extrusion of a guide curve according to the state of the art; Fig. 3 - shows a reprojection panoramic view of the same DVT volume optimized for the mandibular canal as in Fig. 1a, which was generated according to the present invention; Fig. 4 shows a projection of the maximum intensities as well as a segmentation of the mandibular canal (white) on a section plane of the DVT volume perpendicular to the patient's longitudinal axis, whereby the black line indicates a guide curve according to the invention aligned with the mandibular canal, which is used to generate an RPA optimized for the mandibular canal. Fig. 5 - shows an RPA according to the invention optimized for the mandibular canal (a), which serves as the starting point for navigation through the volume; views (bd) show the section planes tangential and perpendicular to the guide curve, which run through the mandibular canal due to the optimized placement of the guide curve and thus enable navigation along it. Fig.Fig. 6 shows an RPA according to the invention optimized for the mandibular canal, on which the center line of the localized mandibular canal is drawn as a white line, whereby the dashed part, in contrast to the solid part, indicates that the mandibular canal is located outside the projection area; Fig. 7 shows a schematic representation of an extraoral X-ray system according to one embodiment.

[0017] The reference numbers shown in the drawings indicate the elements listed below, which will be referred to in the following description of the exemplary embodiments. 1.Reprojection panoramic view (RPA) 2.Mandibular canal 3.Projection area 4, 4'guiding curve, curve 5.Patient's long axis 6.Control points 7.Strong curvature of the mandibular canal at the mental foramen 8.DVT system 9.X-ray machine 10.X-ray tube 11.X-ray detector 12.Control unit 13.Head fixation 14.Bite block 15.Calculator 16.Display

[0018] D: Thickness of the projection area (3) in a section plane perpendicular to the patient’s longitudinal axis (5).

[0019] The method according to the invention is a computer-implementable method and can be carried out on a computer-assisted DVT system (8), as in an embodiment in Fig. 7shown, can be carried out. For this purpose, the present invention also comprises a computer program with computer-readable code. The computer program can be provided on a storage medium. The computer-assisted DVT system (8) comprises an X-ray device (9) for carrying out the patient imaging, wherein the 3D X-ray images or the sinogram are generated. The X-ray device (2) has an X-ray emitter (10) and X-ray detector (11) which are rotated around the patient's head during the imaging. The trajectory of the X-ray emitter (10) and the X-ray detector (11) during the imaging can describe a circular path. Alternatively, it can take on a different shape. If several actuators are controlled simultaneously, a device trajectory around the patient's head which deviates from a purely circular path can be achieved. The patient's head is positioned in the X-ray device (9) using the bite block (14) and the head fixation (13).The computer-assisted DVT system (8) comprises an operating unit (12), preferably a computer (15) or a processing unit that can be connected to the X-ray device (9), and preferably a display (16), among other functions for visualizing the data sets. The computer (15) can be connected to the X-ray device (9) via a local network (not shown) or alternatively via the Internet. The computer (15) can be part of a cloud. Alternatively, the computer (15) can be integrated into the X-ray device (9).

[0020] Alternatively, the calculations can take place in the cloud. The computer (15) executes the computer program and delivers the data sets, including for visualization on the display (16). The display (16) can be spatially separated from the X-ray device (9). The computer (15) can preferably also control the X-ray device (9). Alternatively, separate computers (15) can be used for control and reconstruction.

[0021] The method according to the invention serves for the automatic generation of a reprojection panoramic view (RPA) (1) from a dental DVT volume of a patient, which as in Fig. 3 shown, is aligned with the course of the mandibular canal (2). Fig. 1A-B and Fig. 2show comparative examples from the prior art to explain the invention. The method according to the invention comprises the following steps: (S1) localization of the mandibular canal (2); (S2) automatic definition of a projection area (3) of the RPA (1), which comprises the following substeps: (S2.1) automatic setting of a guide curve (4) in a plane perpendicular to the patient's longitudinal axis (5) based on the localized mandibular canal (2); (S2.2) automatic definition of a variable or constant thickness profile along the guide curve (4); (S2.3) extrusion of the area defined by the guide curve (4) and the thickness profile along the patient's longitudinal axis (5); and (S3) creation of the RPA (1) by reprojection of the DVT volume in the defined projection area (3).The representation of the localized mandibular canal (2) in step (S1) can be, for example, a center line, a segmentation mask, a triangular grid as a surface mesh, a point cloud or a heat map indicating a probability distribution.

[0022] In a preferred embodiment, the guide curve (3) is determined in step (S2.1) by means of an optimization with regard to a distance measure between the guide curve (4) and the localized mandibular canal (2) taking into account at least one of the following criteria: Preservation of the aesthetics of the resulting RPA (1), whereby at least one of the following criteria is used as a measure of the aesthetics: Avoidance of local distortions of the RPA (1) to be created in step (S3), reduction of the recording-related asymmetry of the RPA (1) to be created in step (S3); In the case of a guide curve (4) spanned by freely selected control points (6), limitation of the curve complexity, which is determined by the number of control points (6) or degree of a polynomial.

[0023] Preferably, the guide curve (4) to be set has one of the following representations with associated optimization freedoms. Curve (4') defined by freely selectable control points (6) and an interpolation rule, wherein the positions of the control points (6) are the free optimization parameters; Curve (4') selected from a set of predetermined curve shapes and adapted using geometric transformations, wherein both the transformation parameters of the geometric transformations and the selection of the curve (4') from the predetermined set are optimized; Curve (4') parameterized by a function, wherein the function parameters represent the free optimization parameters.

[0024] If the representation of the mandibular canal (2) is a line in three-dimensional space, the preferred procedure is to project this line onto a plane perpendicular to the patient's longitudinal axis. The distance measure to be minimized is the sum of the distances between points on the projected mandibular canal (2) and their nearest points on the guide curve (4). This sum can be weighted, and the distances can be calculated using any distance metric, such as the Euclidean distance. In the case of a representation of the mandibular canal (2) as a three-dimensional heat map, for example, a center line can be derived from the heat map and then the procedure can be followed as described above.Alternatively, the three-dimensional heat map can be projected onto a plane perpendicular to the patient's longitudinal axis and viewed as a potential landscape within which the guide curve (4) is placed such that the total potential along the guide curve (4) is minimized.

[0025] In a further preferred embodiment, in addition to the mandibular canal (2), further dentally relevant structures can be used to optimize the guide curve (4), which include at least one of the following: teeth, incisal point, mandibular foramen, mental foramen, mental tubercle, mental protuberantia, lingual foramen, mental spine, digastric fossa. These additional structures serve as orientation for the course of the guide curve (4) in areas where, due to the anatomy, no mandibular canal (2) is present, such as in particular in the area of ​​the tip of the chin between the mental foramina, from which the middle part of the RPA (1) is derived, as well as in the areas behind the mandibular foramina, from which the outer parts of the RPA (1) are derived. This has the effect that the guide curve (4) can be usefully bridged or continued in these areas (see Fig. 4 ).

[0026] Preferably, the guide curve (4) is selected in such a way that it continues towards the tip of the chin at the point of the sharp curvature of the mandibular canal at the foramen mentale (7) (see Fig. 4 ) and follows the criteria of aesthetics, whereby the detection of this point can be carried out either by taking into account the positions of the above-mentioned foramina mentale or by means of a curvature measure.

[0027] In a further preferred embodiment, the thickness profile in step (S2.2) results from determining a local thickness (D) for each point on the guide curve (4), which is proportionally adapted to the respective local diameter of the mandibular canal (2). The local diameter for a specific point on the guide curve (4) can be determined, for example, based on the cross-section of the mandibular canal with the plane that is perpendicular to the guide curve (4) and runs through the respective point on the guide curve (4). The proportion between thickness and diameter can vary along the guide curve.

[0028] In a further preferred embodiment, a constant thickness profile with such a small thickness (D) is selected that the resulting RPA (1) corresponds to a curved sectional view.

[0029] Preferably, the localization step (S1) comprises at least one of the following sub-steps: (S1.1) Use of prior knowledge; (S1.2) Manual localization by the physician using an input device; (S1.3) Automatic image processing of the CBCT volume; (S1.4) Use of a trained machine learning method.

[0030] Prior knowledge in step (S1.1) can, for example, be the result of a partial or complete localization that has already taken place. Alternatively, literature or empirical values ​​can also be used as prior knowledge. A dedicated editor can be used as input in step (S1.2), for example, which allows the drawing of splines representing the center lines of the mandibular canal (2) by setting support points.

[0031] Automatic image processing in step (S1.3) can, for example, apply operations such as filtering, thresholding, convolution, application of active shape models, etc. to existing image information such as gray values, edges, histograms, etc. in order to localize the mandibular canal (2).

[0032] In a preferred embodiment, the projection area (3) of the RPA (1) optimized for the mandibular canal (2) serves as a starting point for subsequent navigation through the DVT volume to facilitate mandibular canal-specific workflows. A conventional, dental-specific variant for navigating through the DVT volume is based, for example, on a multiplanar reformation (MPR) as described in Fig. 5 The MPR is typically performed along the guide curve (4), which, as described above, is also used to generate the RPA (1), resulting in the following layers: perpendicular to the patient’s longitudinal axis (axial, Fig. 5 bottom right) perpendicular to axial and tangential to the guide curve (4) (longitudinal, Fig. 5 bottom left) perpendicular to axial and perpendicular to the guide curve (4) (transversal, Fig. 5 bottom center).

[0033] An inventive alignment of the guide curve (4) on the mandibular canal (2) has the following effect: When navigating along the three layers described above, the mandibular canal is always the starting point and thus initially in focus. This facilitates workflows for which the mandibular canal (2) is relevant, such as the placement of an implant, the extraction of teeth, or other surgical interventions in the area of ​​the mandibular canal (2). Another variant for layering the DVT volume is a curved MPR, whereby the corresponding curve is also the guide curve (4) aligned according to the invention on the mandibular canal (2). In this case, too, the mandibular canal (2) is the starting point of the navigation.

[0034] In a preferred embodiment, the result of the mandibular canal localization is displayed on the created RPA (1) (see Fig.6 ).

[0035] Preferably, the resulting RPA (1) is marked where the localized mandibular canal (2) is located outside the projection area (3) (see dashed line in Fig. 6 ), for example, by projecting the localization information of these areas back onto the RPA. This can be done, for example, by color or by the shape / structure of the marking of the mandibular canal (2).

[0036] In a preferred embodiment, in the localization step (S1.4), machine learning methods are used for training, using data pairs of DVT volumes and annotations, wherein these annotations comprise at least one of the following variants: segmentation maps, probability distributions, heat maps, center lines, point clouds, triangular grids, bounding boxes. An annotation refers to the manual or automatic labeling of the structures to be learned during training on a DVT volume in one of the above variants.

[0037] According to the present invention, the data sets generated by the above-mentioned embodiments can be presented to a physician for visualization, in particular for diagnostic purposes, preferably by means of the display (16) or a printout.

Claims

1. A computer-implemented method for automatically producing a reprojection panorama view (RPV) (1) from a dental CBCT volume of a patient, wherein the produced reprojection panorama view is aligned along the mandibular canal (2), and the method comprises the following steps: (S1) localising the mandibular canal (2), characterised by: (S2) automatically defining a projection region (3) of the RPV (1), which comprises the following sub-steps: (S2.1) automatically setting a guide curve (4) in a plane perpendicular to the longitudinal axis of the patient (5) on the basis of the localised mandibular canal (2); (S2.2) automatically defining a variable or constant thickness profile along the guide curve (4); (S2.3) extruding the area defined by the guide curve (4) and the thickness profile along the longitudinal axis of the patient (5); and (S3) creating the RPV (1) by reprojecting the CBCT volume in the defined projection region (3).

2. The computer-implemented method according to Claim 1, wherein the guide curve is determined in step (S2.1) by means of an optimisation which is carried out with regard to a distance measure between the guide curve (4) and the localised mandibular canal (2), taking into account at least one of the following criteria: - maintaining the aesthetics of the resulting RPV (1), wherein at least one of the following criteria is taken as the basis as the measure for the aesthetics: avoiding local distortions of the RPV (1) to be created in step (S3), reducing the imaging-related asymmetry of the RPV (1) to be created in step (S3); - in the case of a guide curve (4) spanned by freely chosen control points (6), limiting the curve complexity, which is determined by the number of the control points (6) or degree of a polynomial.

3. The computer-implemented method according to Claim 1 and 2, wherein the guide curve (4) to be set has one of the following representations with associated optimisation freedoms: - curve (4') which is defined by control points (6) which can be freely chosen and an interpolation rule, wherein the positions of the control points (6) are the free optimisation parameters; - curve (4') which is selected from a set of predefined curve shapes and is adapted under geometric transformations, wherein both the transformation parameters of the geometric transformations and the selection of the curve (4') from the predefined set are optimised; - curve (4') which is parameterised by a function, wherein the function parameters represent the free optimisation parameters.

4. The computer-implemented method according to any one of the preceding claims, wherein, in addition to the mandibular canal (2), further dentally relevant structures are enlisted to optimise the guide curve (4), which comprise at least one of the following: teeth, incisal point, mandibular foramen, mental foramen, mental tubercle, mental protuberance, lingual foramen, mental spine, digastric fossa.

5. The computer-implemented method according to any one of the preceding claims, wherein the guide curve (4) is selected in such a way that at the point of pronounced curvature (7) of the mandibular canal at the mental foramen it continues towards the tip of the chin and thereby follows the criteria of aesthetics, wherein this point can be detected either according to Claim 4 or on the basis of a curvature measure.

6. The computer-implemented method according to any one of the preceding claims, wherein the thickness profile in step (S2.2) results from the fact that for each point on the guide curve (4) a local thickness (D) is determined, which is proportionally adapted to the respective diameter of the mandibular canal (2).

7. The computer-implemented method according to any one of the preceding claims, wherein a constant thickness profile with such a small thickness (D) is chosen that the resulting RPV (1) corresponds to a curved sectional view.

8. The computer-implemented method according to any one of the preceding claims, characterised in that the localising step (S1) comprises at least one of the following sub-steps: (S1.1) utilisation of prior knowledge; (S1.2) manual localisation by the physician using an input means; (S1.3) automatic image processing of the CBCT volume; (S1.4) deployment of a trained machine learning method.

9. The computer-implemented method according to any one of the preceding claims, wherein the projection region (3) of the RPV (1) which is optimised for the mandibular canal (2) serves as the starting point for a downstream navigation through the CBCT volume in order to facilitate mandibular canal-specific workflows.

10. The computer-implemented method according to any one of the preceding claims, wherein the result of the mandibular canal localisation is represented on the RPV (1) created.

11. The computer-implemented method according to any one of the preceding claims, wherein it is marked on the resulting RPV (1) where the localised mandibular canal (2) is located outside the projection region (3).

12. The computer-implemented method according to Claim 7, wherein in the localising step (S1.4), for training, data pairs have CBCT volumes and annotations, wherein said annotations have at least one of the following: segmentation masks, probability distributions, heat maps, centre lines, point clouds, triangular grids, bounding boxes.

13. A computer program comprising computer-readable code which, when it is executed by a computerised CBCT system (8), prompts the CBCT system (8) to execute the method steps of any one of the preceding method claims.

14. A computerised CBCT system (8) comprising an X-ray device (9) and a computing unit (15) which is configured to execute the computer program according to Claim 11.