Patent ID: 12190436

DETAILED DESCRIPTION

Intraoral tomosynthesis is an approach to dental imaging capable of capturing some 3D information. During intraoral tomosynthesis, low-dose x-ray projections are collected across a limited angle-span using a pre-determined geometry relative to a digital detector placed inside the mouth. Each projection delivers a fraction of the dose used for a single, standard 2D radiograph. As such, the total dose delivered to the patient during intraoral tomosynthesis is similar to that of standard 2D dental radiography. Although the series of projection views can be obtained by moving a single x-ray source into the necessary locations, perhaps using an optical system to ensure accurate positioning, a multi-source array provides a reliable approach for collecting multiple projection images quickly.

A distributed array of fixed x-ray sources made possible by carbon nanotube-cathode technology has been developed for dental tomosynthesis imaging. Referred to as stationary intraoral tomosynthesis (sIOT), this experimental approach to dental imaging offers a device size, operation, and study time similar to standard 2D dental imaging. This technology was disclosed in the following patents: U.S. Pat. Nos. 9,782,136 and 9,907,520, the disclosures of which are incorporated by reference herein in their entireties. However, regardless of the technique used to acquire the intraoral tomosynthesis scan, computer processing is needed to generate clinically useful images from the information collected at the time of the study. The series of computer algorithms that accomplish each of the necessary processing steps is known as the image processing chain, and the method described hereinbelow is a novel image processing chain that generates multi-view synthetic dental radiographs from intraoral tomosynthesis images.

Multi-view synthetic dental radiographs represent a unique display of the information collected by intraoral tomosynthesis, since this set of computer-generated images recreates what the viewer would see if a series of x-rays were obtained from different viewpoints. In this way, imaging at a dose typical for a single dental radiograph yields multiple computer-generated images that appear to have been taken across a span of angles. There are several advantages to presenting 3D dental x-ray information in this way. First, the synthetic image can be generated from any angle, not just the angles used to acquire the images. Thus, a site-of-concern can be visualized from different perspectives, which can be selected after the scan has been completed. Second, the synthetic images appear similar to standard 2D dental radiographs, and thus, their interpretation does not require additional training or experience. Third, the processing steps used to generate the synthetic images provide an opportunity to remove artifact commonly present in intraoral tomosynthesis images. Finally, analysis of the 3D image space allows for the identification of specific features of interest. These features can then be highlighted in the synthetic images, potentially improving the diagnostic value of the information presented to the reader. As such, the ability to generate multi-view synthetic dental radiographs is anticipated to enhance the clinical utility of intraoral tomosynthesis.

The systems and methods described herein may improve the diagnostic value of dental radiography by providing a novel approach to displaying the information collected by intraoral tomosynthesis, which is a low-dose dental x-ray imaging technique capable of capturing some depth information, using technology that is practical for the dental clinic. More specifically, this disclosure involves a processing method that generates multi-view synthetic dental radiographs. The processes and systems described herein improve the computer related technology of intraoral dental imaging and diagnosis. Since synthetic images are mathematically-generated through computer processing, they can replicate the appearance of an x-ray taken from a range of perspectives, using the information acquired previously at the time of the study. In this way, the intraoral dental imaging technology is improved because when interpreting the images, different viewing perspectives can be selected in order to maximize the display of a specific site-of-concern. In other words, dental lesions and decay that previously could not be seen by traditional dental imaging techniques (without significant x-ray exposure) are more visible using the techniques described herein.

Additionally, the methods and systems disclosed herein improve the computer related technology of dental imaging by helping to minimize the time a dental professional must spend going through multiple 2D images, by emphasizing specific features inside the patient's mouth, and allowing for a faster conclusion by the dental professional. Accomplished by the assistance of software, the systems and methods described herein involve a series of image processing steps, known collectively as the image processing chain. Each step accomplishes a key manipulation of the information in the image, so that when linked together, the result is a clinically-useful set of unique dental images, further improving the computer related technology of intraoral dental imaging.

The image processing chain first constructs a 3D image space from the 2D information available in the set of projection images collected at the time of the study. A forward-projection algorithm then integrates the information in the 3D image stack into a plurality of synthetic dental radiographs that display information from at least two arbitrary viewing angles. In this way, imaging at a dose typical for a single dental radiograph yields multiple computer-generated images that appear to have been taken from different perspectives. Since these perspectives need not be the same as those from which the original x-ray projections were acquired, views can be selected that best display a specific site-of-concern after the study has been completed. This disclosure also includes additional processing steps that may improve the diagnostic value of the final dental images. These additional processing steps can be described generally as filtering, metal-artifact reduction (MAR), and feature of interest enhancement, each customized to dental imaging. Taken in its entirety, this novel method for processing and presenting dental x-ray images has the potential to enhance the clinical utility of intraoral tomosynthesis.

This description should be read in conjunction with the figures, which are designed to illustrate the concepts discussed herein by depicting representative embodiments of the present disclosure. However, since the present disclosure may be embodied in many different forms, the figures should not be construed as limiting the interpretation of the disclosure to a specific embodiment. Similarly, although this written description includes specific terminology for the sake of clarity, this specificity is not intended to limit the interpretation of this disclosure to any particular embodiment.

The subject matter herein discloses a novel method for processing the information acquired by intraoral tomosynthesis, which is a low-dose, limited-angle tomography technique for dental x-ray imaging. This approach to dental imaging allows for the collection of some depth information, using equipment that can be incorporated into a typical dental office. More specifically, the disclosure presented herein is a method that generates a plurality of synthetic dental radiographs, incorporating a unique functionality that allows selection of the viewing perspectives after the scan has been done, regardless of the angle at which the original x-rays were obtained. As such, a viewing angle can be selected that maximizes the display of a site-of-concern, potentially improving the diagnostic value of the dental radiograph.

Assisted by software, the systems and methods of the present disclosure can be applied to any intraoral tomosynthesis system, with intraoral referring to the location of the detector in the mouth, as long as the system includes one or more processors (computers) for implementing the method and a digital monitor to display the final image products. Intraoral tomosynthesis devices work by collecting a series of projection images across a limited angle-span, using a fixed geometry relative to the intraoral detector. The series of projection images can be acquired by a single x-ray source, which is moved into precise locations, perhaps using optical clues for positioning, or by an array of distributed sources. The array of distributed sources can optionally be connected to the detector in some way to lock it into the correct orientation, as depicted inFIG.1. Regardless of the system used to obtain the tomosynthesis scan, the information available in this set of projection images provides the starting point for the method described herein. This method is a chain of image processing steps, which manipulates the information in the projection images in order to produce a set of synthetic dental radiographs. These descriptions should convey the functionality of the systems and methods presented herein to anyone skilled in the field of dental imaging technology and image processing software.

FIG.1is a schematic of an intraoral tomosynthesis device100. AlthoughFIG.1depicts an intraoral tomosynthesis device100, those having ordinary skill in the art will appreciate that various imaging systems can be used to help perform the processes described herein. Furthermore, although the present disclosure primarily describes the subject matter herein with reference to intraoral tomosynthesis and dental radiographs, those having ordinary skill in the art will appreciate that the systems and methods herein can also be applied to non-dental related imaging. The disclosure herein should not be interpreted as being limited to dental or intraoral related imaging alone. For example and without limitation, the systems and methods described herein can be utilized to perform similar manipulations on tomosynthesis images captured for breast imaging as well as imaging of various other parts of a subject's body. In this depiction, an x-ray source102comprising an array of distributed x-ray sources104is connected to an intraoral x-ray detector108, in order to maintain a fixed geometry. In some embodiments, the x-ray source102can be disconnected from the intraoral x-ray detector108. In some embodiments, the intraoral tomosynthesis device100is configured to capture x-ray exposures106of the subject110(i.e., for example and without limitation, a dental patient's teeth or mouth) from multiple angles to provide a set of 2D projection images, which serve as the starting point for the methods and processes described herein.

Referring toFIG.2, which illustrates a flow chart depicting steps in a method or an image processing chain200that generate multi-view synthetic dental radiographs from the information acquired by an intraoral tomosynthesis scan or other suitable imaging methodology. The purpose of the illustration is to provide a representative embodiment of the image processing chain to demonstrate how each step accomplishes a task upon which the other steps depend. However, since these steps can be connected in different ways and accomplished by various algorithms,FIG.3should not be construed so as to limit the interpretation of the disclosure to this specific embodiment. Additionally, those having ordinary skill in the art will appreciate that one, some, or all of the steps in the image processing chain200can be performed by one or more processors, including a single central processing unit (CPU) comprising one or more cores. Additionally, each step in the image processing chain200can be performed by a separate computer program/subroutine or a single subroutine or computer program function. Moreover, those having ordinary skill in the art will appreciate that steps in the image processing chain200can be performed by hardware and/or software, including a centrally positioned processing engine or distributed processing mechanisms. In this way, dedicated processors, hardware, subroutines, application specific integrated circuits (ASICS) or other components can perform some or all of the steps of the image processing chain200.

In some embodiments, the first step202in the image processing chain200or method comprises producing or capturing one or more x-ray projections from multiple viewing angles. In some embodiments, the method for capturing the x-ray projections can include using intraoral tomosynthesis. In such an embodiment, the method can further comprise positioning an intraoral x-ray detector in a subject's mouth. Furthermore, the method can comprise determining a position of the intraoral x-ray detector relative to one or more x-ray source. The method can also comprise producing or capturing one or more x-ray projections from multiple viewing angles relative to the intraoral x-ray detector and then transferring the one or more x-ray projection images to one or more processors for processing as discussed further hereinbelow. Although this description explains the subject matter herein with regard to intraoral tomosynthesis, those having ordinary skill in the art will appreciate that other imaging methods may be used as well. In some embodiments, after the x-ray projections are captured or produced, the method comprises generating a plurality of 2D synthetic dental radiographs by manipulating the information contained in the set of x-ray projections acquired at the time of the intraoral tomosynthesis (or other imaging method) scan. This “information” refers to the intensity values measured at each pixel by a digital intraoral x-ray detector, which then transfers the information to computer memory for storage. Once available in the computer, the information can be displayed as a digital image on a monitor, display, or screen, and is also available for manipulation by processing (computer programs or algorithms). The image processing chain200described herein works by manipulating these pixel intensity values.

In some embodiments, in the second step204, the method comprises filtering of the plurality of 2D projection images, customized to the dental image. Such filtering can include, for example, processing to reduce the noise, processing to highlight or segment areas of interest with specific pixel intensities. Filtering can be helpful at this early stage to prepare the pixel intensity values in the projection image for further processing. Additionally, given the significant artifact present around high-contrast features in intraoral tomosynthesis images, these features can be identified and removed, or reduced, from the projection image prior to generating the 3D image space. In some embodiments, in the third step206, the method of the present disclosure comprises determining whether artifact reduction, for example and without limitation, metal-artifact reduction, is necessary. In some embodiments, the method determines whether artifact reduction is necessary by identifying significant areas of corresponding to presence of high x-ray attenuation materials. If YES, in some embodiments, the image processing chain200moves to the fourth step208. In some embodiments, the processing chain reduces the artifacts by manipulating the pixel values to reduce the impact of the artifacts. One embodiment of this artifact reduction approach is described in detail with the description ofFIG.9.

If artifact reduction is not needed, the image processing chain200moves to the fifth step210in the process and bypasses the fourth step208. Additionally, if artifact reduction was necessary, after the reduction has occurred, the image processing chain200also moves to the fifth step210. The information available in the modified (i.e., filtered and/or artifact reduction) projection images can then be used to generate a 3D image space. The processing that generates the 3D image space from the information available in the modified set of 2D projection images is known collectively as “reconstruction.” The method presented herein will accept any reconstruction approach, ranging from filtered back projection (FBP) to iterative and/or analytical reconstruction by algebraic or statistical techniques, such as simultaneous iterative reconstruction technique (SIRT), simultaneous algebraic reconstruction technique (SART), or maximum likelihood expectation maximization (MLEM), as long as the processing has been customized to dental imaging, including intraoral tomosynthesis. In some embodiments, the 3D image space is a matrix of voxels or voxel values with calculated intensity values.

Examples of early references for image reconstruction methods include:FBP: L. A. Feldkamp, L. C. Davis, and J. W. Kress, “Practical cone beam algorithm,” J. Opt. Soc. Am. A, vol. 1, pp. 612-9, June 1984.SIRT: P. Gilbert, “Iterative methods for the reconstruction of three dimensional objects from their projections,” J. Theor. Biol., vol. 36, pp. 105-117, 1972.SART: A. H. Andersen and A. C. Kak, “Simultaneous algebraic reconstruction technique (SART): A superior implementation of the art algorithm,” Ultrason. Imaging, vol. 6, pp. 81-94, January 1984.MLEM: Dempster A, Laird N, and Rubin D, “Maximum likelihood from incomplete data via the EM algorithm, Journal of the Royal Statistical Society, 39, 1-38, 1977.

Once available, the 3D image space provides an opportunity to identify and emphasize features of interest using techniques customized to dental imaging. In some embodiments, the method disclosed herein further comprises a sixth step212, namely, manipulating the voxel values using various techniques to emphasize the features of interest. Techniques applicable to the method presented herein cover a range of algorithms, such as filters or deep-learning approaches. In general, these algorithms apply a tunable or adjustable weighting function to the 3D image space, in order to identify and/or enhance specific features of interest. For example and without limitation, feature enhancement could include caries enhancement, fracture enhancement, or any other suitable feature enhancement process. As it may occur in different embodiments of this method, the weighting function may sort voxels by intensity and then mathematically emphasize voxels with intensity values typical of the feature of interest, while suppressing voxel values that could obscure the feature of interest, or the weighting function may emphasize different frequency components of the image. As different features, such as caries or fractures, have quite different image properties, the weighting function must have a tunable parameter in order to selectively enhance a specific feature. As an example, if the dentist is concerned about a fracture, weighting to emphasize high-frequency image components may improve the chances of seeing the fracture, which would be detected by its fine edge (a high frequency feature) in the image.

Once the 3D image space is generated, or reconstructed, and feature-of-interest enhancement has occurred, in some embodiments, the method includes an eighth step216, namely, generating a plurality of multi-view 2D synthetic dental radiographs from the information available in the 3D image space. Additionally, if the image processing chain200performed artifact reduction (i.e., went to step four208), those images go through step seven214, wherein a feature replacement procedure takes place to enhance the areas around where the artifact reduction took place. Additionally, in some embodiments, the method includes a ninth step218, namely, filtering the 2D synthetic dental radiographs to improve the display of one or more features of interest. Such filtering steps may include, but are not limited to, smoothing by noise reduction, sharpening by edge enhancement, and histogram rebalancing for feature of interest enhancement. Finally, in the tenth step220, once the plurality of 2D synthetic dental radiographs have been processed, all or a subset of them can be displayed on a display for a dental professional or other person to view.

Referring toFIG.3, which depicts a logical diagram of a subset300of the steps taken in the image processing chain. In some embodiments, as described herein, the image processing chain uses the 2D information302available in the set of projection images acquired at the time the dental images are captured to mathematically generate a 3D image space304. The 3D image space304, described in more detail hereinbelow, is a mathematical construct that contains the information needed to create the synthetic dental radiographs. Additional algorithms, such as filtering, artifact reduction, and feature enhancement can be incorporated to improve the display of one or more features of interest, as described below. Once the 3D image space304is generated, a set of multi-view dental radiographs306can be synthetically generated (i.e., by one or more processors) from the 3D image space304.

Referring toFIG.4AandFIG.4B, which illustrate flow charts depicting small differences between generating various feature enhanced images, including carries-enhanced synthetic radiographs400A and fracture-enhanced synthetic radiographs400B. In the carries-enhanced synthetic radiographs flow chart400A, as described above, the first step in the process402A is capturing or generating intraoral projection images. Once the images have been captured, they are reconstructed404A, as described herein, into a 3D image space or 3D image stack406A. From there, in some embodiments, the 3D image stack406A is processed and filtered408A, as described herein, to enhance features that detail caries in the teeth. In some embodiments, in order to better emphasize and enhance any caries in the subject, the process can comprise selectively emphasizing lower-frequency components, which can improve the visibility of caries. The caries-enhanced image stack410A can then be forward projected412A, for example and without limitation, onto a monitor, display, or screen for a dentist, dental hygienist, doctor, or other viewer to view one or 2D caries-enhanced synthetic radiographs414A, where, each of the radiographs are synthesized by one or more processors from the caries-enhanced 3D image stack410A.

The method for generating fracture-enhanced synthetic radiographs400B is almost identical to the method for generating caries-enhanced synthetic radiographs400A. However, in some embodiments, in the method for generating fracture-enhanced synthetic radiographs400B, instead of filtering to enhance caries408A, the method for generating fracture-enhanced synthetic radiographs400B includes filtering to isolate the background of the images408B, such as selecting low frequency components and or thresholding pixel values. Additionally, the image can be filtered, for example, by selectively emphasizing the higher-frequency components of the image, which can improve the visibility of small fractures. Once filtered, the background-isolated 3D image stack410B can be selected to enhance some features such as fractures. The feature enhanced 3D images stack together with background overlap tissue images414B then can be forward projected to generate 2D fracture-enhanced synthetic radiographs416B.

Referring toFIG.5, which illustrates another depiction of some steps in the image processing chain of the present disclosure as well as how they interact with physical structures of an x-ray imaging system. The system illustration500depicts both physical structures and virtual processes that make up parts of the methods and systems of the present disclosure. For example and without limitation, the array of spatially distributed x-ray sources104can be configured to expose the subject110to x-ray radiation106at different angles, generating one or more intraoral tomosynthesis projection images502. The projection images502are captured by the detector108(not visible in this view, but positioned behind the subject110) and transmitted to one or more processors (not shown in this view) for processing.

In some embodiments, the one or more processors are configured for reconstructing the one or more intraoral tomosynthesis 2D projection images into a 3D image space506. Once the 3D image space506is created and the various filtering and manipulations of the data in the 3D image space506described herein are complete, the one or more processors is configured to digitally generate one or more multi-view synthetic 2D images510from various angles of the manipulated 3D image space508.

FIG.5further illustrates an example of the step in the image processing chain that generates the multi-view synthetic dental radiographs from the enhanced information now present in the 3D image space. Since the information present in the 3D image space can be projected into a synthetic dental radiograph from any arbitrary angle, this method provides a unique approach to displaying dental images by replicating how a standard 2D radiograph would appear if it had been obtained from the selected viewing angle. By providing a range of perspectives, a set of synthetic images can best display a specific site-of-concern.

Again, as described above, the disclosure herein should not be interpreted as being limited to dental or intraoral related imaging alone. For example and without limitation, the systems and methods described herein can be utilized to perform similar manipulations on tomosynthesis images captured for breast imaging as well as imaging of various other parts of a subject's body.

Referring toFIG.6, which illustrates the effects of applying a tunable weighting function to the 3D image space in order to enhance specific features of interest.FIG.6is a partial system illustration600of the system and methods of the present disclosure. As depicted inFIG.6, multi-view synthetic 2D dental radiographs can be generated from the manipulated 3D image space508from multiple angles to provide additional feature enhancements compared to that inFIG.5. For example, selectively emphasizing the higher-frequency components of the image may improve the visibility of small fractures, whereas emphasizing lower-frequency components may improve the visibility of caries. The application of each weighting function produces a unique set of multi-view synthetic dental radiographs. In other words, based on the manipulation of the data in the 3D image space, caries enhanced images512and/or fracture-enhanced images514can be generated.

Referring toFIG.7, which depicts comparisons700between synthetic radiographs702, generated using systems and methods according to some of the embodiments of the present disclosure, and standard radiographs704, generated according to previously available techniques. As depicted in the comparison pictures, the synthetic radiographs702show more detail such that additional caries and dental disease/lesions can be found and distinguished from healthy tissue. As depicted inFIG.7, the synthetic radiographs702can be generated from multiple angles706with respect to a particular region or perspective. The standard radiograph704on the other hand cannot be generated from multiple angles, it is generated from a single angle708. As can be seen in from the multiple angles706, the tooth surfaces in the region where two teeth come into contact can be separated only in certain view angles of the synthetic radiographs702, which are available only in synthetic radiograph images. Whereas, in standard radiographs704, the overlap surfaces blur the teeth boundary thus inhibiting the proper diagnosis of potential carries in the region.

Referring toFIG.8AandFIG.8B, further comparisons800A and800B between images that are reconstructed with metal-artifact reduction (MAR) and without MAR are provided. As shown in comparison800A when the image is reconstructed using MAR, the tissue around the implant screw is much more visible and pathology is much more visible as compared to the image not reconstructed using MAR. The graph below the comparison images800A indicate the difference in pixel intensity between the image with and without MAR. As shown, the pixel intensity without MAR is much lower around the edges of the screw than the pixel intensity with MAR. Comparison800B illustrates a zoomed-in radiograph where the image with MAR clearly identifies tooth decay underneath the metal filling (bright white amorphous shape) whereas the image without MAR is unclear as to whether decay is present. At a minimum, the image without MAR indicates a significant amount of false positives that would likely lead a professional to ignore the area because of the likelihood of metal-artifact skewing the image.

Referring toFIG.8CandFIG.8D, more comparisons800C and8000between synthetic radiographs802C and8020and standard radiographs804C and804D are depicted. InFIG.8A, the comparison800C is made to illustrate how metal-artifact reduction, part of the filtering processes of the image processing chain of the present subject matter, can be used to better reduce metal artifacts around metal objects in the mouth (e.g., screws, fillings, surgical implants, etc.) and give the professional viewing the synthetic radiographs802C a better visualization of the subject being imaged. Those having ordinary skill in the art can readily appreciate that the areas around the filling in the synthetic radiograph802C is much more clearly defined and is comparable to the standard radiograph804C taken of the same tooth.

As depicted inFIG.8D, the comparison800D here shows how fracture enhancement filtering can give more detail on a fracture in the imaged subject. As depicted in the synthetic radiograph802D, there is a clearly defined and distinct line or crack running down the tissue. The crack or line is not so clearly visible in the standard radiograph804D.

FIG.9is a flow chart900depicting changes in the image information as images are manipulated by some of the processing steps of an artifact reduction approach, as these changes would appear to a viewer during an embodiment of the present disclosure. However, since there are potentially many approaches to accomplishing artifact reduction, including different techniques to complete each of the key steps, as well as different locations within the overall image processing chain where these steps can be applied, the figure should not be construed as limiting the interpretation of the present disclosure to this specific embodiment. Artifact reduction is important when developing an image processing chain for intraoral tomosynthesis, given the frequent presence of artifact-producing objects in the mouth, including metal such as amalgam and implant posts. These artifacts, which can hide pathology, are the result of the processing required to generate the 3D image space and can be amplified by the algorithms which generate the final synthetic images. As such, artifact reduction techniques are needed in some embodiments to minimize these artifacts in order to maximize the clinical value of the displayed images. As shown in the representative approach inFIG.9, artifact reduction begins at the level of the projection images. The first image902, represents such an example 2D projection image captured by means of, for example and without limitation, intraoral tomosynthesis.

Once the first image902is captured, the process continues with the segmentation904and then removal of the pixel values corresponding to an artifact-producing feature. “Segmentation” refers to identifying the pixels which make up a particular feature such as an artifact-producing feature. A host of segmenting approaches customized for the dental image can be envisioned, all of which would be applicable with the method presented herein. For example, as many features in dental images have a high contrast relative to their background and contain sharp edges, one embodiment of this method may include edge-detecting segmentation approaches involving thresholding and/or thresholding the gradient magnitude of the image to identify the pixels that define a feature and/or its boundary, respectively, with “thresholding” referring to the identification of pixels that have an intensity value above a defined level, and the “gradient magnitude” representing the relative change between pixel values in the image. The second image906in the flow chart900illustrates a segmented 2D projection image, segmented according to some embodiments of the present disclosure.

Following segmentation, the artifact-producing feature's pixel values must be replaced in order to proceed through the image processing chain. Therefore, the features must be filled in during a feature filling step908. Methods such as interpolation-based in-painting can be used to estimate appropriate pixel values for the feature filling step908. For example, and without limitation, pixel values can be assigned to segmented regions by inward interpolation from surrounding pixel values for each of the 2D projection images (i.e., the images before they are reconstructed into the 3D image space). However, the features removed from the projection images can have diagnostic value, and as such, in some embodiments, they must be returned to the final synthetic images prior to their display. Once the features are filled in, the image will look similar to the third image910. This represents one of the 2D projection images that will be reconstructed912into the 3D image space. The fourth image914depicts an example slice from the 3D image space after the reconstruction912stage. Once the 3D image space is created, the synthetic dental radiographs are generated916. In this representation, the synthetic dental radiographs include features that are filled in. Using the locations of the segmented pixels in the original projection images, the features can be replaced in the synthetic dental radiographs, with an orientation and appearance appropriate to the selected viewing angle used to generate the synthetic images. The fifth image918illustrates a synthetic dental radiograph with filled-in features.

The synthetic dental radiographs can be optimized by applying additional filtering to improve the quality of the final images. As may be seen in some embodiments of this method, the filtering will involve a string of customized and complementary filters, which the reader can select for a specific dental imaging task. As an example, in order to maximize the display of a tooth fracture, edge-preserving low pass filtering to reduce noise may need to be combined with high-pass filtering to emphasize the fracture edge. Before the final synthetic dental radiographs are ready for display, some of the features, such as, for example and without limitation, fillings or implants, are replaced920and924. This step includes inspecting the original projection image (i.e. the first image902) to determine the details of the feature to be replaced. Finally, the sixth image922illustrates what the final synthetic dental radiograph would look like after all filtering and manipulation is complete. The set of final synthetic images are then displayed to a viewer, such as for example and without limitation, a dental professional, for them to view.

Referring toFIG.10, which illustrates a topology diagram of a system1000of the present disclosure. For example and without limitation, the system1000can comprise an x-ray imaging device1030configured to capture one or more x-ray images of a subject, as described with respect toFIG.1. In some embodiments, the x-ray imaging device1030is in communication with a display1010and/or an image processing system1020. In some embodiments, the image processing system1020is configured to receive, via wireless or wired connection, one or more 2D projection images from the x-ray imaging device1030. As described above, the 2D projection images can be taken from different angles with respect to the subject and transmitted to the image processing system1020from the x-ray imaging device1030.

In some embodiments, the image processing system1020comprises one or more processors1022and non-transitory, computer-readable memory1024. In some embodiments, the one or more processors can be configured to manipulate the 2D projection images according to the various processes described hereinabove. Those having ordinary skill in the art will appreciate that the memory1024can be used to store image data, executable instructions for performing the various processes described above, or any other suitable data. In some embodiments, the one or more processors1022can comprise a single processor with multiple cores, or multiple distinct processors. Once the processor1022has completed manipulating the images, as described above, the image processing system1020is configured to transmit the images to the display1010. In some embodiments, those having ordinary skill in the art will appreciate that the image processing system1020can be configured to transmit the manipulated images to the display1010when a viewer requests the images via buttons or some other tool on the display1010. In some other embodiments, the image processing system1020can be configured to automatically transmit the manipulated images to the display1010after the image manipulation processes are complete.

Additionally, the display1010is configured to receive x-ray images from either the x-ray imaging device1030(i.e., non-manipulated images) or one or more synthetic dental radiographs from the image processing system1020(i.e., x-ray images manipulated according to the processes described herein). Once received, the display1010can be configured to display one or more of the received images based on automatic or manual request from the viewer.

The present description also discloses a system for generating or producing one or more multi-view synthetic dental radiographs. In some embodiments, such a system can comprise a display in communication with an image processing system comprising one or more processors and a computer readable medium such as memory or random-access memory (RAM). In some embodiments, the imaging processing system can be configured to implement the method described herein above. In some embodiments, the image processing system can be combined with an intraoral tomosynthesis device or other x-ray machine to create a whole system that not only captures the x-rays but also processes the images according to the steps discussed hereinabove. In some embodiments, the system for generating one or more multi-view synthetic dental radiographs can be separate and apart from an intraoral tomosynthesis machine or other x-ray machine.

The present subject matter can be embodied in other forms without departure from the spirit and essential characteristics thereof. The embodiments described therefore are to be considered in all respects as illustrative and not restrictive. Although the present subject matter has been described in terms of certain preferred embodiments, other embodiments that are apparent to those of ordinary skill in the art are also within the scope of the present subject matter.