There is a need in dental medicine for making three dimensional (herein also denoted as “3D”) models of internal scenes of the mouth. The term “intra-oral scene” herein denotes any collection of intra-oral objects, artifacts, surfaces, or features which can be visualized and modeled. Such models of intra-oral scenes can support various aspects of dental practice. A well-known illustration of the utility, effectiveness, and procedural and economic impact of automatic measuring and imaging techniques in dentistry involves the examination, charting, diagnosing, and treatment of dental patients who require prostheses such as crowns, bridges, dentures, or implants. Data and information obtained from measuring, imaging, and mapping intra-oral objects can be used to accurately and cost-effectively design, manufacture, fit, and monitor dental prostheses, thereby replacing currently-used inaccurate non-imaging techniques, which are labor-intensive and otherwise costly in materials and time. Automatic dental measuring and imaging techniques are also applicable for performing various types of restorative procedures, occlusal registration, and orthodontic and tempero mandibular joint (TMJ) dysfunction therapies.
Electro-optical techniques are often used in medical imaging because they are relatively inexpensive in capital outlay as well as in cost-per-use, and are perceived as being non-harmful to the patient. Such techniques, however, must be adapted to the particular circumstances and problems associated with dental imaging.
Important constraints in applying medical optical imaging to the dental field include:                space limitations—equipment must be compact enough to fit comfortably within the confines of the mouth;        time limitations—the image must be formed in a brief time to avoid problems of the movement of the patient as well as the movement of the practitioner and apparatus; and        surface detail limitations—accurately plotting 3D surface contours of intra-oral scenes must take into account the absence or paucity of surface detail in many close-up applications, where only partial views of intra-oral features may be available.        
Measuring the three-dimensional distribution and mapping of intra-oral objects, has been implemented by using various methods. Typical intra-oral objects and features include, but are not limited to a part or entirety of any combination of:
teeth; gum; intra-oral soft tissue; bone matter; dental undercuts; dental fixtures and dental prostheses of any kind, permanent or removable, which are located inside the oral cavity. Specific intra-oral objects and features can be measured, for example, as disclosed in U.S. Pat. No. 6,402,707 to Ernst, one of the present inventors, pertaining chiefly to dental applications. In the present application, many well-known methods can be used for producing a compound database which can be stored in a computer to serve as reference for consequent medical procedures.
In practice, a limitation is imposed by the lack of recognizable surficial surgical features on intra-oral objects. This limitation is often encountered in situations in which a surface is to be sampled three dimensionally for 3D modeling. There are a variety of known techniques to compensate for inadequate quantitative and qualitative surface details. These techniques for improving the acquisition of surface details, include (either separately or combined): spraying the surface of the object to be imaged with powder to improve optical properties for imaging, and projecting and/or diffracting structured illumination patterns and observing their deformation.
Several methods have been disclosed for producing maps or three-dimensional distribution models of surficial features. For example, active triangulation is a specific method that uses an active light spot and several cameras for measuring the distribution of objects on a surface. Scanning the active light spot can produce a whole map of a surface. Photogrammetry is a discipline in which analytic methods are applied for extracting three-dimensional information from photographs. Photogrammetry, as well as any discipline based on images, extends easily to map production because of the range of information obtained by the cameras employed.
As suggested above, it is well-known that making three-dimensional measurements of an intra-oral scene for the purpose of electronically constructing a model of the distribution of features, can be achieved by obtaining multi view images of the intra-oral scene and subsequently applying appropriate analytical algorithms to the images. At least two images of the same intra-oral scene are acquired from different viewing angles. Matching features in the intra-oral scene are searched in the corresponding images. To calculate the relative height (z-dimension) of a feature, the parallax between matching appearances of the feature in different images of the same intra-oral scene is calculated via triangulation, from which the distance of the feature from a reference point is computed. Several common techniques for increasing the distinctness of the features in the images are discussed below.
FIG. 1, to which reference is now made, is a flow-chart describing the order of steps that takes place in the course of a common prior-art three-dimensional modeling of a site of interest. In a step 40 the distinctiveness of features in the intra-oral scene is enhanced. In a step 42 images are acquired of the site of interest at different angles. In a step 44 matching is accomplished between features at the different images acquired. In a step 46 the parallax is measured for identical features in different images. In a step 48 the values on the z-axis are calculated for the identified features. A 3D map, or model, can then be compiled, describing the distribution of the identified features in the xyz-space.
As previously noted, however, a significant limitation in dental work is the lack of surface detail in many situations. Without a substantial amount of surface detail, it is not possible to unambiguously match surface features for accurate triangulation. To solve this problem, instead of illuminating the intra-oral scene uniformly and trying to match features through complex pattern-recognition algorithms, a well-known method is to scan a beam of light across the intra-oral scene to create an array of highlighted lines or points. This “structured illumination” can then be used for matching features in the triangulation previously mentioned. The resulting 3D model is a “wire mesh” or “polyhedral” model of the intra-oral scene. This is an advantageous approach, because the resolution of the model can be easily varied by changing the density of the scanned lines or points over the intra-oral scene, and for many intra-oral scenes of interest, the regions between the lines or points (which are not illuminated by the structured illumination) can be approximated through various smoothing functions. The result is a model of adjustable accuracy which can be analyzed using relatively simple algorithms.
Unfortunately, however, scanning (which is essentially a one-dimensional, or “1D” approach) can sometimes require excessive time, particularly if high resolution is desired. In contrast, imaging (which is a two-dimensional, or “2D” approach) can capture a much greater amount of information in the same time—or, alternatively, can capture the same amount of information in a much smaller time. This factor is important when considering the above-mentioned time limitation, in order to reduce the detrimental effects of patient, practitioner, and apparatus movement.
U.S. Pat. No. 4,687,325 to Corby (herein denoted as “Corby”) notes that it is also possible to employ structured illumination using a single image of the intra-oral scene, whereby the triangulation is performed relative to a stored image (or the data corresponding thereto) of the structured illumination as projected on a plane or other surface of known curvature. Corby, however, is limited to the use of a one-dimensional scanning methodology, which (as discussed above) may not be suitable for certain dental applications because of the patient/practitioner movement that is likely to be encountered. Hans-Gerd Maas in International Archives of Photogrammetry and Remote Sensing Vol. XXIX part B5, pages 709-713 (1992), the contents of which article are incorporated by reference for all purposes as if set forth fully herein, likewise teaches the use of a perfect grid projected on a close object whose surface is to be computed. The projected grid deviates from its original form at the surface from which it reflects, and those deviations from the perfect grid are used to compile the three-dimensional model for the reflective surface. A limitation associated with the employment of regular grids is that of discontinuities and ambiguities. In the case of a discontinuity, a broken grid appearing over the reflecting surface is caused by the discontinuous relief. Broken grid lines are a cause for errors because of the ambiguities introduced by this phenomenon.
Other prior art includes U.S. Pat. No. 4,952,149 to Duret et al. (herein denoted as “Duret”), wherein a method and apparatus is disclosed for taking impressions of a portion of the body which utilizes the projection of a grid of sinusoidal profile onto the body portion of which the impression is to be taken. In U.S. Pat. No. 4,964,770 to Steinbichler et al. (herein denoted as “Steinbichler”), a process is disclosed for making artificial teeth, where horizontal or other contour lines are generated on the ground tooth stump and on adjacent surfaces to create a three-dimensional map. Three-dimensional reconstruction is achieved by the use of interferometry, moiré, and laser scanning methods. In U.S. Pat. No. 5,372,502 to Massen et al. (herein denoted as “Massen 502”), an invention is based on calculating a topographic representation by comparing between a digital image of known pixel detail projected onto a tooth surface and the resulting distorted image reflected off the tooth surface, in accordance with moiré, phase-shift, triangulation, and photogrammetry techniques. Through a comparison between the undistorted pattern projected by the probe and the distorted pattern reflected from the specific area within the oral cavity, topographical information of the imaged teeth is obtained. In U.S. Pat. No. 5,386,292 to Massen et al. (herein denoted as “Massen '292”), an invention is described of an error factor that corrects image distortions due to factors such as enamel translucency. In U.S. Pat. No. 6,529,627 to Callari, et al., by a system is described that uses structured illumination that is manually projected on an object and by deriving the 3D model by integrating the 3D data into the initial 3D model.
One of the recognized problems in using structured light in lines or points is that of aliasing, or false matching of the structured illumination. A plain point of light is normally indistinguishable from other plain points of light, and so there can arise ambiguities in matching the same point from one image to another. If two different points are mistakenly matched when triangulating different images, the resulting z-axis calculation will be in error, and the 3D model will be defective. (The same problem applies to the use of lines.) In real-time scanning using electronic imaging, synchronizing the output from the different image sensors serves as an anti-aliasing mechanism. However, this cannot be employed for projected (non-scanned) images or for stored images where features are matched after the structured illumination has been projected, because there is no timing information. It also cannot be used with the single imaging method mentioned above. Several anti-aliasing methods, using different schemes of encoding the structured illumination, are described in Corby. Some of these methods involve modulating the structured illumination in wavelength and/or intensity. Corby's own method involves encoding spatially-modulated predetermined patterns in the scanned light, which can be unambiguously matched in the different images.
Once again, the time limitation presented above is noted for dental applications. In particular, certain prior art schemes would require illuminating the same areas of the intra-oral scene with patterns over a prolonged time period or repeatedly at different times. These practices, however, can introduce inaccuracies in the measurements due to any relative movement between the dental patient, the apparatus that projects the illumination, and the apparatus that captures the images (camera). This condition is exacerbated if the apparatus is being held or manipulated by the dental practitioner, because in this case there is an additional source of movement involved.
U.S. Pat. No. 6,167,151 to Albeck, et al. (herein denoted as “Albeck '151”) discloses a means of creating a spatially-modulated random pattern by the phenomenon of laser speckle, which can then be used in a similar manner to the predetermined patterns of Corby, for identifying corresponding points in multiple images. An advantage of random patterns over predetermined patterns in anti-aliasing is that certain random systems can mathematically generate a large number of distinct patterns easily, whereas systems of distinct predetermined patterns are generally more restricted and thus limited in number. On the other hand, however, predetermined patterns (such as in Corby) can be set up in advance to be absolutely distinguishable. Random patterns, in contrast, are not predetermined, and therefore may exhibit some similarities among themselves. The patterns of Albeck '151, for example, which depend on the interference properties of coherent light upon uneven surfaces, are probabilistic and therefore different patterns can be similar in appearance, even though this is unlikely. The anti-aliasing of Albeck '151, therefore, is statistical rather than absolute.
A principal limitation of Albeck '151 is that the random patterns, being created by a physical process (laser speckle), can be neither stored nor reproduced. This requires that the multiple images of the intra-oral scene under the structured illumination be captured simultaneously in order that the same random speckle patterns be included in the different images. The fact that the random patterns of Albeck '151 cannot be stored or reproduced also precludes using a single image of the intra-oral scene under the structured illumination which is later referenced to a previously-stored image of the structured illumination impinging on a known surface, such as a planar surface (previously noted to have been described in Corby).
As noted above, an important limitation is imposed by the small space inside the mouth, which does not permit the introduction of bulky apparatus. In particular, it would be highly advantageous to use only a single imaging sensor (producing a single image or single projection) to capture the structured illumination patterns on the intra-oral features for comparison with the recorded structured illumination patterns on a known surface. Doing so would significantly reduce the amount of apparatus placed in the mouth and be responsive to the space limitation of dental applications, as previously noted. Furthermore, it would be desirable to employ an imaging, rather than a scanning technique, to eliminate problems caused by movement of the patient and/or the practitioner.
There is thus a need for, and it would be highly-desirable to have, a system and method for use in three-dimensional modeling of intra-oral features in dental applications that provides compact apparatus for use in the confines of the mouth, simultaneous acquisition of three-dimensional information over the entire intra-oral scene to eliminate problems caused by patient and/or practitioner movement, and the ability to extract three-dimensional information from partial scenes which do not have large amounts of surface detail. These goals are met by the present invention.