Abstract: A method for 3-D cephalometric analysis acquires reconstructed volume image data from a computed tomographic scan of a patient's head. The acquired volume image data simultaneously displays from at least a first 2-D view and a second 2-D view. For an anatomical feature of the head, an operator instruction positions a reference mark corresponding to the feature on either the first or the second displayed 2-D view and the reference mark displays on each of the at least first and second displayed 2-D views. In at least the first and second displayed 2-D views, one or more connecting lines display between two or more of the positioned reference marks. One or more cephalometric parameters are derived according to the positioned reference marks, the derived parameters are displayed.

Abstract: A method for 3-D cephalometric analysis of a patient, executed at least in part on a computer processor, displays reconstructed volume image data from a computed tomographic scan of a patient's head from at least a first 2-D view and accepts an operator instruction that positions and displays at least one reference mark on the at least the first displayed 2-D view. One or more dentition elements within the mouth of the patient are segmented and cephalometric parameters for the patient computed and displayed according to data from the at least one reference mark and the one or more segmented dentition elements. Using the computed cephalometric parameters, one or more results indicative of maxillofacial asymmetry are computed and a graphical or text display energized to show the computed results indicative of asymmetry.

Abstract: A method for 3-D cephalometric analysis acquires reconstructed volume image data from a computed tomographic scan of a patient's head. The acquired volume image data simultaneously displays from at least a first 2-D view and a second 2-D view. For an anatomical feature of the head, an operator instruction positions a reference mark corresponding to the feature on either the first or the second displayed 2-D view and the reference mark displays on each of the at least first and second displayed 2-D views. In at least the first and second displayed 2-D views, one or more connecting lines display between two or more of the positioned reference marks. One or more cephalometric parameters are derived according to the positioned reference marks, the derived parameters are displayed.

Abstract: A method for 3-D cephalometric analysis acquires reconstructed volume image data from a computed tomographic scan of a patient's head. The acquired volume image data simultaneously displays from at least a first 2-D view and a second 2-D view. For an anatomical feature of the head, an operator instruction positions a reference mark corresponding to the feature on either the first or the second displayed 2-D view and the reference mark displays on each of the at least first and second displayed 2-D views. In at least the first and second displayed 2-D views, one or more connecting lines display between two or more of the positioned reference marks. One or more cephalometric parameters are derived according to the positioned reference marks, the derived parameters are displayed.

Abstract: A method for 3-D cephalometric analysis of a patient, executed at least in part on a computer processor, displays reconstructed volume image data from a computed tomographic scan of a patient's head from at least a first 2-D view and accepts an operator instruction that positions and displays at least one reference mark on the at least the first displayed 2-D view. One or more dentition elements within the mouth of the patient are segmented and one or more cephalometric parameters computed for the patient according to the at least one reference mark and the one or more segmented dentition elements. One or more results generated from analysis of the one or more computed cephalometric parameters are displayed.

Abstract: A computer-implemented method for generating a digital model of an individual intraoral component from a digital model of a patient's dentition obtains a 3-D digital mesh model of the patient's dentition and performs automatic tooth component segmentation operation on the obtained mesh model. Automated segmentation results display. Interactive segmentation of the automated segmentation results is performed according to an operator instruction. Segmentation results are displayed and stored.

Abstract: A method of automatic tooth segmentation, the method executed at least in part on a computer system acquires volume image data for either or both upper and lower jaw regions of a patient and identifies image content for a specified jaw from the acquired volume image data. For the specified jaw, the method estimates average tooth height for teeth within the specified jaw, finds a jaw arch region, detects one or more separation curves between teeth in the jaw arch region, defines an individual tooth sub volume according to the estimated average tooth height and the detected separation curves, segments at least one tooth from within the defined sub-volume, and displays the at least one segmented tooth.

Abstract: A method for imaging the surface of a tooth, the method executed at least in part on a computer records a first set of images of the tooth, wherein each image in the first set of images is illuminated according to a pattern oriented in a first direction. A second set of images of the tooth are recorded, wherein each image in the second set of images is illuminated according to a pattern oriented in a second direction that is shifted more than 10 degrees with respect to the first direction. A first contour image is reconstructed according to the recorded first set of images and a second contour image according to the recorded second set of images. A residual image is formed as a combination of the first and second contour images. The residual image is analyzed and surface conditions of the tooth reported.

Abstract: A method of automatic tooth segmentation, the method executed at least in part on a computer system acquires volume image data for either or both upper and lower jaw regions of a patient and identifies image content for a specified jaw from the acquired volume image data. For the specified jaw, the method estimates average tooth height for teeth within the specified jaw, finds a jaw arch region, detects one or more separation curves between teeth in the jaw arch region, defines an individual tooth sub volume according to the estimated average tooth height and the detected separation curves, segments at least one tooth from within the defined sub-volume, and displays the at least one segmented tooth.

Abstract: A method of automatic tooth segmentation, the method executed at least in part on a computer system acquires volume image data for either or both upper and lower jaw regions of a patient and identifies image content for a specified jaw from the acquired volume image data. For the specified jaw, the method estimates average tooth height for teeth within the specified jaw, finds a jaw arch region, detects one or more separation curves between teeth in the jaw arch region, defines an individual tooth sub volume according to the estimated average tooth height and the detected separation curves, segments at least one tooth from within the defined sub-volume, and displays the at least one segmented tooth.

Abstract: A method for segmenting an object in a volume image, executed at least in part on a computer, renders the volume image data to a two-dimensional display screen showing first, second, and third mutually orthogonal planes in the two-dimensional rendering. One or more operator instructions that identify a plurality of seed points on the rendered volume image are accepted. Two-dimensional coordinates of the identified seed points on the display screen are converted to three-dimensional seed-point coordinates relating to the first, second, and third mutually orthogonal planes a segmentation operation is performed on the volume image according to the converted three-dimensional seed-point coordinates. Segmentation results are displayed on the display screen, relative to the first, second, and third mutually orthogonal planes.

Abstract: A method for segmenting a feature of interest from a volume image acquires image data elements from the image of a subject. One or more boundary points along a boundary of the feature of interest are identified according to one or more geometric primitives with reference to the displayed view. A foreground seed curve is defined according to the one or more identified boundary points. A background field array that lies outside of, and is spaced from, the foreground seed curve by a predetermined distance, is defined. Segmentation is applied to the volume image according to foreground values obtained according to image data elements that are spatially bounded on or within the foreground seed curve and according to background field array values to create a segmented feature of interest.

Abstract: A method for rib suppression in a chest x-ray image detects and labels one or more ribs in a region of interest and detects rib edges of the one or more detected ribs. Cross rib profiles are generated along the detected ribs. The original x-ray image is conditioned according to at least one of the detected rib edge and cross rib profiles. The conditioned x-ray image can be stored, displayed, or transmitted.

Abstract: A method for 3-D cephalometric analysis acquires reconstructed volume image data from a computed tomographic scan of a patient's head. The acquired volume image data simultaneously displays from at least a first 2-D view and a second 2-D view. For an anatomical feature of the head, an operator instruction positions a reference mark corresponding to the feature on either the first or the second displayed 2-D view and the reference mark displays on each of the at least first and second displayed 2-D views. In at least the first and second displayed 2-D views, one or more connecting lines display between two or more of the positioned reference marks. One or more cephalometric parameters are derived according to the positioned reference marks, the derived parameters are displayed.

Abstract: A method for forming a panoramic image from a computed tomography image volume, acquires image data elements for one or more computed tomographic volume images of a subject, identifies a subset of the acquired computed tomographic images that contain one or more features of interest and defines, from the subset of the acquired computed tomographic images, a sub-volume having a curved shape that includes one or more of the contained features of interest. The curved shape is unfolded by defining a set of unfold lines wherein each unfold line extends at least between two curved surfaces of the curved shape sub-volume and re-aligning the image data elements within the curved shape sub-volume according to a re-alignment of the unfold lines. One or more views of the unfolded sub-volume are displayed.

Abstract: A method of generating a dissection curve between a first and a second object in a volume image. The method accesses volume image data of a subject as a set of image slices and identifies a region of the volume image data that includes at least the first and second objects. At least one starting point in the volume image data is defined for the dissection curve according to a geometric primitive entered by an operator. Successive dissection curve points are identified according to points of minimum intensity in successive image slices. The dissection curve that connects the identified plurality of successive dissection curve points is displayed.

Abstract: A method of providing a corrected reconstructed computed tomography image accesses image data for computed tomography images of a subject, identifying a subset of the computed tomography images that contain high density features. At least one high density feature is detected in each of the identified subset. The high density feature is classified and a compensation image is formed by distributing pixels representative of tissue over the classified high density feature. A difference sinogram is generated for each image in the identified subset of images by subtracting a first sinogram of the high density feature from a second sinogram of the original image. A resultant sinogram is generated for each image in the identified subset by adding a third sinogram generated according to the compensation image to the difference sinogram. The corrected reconstructed computed tomography image is formed according to the resultant sinogram generated for each image in the identified subset of images.

Abstract: A method for segmenting a feature of interest from a volume image acquires image data elements from the image of a subject. At least one view of the acquired volume is displayed. One or more boundary points along a boundary of the feature of interest are identified according to one or more geometric primitives defined by a user with reference to the displayed view. A foreground seed curve defined according to the one or more identified boundary points and a background seed curve encompassing and spaced apart from the foreground seed curve are formed. Segmentation is applied to the volume image according to foreground values that are spatially bounded within the foreground seed curve and according to background values that lie outside the background seed curve. An image of the segmented feature of interest is displayed.

Abstract: A method of automatic tooth segmentation, the method executed at least in part on a computer system acquires volume image data for either or both upper and lower jaw regions of a patient and identifies image content for a specified jaw from the acquired volume image data. For the specified jaw, the method estimates average tooth height for teeth within the specified jaw, finds a jaw arch region, detects one or more separation curves between teeth in the jaw arch region, defines an individual tooth sub volume according to the estimated average tooth height and the detected separation curves, segments at least one tooth from within the defined sub-volume, and displays the at least one segmented tooth.

Abstract: A method for segmenting an object in a volume image, executed at least in part on a computer, renders the volume image data to a two-dimensional display screen showing first, second, and third mutually orthogonal planes in the two-dimensional rendering. One or more operator instructions that identify a plurality of seed points on the rendered volume image are accepted. Two-dimensional coordinates of the identified seed points on the display screen are converted to three-dimensional seed-point coordinates relating to the first, second, and third mutually orthogonal planes a segmentation operation is performed on the volume image according to the converted three-dimensional seed-point coordinates. Segmentation results are displayed on the display screen, relative to the first, second, and third mutually orthogonal planes.