Abstract: Context-specific user interfaces for use with a portable multifunction device are disclosed. The methods described herein for context-specific user interfaces provide indications of time and, optionally, a variety of additional information. Further disclosed are non-transitory computer-readable storage media, systems, and devices configured to perform the methods described herein.

Abstract: Context-specific user interfaces for use with a portable multifunction device are disclosed. The methods described herein for context-specific user interfaces provide indications of time and, optionally, a variety of additional information. Further disclosed are non-transitory computer-readable storage media, systems, and devices configured to perform the methods described herein.

Abstract: A method for characterizing a bone joint of a patient, the method executed at least in part by a computer, accesses 3-D volume image content that includes the bone joint and automatically segments the bone joint volume image content from background content to define at least a first bone surface and a second bone surface that is spaced apart from and faces the first bone surface. One or more distances between at least a first point on the first bone surface and one or more points on the second bone surfaces are computed. The method displays at least the first and second bone surfaces, wherein the display appearance is conditioned by the one or more computed distances. The method displays, stores, or transmits data relating to the one or more computed distances.

Abstract: Context-specific user interfaces for use with a portable multifunction device are disclosed. The methods described herein for context-specific user interfaces provide indications of time and, optionally, a variety of additional information. Further disclosed are non-transitory computer-readable storage media, systems, and devices configured to perform the methods described herein.

Abstract: A method for reporting bone mineral density values for a patient, the method executed at least in part by a computer includes accessing a 3-D volume image that includes at least bone content and background. A 3-D bone region is automatically segmented from the background to generate a 3-D bone volume image having a plurality of voxels. One or more bone mineral density values are computed from voxel values of the 3-D bone volume image. A 3-D mapping of the one or more computed bone mineral density values is generated and displayed, stored, or transmitted.

Abstract: Method and/or apparatus embodiments can process volume image data of a subject. An exemplary method includes obtaining a first group of two-dimensional radiographic images of the subject, wherein each of the images is obtained with a detector and a radiation source at a different scan angle. The method arranges image data from the first group of images in an image stack so that corresponding pixel data from the detector is in register for each of the images in the image stack. Pixels that represent metal objects are segmented from the image stack and data replaced for at least some of the segmented pixels to generate a second group of modified two-dimensional radiographic images. The second group of images is combined with the first group to generate a three-dimensional volume image according to the combined images and an image slice from the three-dimensional volume image is displayed.

Abstract: A method for 3-D interactive examination of a subject tooth, executed at least in part by a computer, obtains volume image data containing at least the subject tooth and background content adjacent to the subject tooth and displays a first image from the volume data that shows at least the subject tooth and the background content. A portion of the background content in the first image is identified according to a first operator instruction. Tooth content for at least the subject tooth in the first image is identified according to a second operator instruction. At least the subject tooth is segmented from within the volume data according to the first and second operator instructions. The segmented subject tooth is then displayed.

Abstract: A method for analyzing a subject tooth. The method includes obtaining volume image data including at least the subject tooth and segments the subject tooth from within the volume data according to one or more operator instructions. An index is generated that is indicative of a suspected fracture or lesion identified for the segmented subject tooth. The subject tooth is displayed with the suspected fracture or lesion highlighted. The generated index also displays.

Abstract: A method for noise suppression in a 3-D volume image, executed at least in part on a logic processor, obtains the 3-D volume image, applies diffusion to the volume image according to a parameter that relates to image scale and is specified in an operator instruction, and displays the volume image modified according to the applied diffusion.

Abstract: A method for creating and sending customized cards to members on a list can include steps for designing a first card, creating a member list and dividing the member list into at least two groups. The first card can initially be associated with all members included in the member list. A second card can be designed and can be based, at least in part, on the first card. The second card can be associated with at least one member group. A data file can be created that can include the first and second card designs and association information regarding the card designs and the member groups.

Abstract: A method for suppressing noise in a diagnostic 3-D image, executed at least in part on a logic processor, captures, at each of a number of projection angles, 2-D image projection data, wherein each 2-D image projection has a central pixel and arranges the 2-D image projection data to form a 3-D data set. Each of the 2-D image projections is processed by performing a diffusion filtering process that obtains a homogeneity value for the 3-D data set, generates a diffusion conductance function according to an intensity gradient between adjacent digital image elements, and applies the diffusion filtering process to digital image elements according to the obtained homogeneity value, the generated diffusion conductance function, and a weighting value that relates to the distance of each pixel in the projection from the central pixel. The diagnostic 3-D image is reconstructed from the processed 2-D image projections.