Data processing systems (DPS) and related methods for nuclear medicine imaging. At an input interface (IN), first projection data (λ), or a first image (V) reconstructable from the first projection data, is received. The first projection data is associated with a first waiting period (ΔT*). The first waiting period indicates the time period from administration of a tracer agent to a start of acquisition by a nuclear medicine imaging apparatus (IA) of the projection date. A trained machine learning module (MLM) estimates, based on the first projection data (λ) or on the first image (V), a second projection data (λ′) or a second image (V′) associable with a second waiting period (ΔT), longer than the first waiting period (ΔT*). Nuclear imaging can thus be conducted quicker. Similar machine learning based data processing systems and related methods are also envisaged to reduce acquisition time periods or the time it takes to reconstruct imagery.

Systems and methods for planning and performing image free implant revision surgery are discussed. For example, a method for generating a revision plan can include collecting pre-defined parameters characterizing a target bone, generating a 3D model, collecting a plurality of surface points, and generating a reshaped 3D model. Generating the 3D model of the target bone can be based on a first portion of the pre-defined parameters. Generating the reshaped 3D model can be done based on the plurality of surface points collected from a portion of the surface of the target bone.

The present disclosure refers to a computer-implemented training system for user-interactive training of a plurality of in-vitro diagnostic (IVD) methods performable in an IVD laboratory system, comprising: one or more data processors; a memory device connected to the one or more data processors; a user interface provided with an output device having a display device and an input device configured to receive user input; and one or more software applications running on the one or more data processors and having a plurality of application modules. The plurality of application modules is further configured to control, in response to receiving user input, output of a plurality of views of the IVD laboratory system through the display device according to view output control data indicative of view parameters assigned to a view output mode from a plurality of view output modes; receive a training mode selection user input indicative of a user selection for an IVD method to be trained from the plurality of methods having an assigned view output mode of the plurality of view output modes.

Systems and methods are provided for scanning a dental impression to obtain a digital model of a patient's dentition as an input to computer aided design (CAD) and computer aided manufacturing (CAM) methods for producing dental prostheses.

Various methods and systems are provided for automatically classifying a plurality of image slices using body region bounding boxes identified from a localizer image. In one embodiment, a localizer image may be mapped to a plurality of bounding boxes, corresponding to a plurality of body regions, using a trained machine learning model. Coordinates of the plurality of bounding boxes may be used to determine body region boundaries, such that the body regions are non-intersecting and coherent. The body regions identified in the localizer image may then be correlated to image slice ranges, and image slices within each image slice range may be labeled as belonging to the corresponding body region.

A site specifying device, includes a memory; and a processor coupled to the memory and the processor configured to: store three-dimensional model data indicating a three-dimensional model of an object, display the three-dimensional model based on the three-dimensional model data, and select from the three-dimensional model a site in a range of a depth specified toward an inner side of the three-dimensional model from a region surrounded by a closed curve on a surface of the three-dimensional model according to an input of the closed curve to the surface of the displayed three-dimensional model and an input to specify the depth from the surface of the three-dimensional model.

In general, an X-ray imaging apparatus according to one embodiment includes an X-ray tube, an X-ray detector, and processing circuitry. The processing circuitry is configured to obtain correction-target data that includes component deterioration resulting from a transient response of the X-ray detector, and to output, based on the obtained correction-target and a model that outputs data in which component deterioration resulting from a transient response is reduced based on an input of data that includes component deterioration resulting from a transient response, corrected data in which the component deterioration resulting from the transient response of the X-ray detector is reduced.

Embodiments of the present disclosure provide a software program that displays both a volume as images and segmentation results as surface models in 3D. Multiple 2D slices are extracted from the 3D volume. The 2D slices may be interactively rotated by the user to best follow an oblique structure. The 2D slices can “cut” the surface models from the segmentation so that only half of the models are displayed. The border curves resulting from the cuts are displayed in the 2D slices. The user may click a point on the surface model to designate a landmark point. The corresponding location of the point is highlighted in the 2D slices. A 2D slice can be reoriented such that the line lies in the slice. The user can then further evaluate or refine the landmark points based on both surface and image information.

The invention provides, in some aspects, a system for implementing a rule derived basis to display image sets. In various embodiments of the invention, the selection of the images to be displayed, the layout of the images, as well as the rendering parameters and styles can be determined using a rule derived basis. In an embodiment of the present invention, the user is presented with images displayed based on their preferences without having to first manually adjust parameters.

The disclosure relates to a system and method for image reconstruction. The method may include the steps of: obtaining raw data corresponding to radiation rays within a volume, determining a radiation ray passing a plurality of voxels, grouping the voxels into a plurality of subsets such that at least some subset of voxels are sequentially loaded into a memory, and performing a calculation relating to the sequentially loaded voxels. The radiation ray may be determined based on the raw data. The calculation may be performed by a plurality of processing threads in a parallel hardware architecture. A processing thread may correspond to a subset of voxels.