An LED controller system includes an LED controller including an image frame buffer able to receive image data. A sensor processing module is used to receive and process sensor data and a decision module is used to determine actions taken in response to processed sensor data. An image creation module is used to create images to be sent to the image frame buffer of the LED controller.

A measurement task is selected, where the measurement task is associated with a transmission of an encoded signal transmitted via a plurality of data lines. The encoded signal is encoded using one or more of 3-Phase, N-Phase, or N-factorial low-voltage differential signaling (LVDS) where N is at least three (3). A repeating waveform is generated corresponding to the measurement task. The repeating waveform corresponding to the measurement task is then transmitted via the plurality of data lines.

Methods, systems, and apparatuses are described for determining deformation of gingiva. A three-dimensional (3D) digital model of an archform comprising a representation of gingiva and a tooth may be received. The 3D model may comprise a 3D mesh describing a surface of the gingiva, the tooth, and a contour between the gingiva and the tooth. A tooth-movement displacement may be applied to the vertices corresponding to the tooth in the 3D mesh and the vertices corresponding to the contour. A vertex-specific displacement may be determined for each of the vertices corresponding to the gingiva by solving a harmonic equation. The 3D digital model may be updated.

A motion analysis system and motion tracking system for capturing moved or moving objects that are thermally distinct from their surroundings. The system has a camera group with at least one thermographic camera, a calibration unit, a synchronization unit, a segmentation unit, a reconstruction unit, a projection unit and an identification unit. Such a system advantageously allows a thermally aided segmentation both of the 2D thermogragraphic images and of any 2D video images, specifically irrespective of the ambient conditions of an object to be analyzed and/or to be tracked and without requiring marker elements attached to the object.

Example embodiments associated with characterizing a sample using NMR fingerprinting are described. One example NMR apparatus includes an NMR logic that repetitively and variably samples a (k, t, E) space associated with an object to acquire a set of NMR signals that are associated with different points in the (k, t, E) space. Sampling is performed with t and/or E varying in a non-constant way. The NMR apparatus may also include a signal logic that produces an NMR signal evolution from the NMR signals and a characterization logic that characterizes a tissue in the object as a result of comparing acquired signals to reference signals. Example embodiments facilitate distinguishing diseased tissue from healthy tissue based on tissue component fractions identified using the NMR fingerprinting.

An image analysis device may include a memory storing learning data for executing image analysis, and may obtain cell image data representing a cell image including a plurality of cell objects, sequentially identify plural pieces of partial image data from the cell image data, sequentially execute a center determination process on each of the plural pieces of partial image data, classify at least one cell corresponding to at least one cell object among a plurality of cell objects by using results of the center determination process on the plural pieces of partial image data and classification data included in learning data, and output a classification result.

A LED controller includes a power distribution module and an interface to an external data bus. An image frame buffer is connected to the interface to receive image data. A separate logic module is connected to the interface and configured to modify image frame buffer output signals sent to an LED pixel array connected to the image frame buffer. The LED pixel array can project light according to a pattern and intensity defined at least in part by the image held in the image frame buffer.

Methods, systems, and apparatuses are described for determining deformation of gingiva. A three-dimensional (3D) digital model of an archform comprising a representation of gingiva and a tooth may be received. The 3D model may comprise a 3D mesh describing a surface of the gingiva, the tooth, and a contour between the gingiva and the tooth. A tooth-movement displacement may be applied to the vertices corresponding to the tooth in the 3D mesh and the vertices corresponding to the contour. A vertex-specific displacement may be determined for each of the vertices corresponding to the gingiva by solving a harmonic equation. The 3D digital model may be updated.

Example apparatus and methods improve magnetic resonance fingerprinting (MRF) by performing MRF with optimized spatial encoding, parallel imaging, and utilization of field inhomogeneities. Multi-echo radial trajectories and spiral trajectories may acquire data according to sampling schemes based on models of charge distribution on a sphere. Non-uniform sampling schemes may account for differences in detector coil performance. Field inhomogeneities provide spatial information that enhances the spatial separation of an MRF signal and facilitates unaliasing pixels. The field inhomogeneity may be manipulated. An MRF pulse sequence may include frequency selective RF pulses that are determined by the field inhomogeneities. Inhomogeneities combined with selective RF pulses result in higher acquisition efficiency.

Methods, systems, and apparatuses are described for determining deformation of gingiva. A three-dimensional (3D) digital model of an archform comprising a representation of gingiva and at least one tooth may be received. The 3D model may comprise a 3D mesh describing a surface of the gingiva and the at least one tooth. The 3D mesh may be separated into a gingiva mesh and a tooth mesh. A set of shared vertices in the gingiva mesh and the tooth mesh may be identified. A tooth-movement displacement may be applied to the vertices in the tooth mesh and the vertices in the set of shared vertices. A vertex-specific displacement may be determined for the remaining vertices in the gingiva mesh by solving a harmonic equation. The 3D model may be updated.