Ricoh Company, Ltd.

Marvell International Limited

Krishna Prasad Agara Venkatesha Rao

Srinidhi Srinivasa

Vipin Namboodiri

Kathrin Berkner

Noah Denis Bedard

Lingfei Meng

Go Maruyama

A cluster-based approach and template-based approach are combined to segment brain matter from a three-dimensional MRI image of voxels. The morphological information captured by the template-based approach may be used to refine the segmentation produced by the cluster-based approach. Conversely, the 'similarity' information captured by the cluster-based approach may be used to refine the segmentation produced by the template-based approach.

Brain segmentation using clustering and templates

In one aspect, a computer-implemented method corrects a multi-sphere head model used in dipole localization for a set of magnetic field sensors (MEG sensors) by replacing ghost spheres with replacement spheres that are not ghost spheres. One type of ghost sphere completely encloses the brain volume but is so large that a center of the sphere is outside the brain volume. Another type of ghost sphere lies entirely outside the brain volume. Various approaches for correcting ghost spheres are disclosed.

Multi-sphere head model for dipole localization

Multi-sphere head model for dipole localization without ghost spheres

A system assists users in time and frequency analysis of magnetoencephalography (MEG) signals. In one aspect, a system includes an analysis module, a configuration module and a user interface. The analysis module performs a time and frequency analysis of the MEG signal, for example a short time Fourier transform (STFT) or a continuous wavelet transform (CWT) analysis. The analysis is parameterized by a parameter set that affects the time and frequency resolution of the analysis, for example window size and overlap size for STFT or center frequency and decay parameter for CWT. The configuration module automatically determines or assists the user to determine correct values for the parameter set.

Intelligent parameterization of time-frequency analysis of encephalography signals

A surface model is generated from a three-dimensional volume model of a person's head. The person's head is modelled as a three-dimensional volume model of loss values (i.e., absorption values). Wave vectors are launched towards the volume model. Each wave vector is characterized by a wavelength and a capture direction (direction of propagation). The launched wave vectors are absorbed by the volume and the point at which they are absorbed (referred to as the intersection point) is determined. The surface model of the person's head is generated from the intersection points of the wave vectors.

Volume surface generator using variable wave vectors

Volume surface generator using wave vectors

An application delivery controller for improving remote healthcare services is disclosed. The application delivery controller may be configured to provide improved service routing and security. In some implementations, the application delivery controller may receive a service request from a client device. The application delivery controller may determine routing parameters based on a requested service of the service request, authenticate access from the client device based on the requested service, a security zone of the requested service, and a token, and route the requested service to the client device based on the routing parameters and the authenticated access.

Application delivery controller

The location of the optical axis of a plenoptic imaging system is determined. In one approach, the plenoptic image is noise filtered, down-sampled, low-pass filtered, and again noise filtered. Slices through this image that have the highest power are used to determine the location of the optical axis. Once the location of the optical axis is determined, corrections for aberrations such as distortion can be applied.

Optical center detection in plenoptic imaging systems

One aspect determines centroids of a plenoptic image, which correspond to the center view of the plenoptic image. A search band spanning a range of different values along a search direction (e.g., range of &#x394;y) is determined. Multiple slices of the plenoptic image are taken at different values of the search coordinate (i.e., different y values). Because the plenoptic image has a periodic structure imposed by the periodicity of the microlens array, each slice will have a strong frequency component at this fundamental frequency. A slice corresponding to the centroid location (i.e., value of y at the centroid) is selected based on analysis of these frequency components. In one approach, the slice with the weakest component at this fundamental frequency is selected as the centroid. A similar approach can be performed in the orthogonal direction to obtain the two-dimensional coordinates of the centroids.

Automatic centroid determination of microlens arrays in plenoptic imaging systems

A multimode fundus camera enables three-dimensional and/or spectral/polarization imaging of the interior of the eye to assist in improved diagnosis.

Simultaneous capture of filtered images of the eye

Calibration for a plenoptic imaging system. The plenoptic imaging system includes a detector array that is subdivided into superpixels. A plenoptic image captured by the detector array of the plenoptic imaging system is accessed. For a row of superpixels, a slice is selected through the row, the selected slice having a Fourier transform with a stronger fundamental component compared to other slices through the row. A pitch of the row of superpixels is determined based on a frequency of the fundamental component of the selected slice. A rotation of the row of superpixels is determined based on a rotation of the selected slice.

Calibration of plenoptic imaging systems using fourier transform

A light field imaging system captures different images provide views that are shifted by sub-pixel amounts relative to one another. These views can be combined to produce a higher resolution digital image of the object.

Automatic adjustment of light field imaging systems for resolution enhancement

Enhancing spatial resolution of images from light field imaging systems using sub-pixel disparity

Embodiments of the present disclosure provide a method that comprises receiving a first stream of video frames at a first frame rate and generating a second stream of video frames at a second frame rate. The method also comprises interpolating between a pair of adjacent video frames of the first stream of video frames to produce a first number of interpolated intermediate video frames in a particular sequence of the intermediate video frames. The method further comprises duplicating at least one of the adjacent video frames of the pair of adjacent video frames to produce a second number of duplicated intermediate video frames in the particular sequence of the intermediate video frames. The method further comprises, in response to a change in observed interpolation quality, dynamically changing the first number of interpolated intermediate video frames and the second number of duplicated intermediate video frames.

Interpolated video error concealment

Embodiments of the present disclosure provide a method that comprises receiving a motion-interpolated pixel of an interpolated video frame, wherein the motion-interpolated pixel is based at least in part on a pair of anchor video frames. The method further comprises blending the motion-interpolated pixel with one or more anchor pixels of the pair of anchor video frames to produce a temporally filtered pixel, wherein the one or more anchor pixels correspond in position to the motion-interpolated pixel of the interpolated video frame. The method also comprises substituting the temporally filtered pixel for the motion-interpolated pixel in the interpolated video frame.

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Bengaluru, India

Krishna Prasad Agara Venkatesha Rao