An illustrative method includes accessing, by a computing device, a model simulating light scattered by a simulated target, the model comprising a plurality of parameters. The method further includes generating, by the computing device, a set of possible histogram data using the model with a plurality of values for the parameters. The method further includes determining, by the computing device, a set of components that represent the set of possible histogram data, the set of components having a reduced dimensionality from the set of possible histogram data.

An unsupervised image segmentation method includes: performing a superpixel segmentation on an image containing a target object to acquire a plurality of superpixel sets, each superpixel set corresponding to a respective superpixel node; generating an undirected graph according to superpixel nodes; determining foreground superpixel nodes and background superpixel nodes in the undirected graph according to a first label set corresponding to the plurality of superpixel nodes; generating a minimization objective function according to the foreground superpixel nodes and the background superpixel nodes; segmenting the undirected graph according to the minimization objective function to acquire a foreground part and a background part and to generate a second label set; and performing an image segmentation on the image according to a comparison result of the first label set and the second label set.

A system and method comprising a computer system and database configured using artificial intelligence software for storing historical histograms derived from images of particular biological features of different patients. The stored histograms are each associated with a transfer function that can be used in a 3D model of the biological features to allow users of the model to better observe particular features of the model. The system will automatically determine a transfer function for a new scan(s) by deriving a current histogram of the new scan, comparing this current histogram with the historical histograms stored in the database, and selecting the histogram that is closest to the current histogram based on certain features. The transfer function associated with the closest histogram is then used to obtain a new transfer function for the current histogram for use in a 3D model of the new scan(s).

Noninvasive imaging biomarkers to predict cancer treatment response based on early measurements, which would spare non-responding patients from unnecessary side effects and costs of ineffective treatment. Tissue characterization, classification and/or discrimination method is provided to capture different patterns of tissue perfusions. Two or three-dimensional dynamic contrast enhanced ultrasound (DCE US) data of a contrast bolus perfused tissue are acquired or available. Parametric perfusion maps of contrast bolus tissue perfusion parameters representing the DCE US data are generated. For each of the generated parametric perfusion maps statistical parameters are extracted. These statistical parameters, which are based on underlying perfusion characteristics, are first order statistical parameters, second order statistical parameters, or a combination thereof. The method then further classifies and/or discriminates the perfusion maps of the tissue using the extracted statistical parameters.

An information handling system determines a frame rate of a frame or an image, and determines a type of an application based on a histogram analysis of the frame or the image analysis and on the frame rate. A hardware equalizer setting may also be applied for audio content based on the application type, wherein the hardware equalizer setting is from a pre-defined list of applications with corresponding hardware equalizer settings.

A computer vision method performed by a computing system includes: receiving an image; identifying a light intensity value for each pixel of a set of pixels of the image; defining a light intensity band formed by an upper light intensity threshold and a lower light intensity threshold based on a light intensity distribution of the light intensity values of the set of pixels; for each pixel of the set of pixels, identifying whether that pixel has a light intensity value that is within the light intensity band or outside of the intensity band; and generating a modified image by increasing a light intensity contrast between a first subset of pixels identified as having light intensity values within the light intensity band and a second subset of pixels identified as having light intensity values outside of the light intensity band.

The disclosure relates to stent detection and shadow detection in the context of intravascular data sets obtained using a probe such as, for example, and optical coherence tomography probe or an intravascular ultrasound probe.

An image recognition device involves successively extracting co-occurrence pairs in synchronization with a clock, setting a weighting for the portion connecting the input layer and the intermediate layer corresponding to the extracted co-occurrence pairs, and successively inputting a first vote to the input layer. Meanwhile, the intermediate layer adds and stores the successively inputted number of votes. By continuing this operation, a value the same as if a histogram were inputted to an input layer is achieved in the intermediate layer, without creating a histogram. In this way, the image recognition device of this embodiment can perform image recognition while avoiding the creation of a histogram, which consumes vast amounts of memory. As a result of this configuration, it is possible to save memory resources, simplify circuits, and improve calculation speed, and achieve an integrated circuit suitable to an image recognition device.

The present disclosure relates to a method and a device for recognizing hand gestures in real-time. A shape is given as an input in a form of a binary image. The shape contour is partitioned into radial and angular spaces by an Angular Radial Bin distribution including multiple concentric circles and angular space partitions in a way that multiple angular radial sections are created denoted Angular Radial Bins. The ARB distribution is angle tilted through its centre of mass multiple times and the same procedure is repeated in order to capture a shape descriptor from different angle perspectives. A shape descriptor is calculated for each of an angle tilted instance of the ARB distribution belonging to a sequence of angle tilted instances of the ARB distribution.

An optimal automatic mapping method between a real image and a thermal image in a body heat tester, and the body heat tester using the method. The real image from the real imaging camera has wider angle of view than the thermal image from the thermal imaging camera, to maximize the use of thermal imaging without omission of thermal imaging pixels in a thermal inspection device using an infrared imaging device. The body heat tester comprises a thermal imaging camera, a real imaging camera and a data processing unit. The data processing unit matches the thermal and real images, obtains the reconstructed real image matched with the thermal image by stretching or shortening the top, bottom, left, and right of the real image based on the thermal image, and detects the body heat (temperature) of the subject using the thermal image and the reconstructed real image.