An information processing apparatus according to an embodiment includes a processing circuit. The processing circuit acquires a measurement field corresponding to a spatial distribution of a predetermined physical quantity in a subject of measurement. The processing circuit calculates an unknown quantity in the subject of measurement based on a first equation between the measurement field and the unknown quantity having spatial dependence, and on the acquired measurement field. The first equation is one that is acquired based on a second equation expressing a dual field divergence of which can be expressed using the measurement field, by using the measurement field and the unknown quantity, and on the Helmholtz decomposition of the dual field.

Systems and methods for predicting and treating relapses for neurological conditions in accordance with embodiments of the invention are illustrated. One embodiment includes a method for predicting and treating a clinical neurological condition relapse. The method includes steps for selecting a threshold heart rate variability value for a patient suffering from a clinical neurological condition, monitoring, using a cardiac monitor, the heart rate variability of the patient over time, providing an indicator that a relapse is imminent when the heart rate variability of the patient falls below the threshold heart rate variability value, and treating the patient using a transcranial magnetic stimulation device by applying an accelerated theta burst stimulation protocol where the transcranial magnetic stimulation target is the left prefrontal dorsolateral cortex.

Methods, systems, and apparatus for signal artifact detection and reduction are provided. The signal artifact may comprise an interference between an electroencephalography (EEG) signal and a magnetic resonance imaging (MRI) signal arising out of simultaneous EEG and MRI treatment.

A system for selection and configuration of an automated robotic process includes a media input module structured to receive at least one functional media, a media analysis module structured to analyze the at least one functional media and identify an action parameter; and a solution selection module structured to select at least one component of an AI solution for use in an automated robotic process, wherein the selection is based, at least in part, on the action parameter.

Systems and methods for mapping neuronal circuitry in accordance with embodiments of the invention are illustrated. One embodiment includes a method for generating a neuronal shape graph, including obtaining functional brain imaging data from an imaging device, where the functional brain imaging data includes a time-series of voxels describing neuronal activation over time in a patient's brain, lowering the dimensionality of the functional brain imaging data to a set of points, where each point represents the brain state at a particular time in the timeseries, binning the points into a plurality of bins, clustering the binned points, and generating a shape graph from the clustered points, where nodes in the shape graph represent a brain state and edges between the nodes represent transitions between brain states.

A system includes a machine readable storage medium storing instructions and a processor to execute the instructions. The processor executes the instructions to receive radial k-space magnetic resonance imaging (MRI) data of a patient and determine a series of dipole sources via direct dipole decomposition of the radial k-space MRI data. The processor executes the instructions to identify an activation within the patient based on the series of dipole sources.

A method of quantitatively evaluating a cognitive impairment and its future change from a medical image of an individual's brain, the method comprising scanning the individual's brain with a scanning device so as to acquire at least one medical brain image; processing the medical brain image to obtain at least one feature of the image; using a pre-established prediction model to determine a condition of the cognitive impairment and predict its future change based on the at least one feature obtained.

A computing device having a first processor configured to receive three-dimensional imaging data acquired by an imaging system, the three-dimensional imaging data being from ahead of a subject. The first processor can be configured to determine vascular structures from the three-dimensional imaging data, generate a three-dimensional model of the head of the subject from the three-dimensional imaging data, the three-dimensional model of the head including a three-dimensional model of the vascular structures and a three-dimensional model of a portion of a frontal horn of the subject, determine an entry point on the three-dimensional model of the head of the subject, determine a plurality of trajectories, each trajectory intersecting the three-dimensional model of the portion of the frontal horn and does not intersect the three-dimensional model of the vascular structures, and each trajectory is linear, and select a final trajectory from the plurality of trajectories.

Techniques are disclosed for measuring the corpus callosum volume of a fetus using magnetic resonance imaging. A scanogram of a fetus is acquired, and a detection area is determined using the corpus callosum position of the fetus in the scanogram. Magnetic resonance scanning is performed on the detection area to obtain a diffusion weighted image, with a gradient direction that is orthogonal or normal to an extending direction of fiber bundles of the corpus callosum. A fetal head image is cropped in the diffusion weighted image, and a predetermined threshold is applied to obtain an image including pixels having a brightness value that is greater than the threshold. Image processing is performed on the binarized image, with the largest region therein being identified as the corpus callosum, and the sum of voxel dimensions associated with the signal of the largest region being calculated as the corpus callosum volume.

A measurement apparatus includes a light source, a sensor including light detection cells including a first light detection cell and a second light detection cell, and an electronic circuit. The circuit causes the light source to emit a light pulse, causes the first light detection cell to detect a reflected light pulse from a target in an exposure period including at least part of a period from when an intensity of the reflected light pulse starts increasing to when it starts falling and generate a first signal, causes the second light detection cell to detect the reflected light pulse in an exposure period including at least part of a trailing period from when the intensity of the reflected light pulse starts falling to when it stops falling and generate a second signal. The circuit generates, based on the first and second signals, data representing states of the target.