An apparatus includes: a processor configured for obtaining a first image that corresponds with a first multi-leaf collimator (MLC) configuration, wherein the first image is generated when the MLC is stationary, obtaining a second image that corresponds with a second MLC configuration, wherein the second image is generated when the MLC and/or another component of a radiation machine is being operated to track a motion, and performing an analysis based at least in part on the first image and the second image to obtain a result; and a non-transitory medium for storing the result.

A biological information detection apparatus for measuring a SpO.sub.2 without contact from a distant position includes a camera that acquires an image with visible and infrared light, a first wavelength fluctuation detection section detects a temporal variation of a wavelength of an image with the visible light to generate a first wavelength difference data signal, a first amplitude detection section detects an amplitude of the first wavelength difference data signal, a second wavelength fluctuation detection section detects a temporal variation of a wavelength of an image with the infrared light to generate a second wavelength difference data signal, a second amplitude detection section detects an amplitude of the second wavelength difference data signal, a ratio calculation section calculates a ratio between the amplitudes of the first and second wavelength difference data signals, and an oxygen saturation concentration calculation section calculates an oxygen saturation concentration based on the calculated amplitude ratio.

The invention provides for a medical imaging system (100, 300, 500) comprising a processor (104). Machine executable instructions cause the processor to: receive (200) magnetic resonance data (120) comprising discrete data portions (612) that are rotated in k-space; bin (202) the discrete data portions into predetermined motion bins (122) using a motion signal value; reconstruct (204) a reference image (124) for each of the predetermined motion bins; construct (206) a motion transform (126) between the reference images; bin (208) a chosen group (610) of the discrete data portions into a chosen time bin (128). Generate an enhanced image (130) for the chosen time bin using the chosen group of the discrete data portions and the motion transform of each of the chosen group to correct the discrete data portions.

An analysis device configured to analyze an attribute of a correlation between responses with respect to a stimulus to a first subcellular component that is a subcellular component of a cell and a second subcellular component different from the first subcellular component, the analysis device including an attribute analysis unit that analyzes the attribute of the correlation between the first subcellular component and the second subcellular component based on a first change in a feature value of the second subcellular component with respect to the stimulus in a state a function of the first subcellular component is suppressed and a second change in a feature value of the second subcellular component with respect to the stimulus in a state the function of the first subcellular component is not suppressed.

A dynamic analysis system includes a hardware processor and an output device. The hardware processor obtains a cycle of temporal change in a feature amount relevant to a function to be diagnosed from each of dynamic images obtained by imaging of a dynamic state of a living body with radiation. The hardware processor further adjusts the obtained cycle, thereby generating a plurality of cycle-adjusted data having cycles of the temporal change in the feature amount being equal to one another. The hardware processor further generates difference information at each phase in the plurality of cycle-adjusted data. The output device outputs the difference information.

The present application relates to a method for acquiring maximum principal strain or a maximum principal stress status of a vessel wall. The method includes: acquiring first vessel data of a first time phase corresponding to a vessel; acquiring second vessel data of a second time phase corresponding to the vessel; generating, based on the first vessel data, a first vessel model relating to the first time phase, generating a second vessel model relating to the second time phase based on the second vessel data, determining a region of interest in the first vessel model; determining the corresponding region of interest in the second vessel model; determining a reference point in the region of interest of the first vessel model; determining the corresponding reference point in the region of interest of the second vessel model; determining a displacement of the reference point from the first vessel model to the second vessel model; and determining a maximum principal strain or a maximum principal stress at the reference point based on the displacement of the reference point.

A method for monitoring the position of a patient's teeth includes the following steps: a) modeling a target position of the teeth in the form of a target model; b) after a time interval, modeling an updated position of the teeth in the form of an updated model; and c) comparing the target and updated models. The updated model is created by the patient himself or by one of his relations.

Methods that implement image-guided tissue analysis, MRI-based computational modeling, and imaging informatics to analyze the diversity and dynamics of molecularly-distinct subpopulations and the evolving competitive landscapes in human glioblastoma multiforme (GBM) are provided. Machine learning models are constructed based on multiparametric MRI data and molecular data (e.g., CNV, exome, gene expression). Models can also be built based on specific biological factors, such as sex and age. Inputting MRI data into the trained predictive models generates maps that depict spatial patterns of molecular markers, which can be used to quantify and co-localize regions molecularly distinct subpopulations in tumors and other regions, such as the non-enhancing parenchyma, or brain around tumor (BAT) regions.

Systems and methods for generating high resolution 3D images of the entire human skin comprising at least two sets of cameras, a first set being sensitive to UV light while the second set being sensitive to visible frequencies of light, wherein subsets of each camera set are focused at different focal distances; wherein the system provides a rotatable structure wherein the two sets of cameras are mounted adjacent to the source of light; wherein the rotatable structure is engaged to a program that can define the point of rotation, so as to allow for a reproducible mechanism to take images along the path of rotation.

A location identification system analyzes information received corresponding to a device detected in a room of a patient. On detecting a location identification of the device, the system assigns the device to the location corresponding to the location identification. In embodiments, the system retrieves patient and care team information for the location. The location and patient and care team information may be communicated to a central video monitoring system.