A blood flow field estimation apparatus is provided, including an estimation unit that uses a learned model obtained in advance by performing machine learning to learn a relationship between organ tissue three-dimensional structure data including image data of a plurality of organ cross-sectional images serving as cross-sectional images of an organ and having each pixel provided with two or more bit depths and image position information serving as information indicating a position of an image reflected on each of the organ cross-sectional images in the organ, and a blood flow field in the organ, and estimates the blood flow field in the organ of an estimation target, based on the organ tissue three-dimensional structure data of the organ of the estimation target, and an output unit that outputs an estimation result of the estimation unit.

The invention provides a fluid analysis apparatus, a method for operating a fluid analysis apparatus, and a fluid analysis program that perform display such that the tendency of a fluid flow in a blood vessel is easily checked. Route position information that is capable of identifying an order along a route of the anatomical structure is assigned to each position in the anatomical structure, using three-dimensional volume data in which each voxel has the information of a three-dimensional flow velocity vector indicating a flow velocity of a fluid in an anatomical structure. The three-dimensional flow velocity vector is selected such that the route position information of a position where the three-dimensional flow velocity vector is present is sequentially arranged from one point in the anatomical structure and a trajectory indicating the flow of the fluid is drawn so as to be visibly recognized.

The present disclosure relates to a system for generating a predefined electrical signal in an MR scanner for use in electrical stimulation of a subject during MRI or functional MRI of said subject, wherein said MR scanner is located inside a shielded MRI room. The system comprises a control unit to be located outside the MRI room for generating an electrical signal and an electrical to optical converter to be located outside the MRI room for converting said electrical signal to a corresponding optical signal. An optical transmitting element, such as an optical fiber, is used for transmitting the optical signal into the MRI room, and an optical to electrical converter is used for converting the optical signal to said predefined electrical signal for electrical stimulation of the subject during magnetic resonance imaging. The optical to electrical converter is configured for being located inside the MRI room and for operation during magnetic resonance imaging.

A system is provided for augmenting a three-dimensional (3D) model of a heart to indicate the tissue state. The system accesses a 3D model of a heart, accesses two-dimensional (2D) images of tissue state slices of the heart, and accesses source location information of an arrhythmia. The system augments the 3D model with an indication of a source location based on the source location information. For each of a plurality of the tissue state slices of the heart, the system augments a 3D model slice of the 3D model that corresponds to that tissue state slice with an indication of the tissue state of the heart represented by the tissue state information of that tissue state slice. The system then displays a representation of the 3D model that indicates the source location of the arrhythmia and the tissue state of the heart.

Methods, compositions and kits useful in the detection, assessment, diagnosis, prognosis and/or treatment of brain injuries, especially mild traumatic brain injury (mTBI) or concussion, are based upon detection of changes in levels of certain protein biomarkers in a subject undergoing testing, or upon detection of changes in levels of certain protein biomarkers in conjunction with neuroimaging analyses to detect changes in vascular or blood brain barrier (BBB) permeability in the brain, or to detect damage to fiber tracts in the brain, in which changes in biomarker levels correlate with detection of changes in BBB permeability or in brain fiber tract or white matter damage in a subject with brain injury such as mTBI or concussion.

A method for quantitatively estimating heat transfer energy parameters in an encephalon through discretization and numerical calculation comprises the steps of: acquiring composition data regarding a distribution of matter in the encephalon; acquiring cerebral temperature data regarding a temperature distribution in the encephalon; calculating a thermal conductivity distribution in the encephalon as a function of the composition data; calculating a distribution of conductive heat flows in the encephalon as a function of the cerebral temperature data and the thermal conductivity distribution using the “general heat conduction equation”.

A computing system (118) includes a computer readable storage medium (122) with computer executable instructions (124), including a biophysical simulator (126) and an electrocardiogram signal analyzer (128). The computing system further includes a processor (120) configured to execute the electrocardiogram signal analyzer determine myocardial infarction characteristics from an input electrocardiogram and to execute the biophysical simulator to simulate a fractional flow reserve or an instant wave-free ratio index from input cardiac image data and the determined myocardial infarction characteristics.

A method for performing magnetic resonance imaging on a subject comprises: injecting a contrast agent into a region of interest of the subject; applying a pulse sequence to the region of interest; collecting auxiliary data for the region of interest, the auxiliary data being related to one or more time-varying parameters of the subject within the region of interest; determining a temporal factor Φ from the auxiliary data; collecting imaging data for the region of interest, the imaging data being related to one or more spatially-varying parameters of the subject within the region of interest; determining a spatial factor Ur from the imaging data; modeling a multi-dimensional image sequence as I=UrΦ; and deriving at least a first metric and a second metric from the multi-dimensional image sequence I, the first metric and the second metric being associated with distinct perfusion-based imaging techniques.

Vasculature or parenchyma is imaged using upright MRI techniques, on patients who may have conditions such as congestive heart failure, or otherwise be healthy. When an individual is horizontal, venous drainage is minimized, causing the vessels to remain engorged, also referred to herein as vascular congestion. Vascular congestion results in an enlarging of the vessels and surrounding tissue causing the vessels to be more visible on MRIs. The decrease in vascular visibility in upright subjects is in part, due to an increase in venous drainage. Patients suffering from coronary and/or pulmonary deficiencies (e.g. CHF) experience decreased rates and degrees of venous drainage. In one embodiment, the present invention uses upright imaging to visualize these enlarged vessels.

Embodiments and aspects described herein provide methods and systems for determining pressure difference across a tube arising from fluid flow within the tube, comprising: obtaining three-dimensional time dependent fluid velocity data at a plurality of points along the tube; processing the three-dimensional time dependent fluid velocity data to determine: i) a flow rate (Q) of the fluid through the tube; ii) the kinetic energy (K) of the fluid flow through the tube; iii) an advective energy rate (A) of the fluid flow through the tube; and iv) a viscous dissipation rate (V) pertaining to the fluid flow; and calculating the pressure difference in dependence on all of the flow rate (Q), kinetic energy (K), advective energy rate (A), and viscous dissipation rate (V). Further embodiments are also described.