Provided is a technology capable of simply and efficiently obtaining a contrast of a speckle pattern as a prerequisite for measuring a fluid velocity.

The present technology provides an information processing apparatus including: a luminance integrator that integrates a luminance of a plurality of speckle images obtained by an imaging element by a plurality of times of imaging of scattered light obtained from an imaging target to which coherent light is emitted; and a contrast calculation unit that calculates a contrast of a speckle pattern on the basis of a speckle integrated image integrated by the luminance integrator.

A system and method for automated contrast arrival detection in temporally phased images or datasets of tissues effectively determines contrast arrival in regions that are substantially free of arteries. A plurality of tissue voxels in a plurality of temporally phased images are identified as a function of voxel enhancement characteristics associated with discrete tissue voxels. A processor/process computes average enhancement characteristics from the plurality of identified tissue voxels. The average enhancement characteristics are compared with predetermined average enhancement characteristics associated with contrast media arrival phases. Contrast media arrival phases in the temporally phased images are provided based on the comparison.

The invention relates to a method, an image processor (26) and a medical observation device (1), such as a microscope or endoscope, for observing an object (4) containing a bolus of at least one fluorophore (12). The object (4) is preferably live tissue comprising several types (16, 18, 20) of tissue. According to the method, a set (34) of component signals (36) is provided. Each component signal (36) represents a fluorescence intensity development of the fluorophore (12) over time in a different type of tissue. A time series (8) of input frames (10) is accessed, one input frame (10) after the other. The input frames (10) represent electronically coded still images of the object (4) at subsequent time. Each input frame (10) contains at least one observation area (22) comprising at least one pixel (23). In the observation area (22) of the current input frame (10) of the time series (8), a fluorescent light intensity (I) is determined over at least one fluorescence emission wavelength (15) of the fluorophore (12). This fluorescent light intensity (I.sub.1) is joined with the fluorescence light intensities (I.sub.n) of the observation area (22) of preceding input frames (10) of the time series (8) to generate a time sequence (40) of fluorescent light intensities (I.sub.1, I.sub.n) of the observation area (22). This time sequence (40) is decomposed on in a preferably linear combination (72) of at least some of the component signals (36) of the set (34). A new set (34) of component signals (36) is provided which includes only those component signals (36) which are present in the combination (72). An output frame (46) is generated, in which the observation area (22) is assigned a color from a color space depending on the combination (72) of component signals (36).

According to embodiment, an image processing apparatus comprising a specifying unit and a display controller. The specifying unit that specifies an acquisition position of an indicator relating to blood flow on a blood vessel-containing image collected by a medical image diagnostic apparatus. The display controller that displays the acquisition position on the blood vessel-containing image and displays the indicator on a display unit in association with the acquisition position.

A vascular assessment apparatus is disclosed. The apparatus is configured to receive a stenotic model having measurements of a coronary vessel tree of a subject, the stenotic model created from a set of medical images recorded before the subject underwent a stent procedure. The apparatus is also configured to receive a post-medical image of the coronary vessel tree of the subject after the stent has been placed into the coronary vessel tree and identify vascular features within the post medical image that correspond to vascular features that are provided among the set of medical images. The apparatus is further configured to modify geometrical information for the corresponding vascular features in the stenotic model to create an updated stenotic model from the identified vascular features of the post medical image and calculate an index indicative of vascular function, based, at least in part, on the updated stenotic model.

A fuel injection pump (1) for a diesel engine (30), including: a control rack (20) an in a rack chamber (5) formed between a pump head (3) and a pump housing (2), and configured to adjust a fuel injection amount; a transmission shaft (49) rotatably supported by a transmission shaft hole (2C) formed in the pump housing; and a lubricating oil passage (2D) formed in the pump housing, and configured to pressure-feed lubricating oil between the transmission shaft and the transmission shaft hole. The transmission shaft has an oil passage (40) therein through which passage the lubricating oil pressure-fed to the lubricating oil passage partially passes, a first opening of the oil passage is communicated with the lubricating oil passage, and a second opening (42A) of the oil passage is formed on the outer circumferential surface of an upper portion of the transmission shaft, nearby the control rack.

Disclosed is a method and an apparatus for quantifying vascular fluid motions from digital subtraction angiography (DSA) images, comprising: calculating an optical flow field between two temporal consecutive DSA images; and estimating a displacement of blood or tissue between the two temporal consecutive DSA images from the calculated optical flow field, wherein the optical flow field is calculated by solving a minimization problem of a CLG energy function, wherein the CLG energy function combines the temporally extended variant of Horn-Schunck approach with Lucas-Kanade approach non-linearly in spatiotemporal approach. The present disclosure provides a new optical flow solution significantly reducing the computation cost with a high robustness for quantifying vascular fluid motions from DSA.

Disclosed are a method and an apparatus for quantifying vascular fluid motions from digital subtraction angiography (DSA) images, comprising: calculating an optical flow field between two temporal consecutive DSA images; and estimating a displacement of blood or tissue between the two temporal consecutive DSA images from the calculated optical flow field, wherein the optical flow field is calculated by solving a minimization problem of a CLG energy function, wherein the CLG energy function combines the temporally extended variant of Horn-Schunck approach with Lucas-Kanade approach non-linearly in spatiotemporal approach. The present disclosure provides a new optical flow solution significantly reducing the computation cost with a high robustness for quantifying vascular fluid motions from DSA.

An embodiment includes analyzing a body part perfused with a contrast agent, which has been pre-administered as a bolus to circulate through the body-part with at least a first passage during an analysis interval. The analyzing includes providing at least one input signal indicative of a response to an interrogation signal of a corresponding location of the body part during the analysis interval, and fitting each input signal over the analysis interval by an instance of a combined bolus function of time, based on a combination of a first simple bolus function of time modeling the first passage of the contrast agent and at least one second simple bolus function of time each one modeling a corresponding second passage of the contrast agent.

A system and method are provided for generating time resolved series of angiographic volume data having flow information. The system and method are configured to receive angiographic volume data acquired from a subject having received a dose of a contrast agent using an imaging system and process the angiographic volume data to generate angiographic volume images. The angiographic volume data is processed to derive flow information by determining a distance between two points along a vessel in the angiographic volume images and determining a phase at each of the two points along the vessel in the angiographic volume images. A flow direction or a velocity of flow within the vessel is determined using the distance between the two points along the vessel and the phase at each of the two points along the vessel.