Methods and systems are provided for extracting cardiac frequency angiographic phenomena for an unconstrained vascular object from an angiographic study. In one example, a computer may obtain a series of angiographic image frames obtained at a rate faster than cardiac frequency. Each image frame may comprise a plurality of pixels, and each pixel may have a corresponding intensity. The computer may apply an optical flow technique to the angiographic image frames to generate a plurality of paths corresponding to a displacement of respective pixels from image frame to image frame. The computer may further generate a spatiotemporal reconstruction of cardiac frequency angiographic phenomena based on the plurality of paths and the corresponding intensities associated with respective pixels of the paths, and output for display the spatiotemporal reconstruction of cardiac frequency angiographic phenomena in one or more images.

A mechanism is provided in a data processing system for refining lesion contours with combined active contour and inpainting. The mechanism receives an initial segmented medical image having organ tissue including a set of object contours and a contour to be refined. The mechanism inpaints object voxels inside all contours of the set. The mechanism calculates an updated contour around the contour to be refined based on the in-painted object voxels to form an updated segmented medical image. The mechanism determines whether the updated segmented medical image is improved compared to the initial segmented medical image. The mechanism keeps the updated segmented medical image responsive to the updated segmented medical image being improved.

This patent includes a method for utilizing imaging biomarkers to improve pharmacologic dosing strategies. Specifically, biomarker specific CT and MM examination protocols are disclosed. Dose adjustments based on imaging biomarkers are discussed. Longitudinal analysis of imaging biomarkers is disclosed assess effectiveness of pharmacotherapy and dosing strategies thereof. Finally, manufacturing of a combination pill with day-to-day variations of drug quantities is disclosed.

A processor acquires first-direction and second-direction radiographic images captured by emitting radiation in different directions. The processor derives a bone mineral content for each pixel in the bone portion included in the first-direction and second-direction radiographic images. The processor divides the bone portion included in the first-direction and second-direction radiographic images into a plurality of small regions and derives first and second evaluation results for each small region of the bone portion on the basis of the derived bone mineral content.

An image processing apparatus for processing a radiation image, comprises a calculation unit configured to calculate, in a calculation region, a physical amount representing a characteristic of a material, the calculation region being obtained using (a) a specific region regarding a specific material in an image representing the characteristic of the material and (b) a relative positional relationship of a radiation tube, a radiation detector, and an object, wherein the image representing the characteristic of the material is obtained using information about a plurality of radiation energies.

Disclosed herein is an apparatus comprising: an X-ray source configured to direct X-rays through a human tissue; an X-ray detector configured to capture an image of the human tissue with the X-rays; wherein the apparatus is configured to identify an image of a blood vessel from the image of the human tissue and configured to determine a blood sugar level based on the image of the blood vessel.

A console for a radiography system includes at least one processor configured to execute display-related processing of displaying, at an imaging site, a radiographic image obtained by radiography, the display-related processing including reception processing of receiving the radiographic image from a radiographic image detection device and image processing of processing the received radiographic image to a radiographic image for display, computer aided diagnosis processing on the radiographic image after the image processing, and priority processing of giving priority to the display-related processing over the computer aided diagnosis processing in a case where the display-related processing and the computer aided diagnosis processing compete with each other.

A medical information processing apparatus according to an embodiment includes processing circuitry. The processing circuitry obtains image data rendering a blood vessel of a patient. The processing circuitry performs a fluid analysis on the obtained image data and calculates an index value related to a blood flow in the blood vessel with respect to each of a plurality of positions in the blood vessel. With respect to the index values to be calculated, the processing circuitry selects a position in which a first value is to be obtained from among the plurality of positions or selects a value serving as the first value from among the index values exhibited in positions. The processing circuitry causes a display to display the first value in a predetermined display region thereof used for displaying the first value.

The present invention relates to a device (1) for fractional flow reserve determination. The device (1) comprises a model generator (10) configured to generate a three-dimensional model (3DM) of a portion of an imaged vascular vessel tree (VVT) surrounding a stenosed vessel segment (SVS), based on a partial segmentation of the imaged vascular vessel tree (VVT). Further, the device comprises an image processor (20) configured to calculate a blood flow (Q) through the stenosed vessel segment (SVS) based on an analysis of a time-series of X-ray images of the vascular vessel tree (VVT). Still further, the device comprises a fractional-flow-reserve determiner (30) configured to determine a fractional flow reserve (FFR) based on the three-dimensional model (3DM) and the calculated blood flow.

There are provided machine learning device and method which can prepare divided data suitable for machine learning from volume data for learning. A machine learning unit (15) calculates detection accuracy of each organ O(j,i) in a predicted mask Pj using a loss function Loss. However, the detection accuracy of the organ O(k,i) with a volume ratio A(k,i)<Th is not calculated. That is, in the predicted mask Pk, the detection accuracy of the organ O(k,i) with a volume ratio that is small to some extent is ignored. The machine learning unit (15) changes each connection load of a neural network (16) from an output layer side to an input layer side according to the loss function Loss.