A method of treating a human patient identified as having an injury to a body region includes receiving CT images, where the CT images were generated by performing a CT angiography of an injured body region of the human patient. The method further includes determining, based on the CT images, a total volumetric rate of active bleeding in the injured body region; and recommending at least one treatment approach for the human patient based on the total volumetric rate of active bleeding.

A medical-information processing apparatus according to an embodiment includes processing circuitry. The processing circuitry acquires medical image data that is obtained during imaging on the subject in a resting state in the time phase where the relationship between the volume of blood flow and the pressure in a blood vessel in the cardiac cycle of the subject indicates a proportional relationship. The processing circuitry extracts the structure of a blood vessel, included in the medical image data, applies fluid analysis to the structure of the blood vessel to obtain a first index value, which is obtained based on the pressure in the blood vessel on the upstream side of a predetermined position within the blood vessel and the relation equation between the volume of blood flow and the pressure in the blood vessel in the resting state, and a second index value, which is obtained based on the pressure in the blood vessel on the downstream side of the predetermined position and the relation equation, and calculates the pressure ratio, which is the ratio of the first index value to the second index value.

A risk evaluation system is provided with an imager and a controller. The imager takes images at different times of equipment having zones that do not overlap each other, and outputs the images that are taken. The controller detects a contact count of a number of times a living body contacts each of the zones in accordance with the images, decides evaluation information about a contact infection risk in each of the zones in accordance with the contact count, and outputs the evaluation information.

A method for identification of an optimal image within a sequence of image frames includes inputting the sequence of images into a computer processor configured for executing a plurality of neural networks and applying a sliding window to the image sequence to identify a plurality of image frame windows. The image frame windows are processed using a first neural network trained to classify the image frames according to identified spatial features. The image frame windows are also processed using a second neural network trained to classify the image frames according to identified serial features. The results of each classification are concatenated to separate each of the image frame windows into one of two classes, one class containing the optimal image. An output is generated to display image frame windows classification as including the optimal image.

According to one embodiment, a medical image processing apparatus includes processing circuitry. The processing circuitry obtains first and second blood vessel image by image generation processing which obtains time phase changes in concentrations of a contrast agent based on X-ray contrast image and generates time phase image according to a gray or color scale. The time phase image has pixel values corresponding to time phases at which the concentrations of the contrast agent become a specific condition. The image generation processing is performed multiple times based on X-ray contrast images acquired at different times. Further, the processing circuitry determines or corrects pixel values or time phases of at least one of the first and second blood vessel image, to make a pixel value of a time phase of the first blood vessel image coincident with that of the second blood vessel image.

Systems and methods for detecting complex networks in MRI image data in accordance with embodiments of the invention are illustrated. One embodiment includes an image processing system, including a processor, a display device connected to the processor, an image capture device connected to the processor, and a memory connected to the processor, the memory containing an image processing application, wherein the image processing application directs the processor to obtain a time-series sequence of image data from the image capture device, identify complex networks within the time-series sequence of image data, and provide the identified complex networks using the display device.

A system and method for camera-based heart rate tracking. The method includes: determining bit values from a set of bitplanes in a captured image sequence that represent the HC changes; determining a facial blood flow data signal for each of a plurality of predetermined regions of interest (ROIs) of the subject captured by the images based on the HC changes; applying a band-pass filter of a passband approximating the heart rate to each of the blood flow data signals; applying a Hilbert transform to each of the blood flow data signals; adjusting the blood flow data signals from revolving phase-angles into linear phase segments; determining an instantaneous heart rate for each the blood flow data signals; applying a weighting to each of the instantaneous heart rates; and averaging the weighted instantaneous heart rates.

A method is provided for operating a medical imaging device when performing an imaging examination. In order to allow an improved preparation of images in the context of such an imaging examination, the method includes: providing an original image of a body region; recording an updated image of the body region; and generating a three-dimensional subsequent image from the original image and from the updated image using a previously trained artificial neural network.

Apparatus for an automatic identification of medically relevant video elements, the apparatus including a data input, configured to receive a data stream of image slices, wherein the data stream of image slices represents a temporal course of a view of image slices defined by a masking strip of video images from a video which has been recorded during a medical surgery on a patient an analysis apparatus configured to analyze the data stream of image slices via an analysis including at least one predefined analysis step for the presence of at least one sought-for feature and to output a result of the presence, and a processing device configured to output a start mark which indicates a correspondence between the presence and a position in the data stream of image slices if the result indicates the presence of the sought-for feature. Also, a corresponding method is disclosed.

There is provided a method comprising: providing two anatomical images of a target individual, each captured at a unique orientation of the target individual, inputting first and second anatomical images respectively into a first and second convolutional neural network (CNN) of a classifier to respectively output first and second feature vectors, inputting a concatenation of the first and second feature vectors into a fully connected layer of the classifier, and computing an indication of distinct visual finding(s) present in the anatomical images by the fully connected layer, wherein the statistical classifier is trained on a training dataset including two anatomical images of each respective sample individual, each image captured at a respective unique orientation of the target individual, and a tag created based on an analysis that maps respective individual sentences of a text based radiology report to one of multiple indications of visual findings.