The present disclosure provides a method for correcting a resting blood flow velocity on the basis of an interval time between angiogram images, comprising: acquiring, in an angiography state, an average blood flow velocity V.sub.h from a coronary artery inlet to a distal end of a coronary artery stenosis (S100); acquiring a time difference Δt between start times of two adjacent bolus injections of contrast agent (S200); obtaining a correction coefficient K according to the time difference Δt (S300); obtaining a resting blood flow velocity V.sub.j according to the correction coefficient K and the average blood flow velocity V.sub.h (S400), as well as an apparatus configured for implementing the above method. The disclosure obtains the resting blood flow velocity V.sub.j according to the correction coefficient K and the average blood flow velocity V.sub.h.

From a plurality of medical images in time phases, a target site is extracted from at least one medical image, a reference point is set on each of a target-site side, and a periphery side of the target site which are on across from each other over an outline of the extracted target site, and movement information for the reference points is calculated.

Systems and methods for tracking healing progress of multiple adjacent wounds are provided. In one embodiment, a system may include a processor configured to receive a first image of a plurality of adjacent wounds near a form of colorized surface having colored reference elements, determine colors of the plurality of wounds, correct for local illumination conditions, receive a second image of the plurality of wounds near the form of colorized surface, to determine second colors of the plurality of wounds in the second image, match each of the plurality of wounds in the second image to a wound of the plurality of wounds in the first image, and determine an indicator of the healing progress for each of the plurality of wounds based on changes between the first image and the second image.

A method for providing an optimum subtraction data set includes: receiving first image data sets acquired by a medical imaging device and which map an object under examination within a first time phase; receiving at least one second image data set acquired by the same or another medical imaging device and which maps a change in the object under examination within a second time phase; dividing the at least one second image data set into a plurality of image regions; generating subtraction image regions for the plurality of image regions; determining an image quality parameter for each subtraction image region; determining an optimum subtraction image region for each image region of the plurality of image regions of the at least one second image data set by comparing the image quality parameters; generating the optimum subtraction data set from the optimum subtraction image regions; and providing the optimum subtraction data set.

An apparatus for indicating health conditions of a user is disclosed. The apparatus includes a camera configured to capture a reference image of a user's face and a new image of a user's face. The apparatus also includes a processor configured to determine facial properties of the user in the reference image and the new image; determine any differences in the facial properties determined from the reference image and the status image; generate a warning when differences in the facial properties between the reference image and the new image are determined; and store the record in a memory. A method of facial recognition for indicating health conditions of a user and a computer program comprising machine readable instructions are also provided.

A method for providing an optimum subtraction data set includes receiving first image data sets that are recorded by a medical imaging device and map an examination object within a first temporal phase. At least one second image data set that maps the examination object within a second temporal phase and is recorded by the same or another medical imaging device is received. Mask data sets are determined. The mask data sets include at least one of the first image data sets and/or an averaging of at least one combination of the first image data sets. Subtraction data sets are generated by subtracting one of the mask data sets from the at least one second image data set, and an image quality parameter is determined for each of the subtraction data sets. An optimum subtraction data set is provided by a comparison of the image quality parameters.

Systems and methods for improving endoscopy procedures are described that provide not only a conventional real time image of the view obtained by an endoscope, but in addition, a near real time 3D model and/or a 2D flattened image of an interior surface of an organ, which model and image may be processed using AI software to highlight potential tissue abnormalities for closer examination and/or biopsy during the procedure. A navigation module interacts with other system outputs to further assist the endoscopist with navigational indicia, e.g., landmarks and/or directional arrows, that enhance the endoscopists' spatial orientation, and/or may provide navigational guidance to the endoscopist to assist manipulation of the endoscope.

An apparatus includes at least one processor configured to obtain stereo-spatio-temporal data measurements of plants in a growing area. The stereo-spatio-temporal data measurements include (i) first spatio-temporal data measurements of the plants in the growing area and (ii) second spatio-temporal data measurements of the plants in the growing area. The at least one processor is also configured to analyze the stereo-spatio-temporal data measurements to identify one or more actual or potential problems associated with one or more of the plants. The at least one processor is further configured to generate a graphical user interface identifying at least one of the one or more actual or potential problems with the one or more plants. The first and second spatio-temporal data measurements of each stereo-spatio-temporal data measurement are associated with at least one common plant characteristic and different three-dimensional positions within the growing area taken at one or more known times.

A method for enhancing an accuracy of a benign tumor development trend assessment system includes: a first processing procedure, an image captured before the treatment is inputted to and be processed by a server computing device of the benign tumor development trend assessment system to obtain a first processing result; a second processing procedure, the images captured before and in at least one period after the treatment are inputted to and processed by the server computing device to obtain a second processing result; a trend analyzing procedure, the trend analyzing module of the server computing device analyzes the first processing result, the second processing result and the trend pathways to obtain a tumor development trend result; and a storing procedure, the first processing result, the second processing result and the tumor development trend result are transformed to an individual trend pathway which is stored in the trend analyzing module.

Embodiments are provided for identification of a section of bodily tissue as either a candidate or a non-candidate for pathology tests. In some embodiments, a system can include a processor that executes computer-executable components stored in memory. The computer-executable components can include a feature composition component that generates a feature vector representing a physical model describing dye dynamics that determines a group of multispectral images of a section of bodily tissue. The computer-executable components also can include a classification component that generates a classification attribute for the section of bodily tissue by applying a classification model to the feature vector. The classification attribute designates the section of bodily tissue as one of biopsy-candidate or non-biopsy-candidate.