An apparatus for determining an enhanced image of a vascular treatment provides (12) a plurality of images including a representation of a region of interest of a vascular structure. Each of the plurality of images includes image data of at least one localizing feature associated with at least one tool configured to be used in the vascular treatment. Each of the plurality of images also includes image data associated with the at least one tool. Registration information for each of the images of the plurality of images is determined (14). At least two images from the plurality of images are selected (16) as a function of the registration information for each of the images. An enhanced image that provides for enhanced visibility of the at least one tool is determined (20). Data representative of the enhanced image is output (24).

An information processing apparatus, an information processing method, and a cell analysis system are provided. The information processing apparatus includes a processor configured to: determine a frequency feature value based on motion data from an image of a cell, and control displaying information associated with the frequency feature value, wherein the frequency feature value includes a power spectral density for each time range and each frequency band, and wherein the information associated with the frequency feature value is displayed in association with the each time range and the each frequency band.

A dynamic image processing system including a hardware processor that extracts a heart region from a chest dynamic image which is obtained by radiation imaging of a dynamic state at a chest, extracts a density waveform for each pixel in the extracted heart region, determines an extraction target candidate region of blood flow information based on the extracted density waveform for each pixel, and sets an extraction target region of the blood flow information in the determined extraction target candidate region of the blood flow information.

A method of processing optical coherence tomography (OCT) scans through a subject's skin, the method comprising: receiving a plurality of scans through the subject's skin, the scans representing an OCT signal in slices through the user's skin at different times; comparing the scans to determine time-varying regions in the scans; determining a depth-distribution of the time varying regions.

Implementations relate to detecting/replacing transient obstructions from high-elevation digital images, and/or to fusing data from high-elevation digital images having different spatial, temporal, and/or spectral resolutions. In various implementations, first and second temporal sequences of high-elevation digital images capturing a geographic area may be obtained. These temporal sequences may have different spatial, temporal, and/or spectral resolutions (or frequencies). A mapping may be generated of the pixels of the high-elevation digital images of the second temporal sequence to respective sub-pixels of the first temporal sequence. A point in time at which a synthetic high-elevation digital image of the geographic area may be selected. The synthetic high-elevation digital image may be generated for the point in time based on the mapping and other data described herein.

A method and system for determining fractional flow reserve (FFR) for a coronary artery stenosis of a patient is disclosed. In one embodiment, medical image data of the patient including the stenosis is received, a set of features for the stenosis is extracted from the medical image data of the patient, and an FFR value for the stenosis is determined based on the extracted set of features using a trained machine-learning based mapping. In another embodiment, a medical image of the patient including the stenosis of interest is received, image patches corresponding to the stenosis of interest and a coronary tree of the patient are detected, an FFR value for the stenosis of interest is determined using a trained deep neural network regressor applied directly to the detected image patches.

Some methods of analyzing one or more brain lesions of a patient comprise, for each of the lesion(s), calculating one or more lesion characteristics from a first 3-dimensional (3D) representation of the lesion obtained from data taken at a first time and a second 3D representation of the lesion obtained from data taken at a second time that is after the first time. The characteristic(s) can include a change, form the first time to the second time, in the lesion's volume and/or surface area, the lesion's displacement from the first time to the second time, and/or the lesion's theoretical radius ratio at each of the first and second times. Some methods comprise characterizing whether the patient has multiple sclerosis and/or the progression of multiple sclerosis in the patient based at least in part on the calculation of the lesion characteristic(s) of each of the lesion(s).

In some examples, an electronic device comprises an interface to receive a video of a human face, a memory storing executable code, and a processor coupled to the interface and to the memory. As a result of executing the executable code, the processor is to receive the video from the interface, use a facial detection technique to produce a sequence of images of the human face based on the video, use a neural network to predict a photoplethysmographic (PPG) signal based on the sequence of images, convert the PPG signal to a frequency domain signal, and determine a heart rate by performing a frequency analysis on the frequency domain signal.

Fluorescence based tracking of a light-emitting marker in a bodily fluid stream is conducted by: providing a light-emitting marker into a fluid stream; establishing field of view monitoring by placement of a sensor, such as a high speed camera, at a region of interest; recording image data of light emitted by the marker at the region of interest; determining time characteristics of the light output of the marker traversing the field of view; and calculating flow characteristics based on the time characteristics. Furthermore generating a velocity vector map may be conducted using a cross correlation technique, leading and falling edge considerations, subtraction, and/or thresholding.

The present disclosure is generally related to systems and methods that can be implemented in a mobile application to allow users, such as parents and care providers, to measure and monitor, for example, a patient's body including an infant's head shape, at the point of care. The point of care can be, for instance, the home environment, a doctor's office, or a hospital setting. After acquiring 2D and/or 3D images of the body part, parameters reflecting potential deformity can be calculated. If abnormal measurements are determined, the user can be guided through therapeutic options to improve the condition. Based on the severity of the condition, different recommendations can be provided. Moreover, longitudinal monitoring and evaluation of the parameters can be performed. Monitoring of the normal child development can also be performed through longitudinal determination of parameters and comparison to normative values. Data can be shared with clinician's office.