A method of mapping autoregulation of a kidney using magnetic resonance (MR) imaging is provided. The method includes acquiring a time series of MR images of a subject while the subject is at rest by acquiring MR images of an imaging region repeatedly over a period of time by applying a pulse sequence. The imaging region includes at least a kidney of the subject. The method also includes analyzing the time series of MR images along a temporal dimension, and identifying features associated with autoregulation of the kidney including tubuloglomerular feedback (TGF) in voxels of the MR images based on the analysis. The method further includes generating a map and/or a metric of the autoregulation based on the identified features, and outputting the map and/or the metric.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a respective response score for each of a plurality of patient categories. In one aspect, a method comprises: generating a drug signature for a drug; generating an embedding of the drug signature in a latent space; and processing: (i) the embedding of the drug signature in the latent space, and (ii) data defining a plurality of patient categories, to generate a plurality of response scores, wherein each response score corresponds to a respective patient category and characterizes a predicted response of patients included in the patient category to the drug.

The present invention provides devices, systems, and methods, for performing biological and chemical assays.

A radiographic imaging apparatus includes an image processor configured to perform image processing on a radiation image generated by an image generator, and a display configured to display a processed image that has been subjected to the image processing in the image processor. The image processor is configured to perform control to create the processed image showing an expanded portion in which a balloon introduced into a subject is expanded.

A system for monitoring the movement of objects, structures, models of structures, cables and the like provides for the acquisition of images with an optical sensing device such as a video camera fixedly mounted at a selected distance from the item studied, in which the images are arranged into frames divided into pixels which are characterized by an intensity reflected or emitted over a selected time interval, and a data processing system to calculate a physical displacement as function of time of the item being studied or a portion of the item being studied based on an output from the video camera, and in some embodiments the system visually distinguishes one or more locations in the frame to indicate a difference in the phase of motion for multiple objects appearing in the frame.

A time phase determination apparatus according to an embodiment is a time phase determination apparatus for determining the range of a particular time phase in a contrast-enhanced image, and includes processing circuitry. The processing circuitry acquires medical images at a plurality of different timings. The processing circuitry extracts a plurality of regions of interest on the basis of the medical images at the different timings. The processing circuitry generates a plurality of time intensity curves that are time intensity curves corresponding to the respective regions of interest. The processing circuitry determines the range of the particular time phase on the basis of the time intensity curves.

A computer-implemented method for providing a vascular image data record includes receiving a plurality of projection-X-ray images recorded in temporal succession. The plurality of projection-X-ray images at least partially map a common examination region of an examination object. The plurality of projection-X-ray images map a temporal change in the examination region of the examination object. A change image data record is determined in each case based on at least one region of interest of the plurality of projection-X-ray images. The at least one region of interest includes a plurality of image points. The change image data record in each case includes a time-intensity curve for each of the image points. The vascular image data record is generated based on the change image data record, and the vascular image data record is provided.

System and method for diagnosing a disease using image classification is provided. The method includes receiving diagnostic images associated with a subject. The diagnostic images comprise a first image and a second image captured at a first instance of time and at a second instance of time, respectively. The method further includes extracting feature maps from the first image and the second image, using a first pipeline and a second pipeline of stacked convolutional layers of a temporal convolutional neural network (CNN) model respectively. The method further includes identifying relevant feature maps from the feature maps using temporal CNN layer of the temporal CNN model, generating a concatenated feature map based on the relevant feature maps, determining an image class corresponding to the second image using fully connected layers of the temporal CNN model, and diagnosing the disease associated with the subject based on the image class.

A computer-implemented method for comparing follow-up medical findings includes receiving image data showing a body part of a patient at a first time and retrieving, from a database, reference data associated to the image data. The reference data includes reference biometric data and one or more reference medical findings. Thereby the reference biometric data and the one or more reference medical findings have been extracted from reference image data depicting the body part of the patient at a second time, different than the first time. The method further includes processing the received image data to extract, from the image data, biometric data corresponding to the reference biometric data and one or more medical findings; performing a registration of the extracted biometric data with the reference biometric data; and comparing the extracted medical findings with the reference medical findings using the registration.

A method for identifying brain-state dependent functional areas of unitary pooled activity (FAUPAs) using a statistical model that does not require a priori knowledge of the activity-induced ideal response signal time course is provided. A system for identifying a functional network in a brain of a living object includes a FAUPA identifier configured to identify FAUPAs by analyzing a plurality of images of the brain over a predetermined period. The plurality of images include a plurality of voxels, and the FAUPA identifier analyzes each voxel of the plurality of voxels in relation to one or more surrounding voxels of each voxel until each voxel of the plurality of voxels is evaluated. A brain network identification module configured to construct the functional network based on the identified FAUPAs that are functionally connected. A display module configured to display images of the brain depicting the FAUPAs included in the functional network.