Systems and methods for establishing a patient's current or future clinical or lab values are provided. A neural network is trained on a dataset of medical images, such as ultrasound images, that are tagged with information concerning the lab values of people who were imaged to produce the medical images. The trained neural network can then be provided with medical images of a patient, and the neural network can then make a determination as to the patient's current or future clinical or lab values.

The present invention relates to a device and a method for extracting physiological information from remotely detected electromagnetic radiation emitted or reflected by a subject. A data stream derivable from electromagnetic radiation emitted or reflected by a subject is received. The data stream comprises a sequence of signal samples indicative of desired subject motion and of disturbing motion. The signal samples represent at least one region of interest exhibiting an at least partially periodic indicative motion pattern attributable to at least one physiological parameter, and a non-indicative motion region. The sequence of signal samples is processed, comprising deriving a sequence of derivative motion compensated samples at least partially compensated for undesired overall motion; detecting an evaluation parameter representative of motion compensation accuracy; and deriving at least one characteristic signal at least partially indicative of the at least partially periodic indicative motion pattern from the sequence of motion compensated samples, wherein deriving the characteristic signal is performed depending on the detected evaluation parameter.

A method for assessing blood vessel stenosis using image data of a subject is disclosed. The image data represents a vascular structure of the subject. The method comprises: (a) segmenting, from the image data, a vessel segment representing a segment of a blood vessel, (b) obtaining, using the image data, a plurality of two-dimensional images of the vessel segment; said plurality of two-dimensional images representing respective cross-sections of the vessel segment, (c) identifying, for each of the plurality of two-dimensional images, a lumen area comprising lumen pixels representing a lumen of the corresponding cross-section, (d) obtaining a quantitative measure using the lumen areas of successive cross-sections of the vessel segment, and (e) assessing blood vessel stenosis using the quantitative measure. A computer system for performing the above method is disclosed.

An Optical Coherence Tomography (OCT) data processing apparatus includes an acquisition unit configured to acquire three dimensional (3-D) OCT data of an object to be inspected, a generation unit configured to generate a motion contrast image based on the 3-D OCT data, and a detection unit configured to detect a inner surface coordinate of a vessel wall based on position information of an edge of a vessel region in the motion contrast image.

An object information acquiring apparatus, comprises a photoacoustic image acquiring unit configured to generate a first image related to optical characteristics within the object; an ultrasonic image acquiring unit configured to generate a second image related to acoustic characteristics within the object; a region of interest designating unit configured to receive designation of a region of interest with regard to the first image; an image processing unit configured to perform image processing on the first image inside the region of interest and outside the region of interest, respectively, using different image processing parameters; and an image synthesizing unit configured to superimpose and synthesize the first image, which has been image processed, and the second image.

Systems and methods for enhancing quality of a flow image of a sample are provided. An image is obtained from a plurality of optical image scans of a sample comprising blood perfused tissue. A vector comprising tissue components, flow components, and noise is then generated, and eigenvectors and eigenvalues are estimated from the vector. From the eigenvectors and eigenvalues, an eigen regression filter is applied to isolate flow components from the tissue components in the sample. The isolated tissue components may then be removed from the image to enhance visualization and quantification of a flow of dynamic moving particles within the sample.

A medical information processing apparatus includes processing circuitry. The processing circuitry is configured to acquire medical image data representing a blood vessel of a subject, extract a blood vessel shape from the medical image data, determine degree of meandering in each of regions from the extracted blood vessel shape, specify a deformed region in which the degree of meandering changes due to insertion of a device into the blood vessel on the basis of the degree of meandering, and output the deformed region in the blood vessel.

The disclosure relates generally to the field of vascular system and peripheral vascular system data collection, imaging, image processing and feature detection relating thereto. In part, the disclosure more specifically relates to methods for detecting position and size of contrast cloud in an x-ray image including with respect to a sequence of x-ray images during intravascular imaging. Methods of detecting and extracting metallic wires from x-ray images are also described herein such as guidewires used in coronary procedures. Further, methods for of registering vascular trees for one or more images, such as in sequences of x-ray images, are disclosed. In part, the disclosure relates to processing, tracking and registering angiography images and elements in such images. The registration can be performed relative to images from an intravascular imaging modality such as, for example, optical coherence tomography (OCT) or intravascular ultrasound (IVUS).

A medical image processing apparatus according to an embodiment includes processing circuitry. The processing circuitry acquires image data including image data of a blood vessel of a subject. The processing circuitry performs analysis related to the blood vessel by using the image data, and specifies a region of interest in the blood vessel based on a result of the analysis. The processing circuitry performs fluid analysis on a region other than the region of interest at a first accuracy, and performs fluid analysis on the region of interest at a second accuracy that is higher than the first accuracy.

The invention relates to liver diseases. Liver diseases notably encompass chronic liver disease and liver cancer (a liver primitive cancer or metastasis). There is therefore a need to be able to extract biomarkers for subjects to suffer from this disease. As a consequence, the inventors worked on a method for post-processing images of a region of interest to obtain at least one perfusion parameter and at least one transport parameter. Such method enables to obtain a method which can be implemented on computer and provides access to relevant parameters for liver diseases in an easier and more accurate way. This method may be applied for predicting that a subject is at risk of suffering from such disease, diagnosing a disease, identifying a therapeutic or a biomarker and screening compounds useful as a medicine.