Described is a system for feature selection for formal concept analysis (FCA). A set of data points having features is separated into object classes. For each object class, the data points are convolved with a Gaussian function, resulting in a class distribution curve for each known object class. For each class distribution curve, a binary array is generated having ones on intervals of data values on which the class distribution curve is maximum with respect to all other class distribution curves, and zeroes elsewhere. For each object class, a binary class curve indicating for which interval a performance of the known object class exceeds all other known object classes is generated. The intervals are ranked with respect to a predetermined confidence threshold value. The ranking of the intervals is used to select which features to extract from the set of data points in FCA lattice construction.

An image processing apparatus includes an information obtaining unit configured to obtain three-dimensional polarization sensitive tomographic information and three-dimensional motion contrast information about a subject based on tomographic signals of lights having different polarizations, the lights being obtained by splitting a combined light obtained by combining a returned light from the subject illuminated with a measurement light with a reference light corresponding to the measurement light, an obtaining unit configured to obtain a lesion region of the subject using the three-dimensional polarization sensitive tomographic information, and an image generation unit configured to generate an image in which the lesion region is superimposed on a motion contrast image generated using the three-dimensional motion contrast information.

The present disclosure is directed to methods and systems for fusing Phase Contrast Angiography (PCA) with anatomic images to create a perforator PCA (pPCA) data set. In the pPCA) method, vascular and anatomic information may be provided by different MRI sequences. A four-point acquisition scheme may be used for 3D PCA acquisition of vascular images. Anatomical MRI images are acquired and may be enhanced with image post-processing techniques. The vascular and anatomical images may be combined with image fusion to create a high resolution map of abdominal wall vasculature. This high resolution map visualizes not only the size and location of the DIEP perforators, but also their relationship with surrounding tissue, and the blood flow velocity within them. As such, the fused pPCA image has substantially higher SNR and CNR than CTA image of the same slice thickness.

A system and method for performing image processing. The method includes receiving an image of a first modality and a real image of a second modality, the image of the first modality and the image of the second modality capturing respective images of a same subject, applying a first trained model to the image of the first modality to generate an artificial image mimicking the image of the second modality, applying a second trained model to the artificial image mimicking the image of the second modality and data of the image of the first modality, and outputting at least one conclusion regarding the generated artificial image.

Embodiments include systems and methods for determining cardiovascular information for a patient. A method includes receiving patient-specific data regarding a geometry of the patient's vasculature; creating an anatomic model representing at least a portion of the patient's vasculature based on the patient-specific data; and creating a computational model of a blood flow characteristic based on the anatomic model. The method also includes identifying one or more of an uncertain parameter, an uncertain clinical variable, and an uncertain geometry; modifying a probability model based on one or more of the identified uncertain parameter, uncertain clinical variable, or uncertain geometry; determining a blood flow characteristic within the patient's vasculature based on the anatomic model and the computational model of the blood flow characteristic of the patient's vasculature; and calculating, based on the probability model and the determined blood flow characteristic, a sensitivity of the determined fractional flow reserve to one or more of the identified uncertain parameter, uncertain clinical variable, or uncertain geometry.

An ultrasonic diagnostic device according to an embodiment includes a collecting unit and processing circuitry. The collecting unit performs ultrasonic scanning with respect to a subject and collects reflected-wave data. The processing circuitry performs short-time Fourier transform in the depth direction with respect to the reflected-wave data; applies a nonlinear adaptive MTI filter on a frequency-by-frequency basis with respect to the result of the short-time Fourier transform; and performs inverse short-time Fourier transform in the depth direction with respect to the output of the nonlinear adaptive MTI filter. Then, the processing circuitry estimates blood flow information from the result of the inverse short-time Fourier transform.

An image registration device includes: an image acquisition unit that acquires a plurality of images; a divided region setting unit that sets divided regions by dividing each registration processing target of the plurality of images; a pixel value conversion method determination unit that determines, for each set of divided regions set at the same position of the respective registration processing targets, a pixel value conversion method for each divided region based on a pixel value of each divided region of the set; a pixel value conversion unit that performs pixel value conversion within each divided region of the set of divided regions using the determined pixel value conversion method for each divided region; and a registration processing unit that performs registration processing on the plurality of images subjected to pixel value conversion.

The invention relates to a processing apparatus for processing cardiac data of a living being and to an imaging system comprising the processing apparatus. A distribution of Fractional flow reserve (FFR) values being indicative of the FFR of different coronary arteries of the living being, a distribution of myocardial perfusion values like values of an iodine map being indicative of the myocardial perfusion of different portions of the myocardium of the living being and assignments between coronary arteries and portions of the myocardium of the living being are used for determining degrees of correspondence between FFR values and myocardial perfusion values. This allows for, for example, a determination of the reliability of the FFR values, if the myocardial perfusion values are known to be reliable, based on the determined degrees of correspondence.

Determining collateral information describing blood flow in collaterals of a blood vessel system in a target region of a patient from a four-dimensional vascular data set describing image values of temporal flow of a contrast medium and/or marked blood constituents as recorded by a medical imaging device is provided. A method includes segmenting the blood vessel system in the vascular data set and determining collaterals among the segmented blood vessels by a collateral classifier. For all collaterals determined, a diameter of the collateral is determined taking into account the segmentation, a filling parameter describing the filling of the collaterals, and a time parameter describing the time response relative to a reference point in the blood vessel system from a temporal course of the image values in a portion of the collaterals under consideration. The method includes determining the collateral information from the diameter, the filling parameter, and the time parameter.

A computer-implemented method for providing a scene with synthetic contrast includes receiving preoperative image data of an examination region containing a hollow organ, wherein the medical image data images a contrast agent flow in the hollow organ; receiving intraoperative image data of the examination region of the examination subject, wherein the intraoperative image data images a medical object at least partially disposed in the hollow organ, generating the scene with synthetic contrast by applying a trained function to input data, wherein the input data is based on the preoperative image data and the intraoperative image data, wherein the scene with synthetic contrast images a virtual contrast agent flow in the hollow organ taking into account the medical object disposed therein, wherein at least one parameter of the trained function is based on a comparison between a training scene and a comparison scene; and providing the scene with synthetic contrast.