Systems and methods are disclosed for predicting coronary plaque vulnerability, using a computer system. One method includes acquiring anatomical image data of at least part of the patient's vascular system; performing, using a processor, one or more image characteristics analysis, geometrical analysis, computational fluid dynamics analysis, and structural mechanics analysis on the anatomical image data; predicting, using the processor, a coronary plaque vulnerability present in the patient's vascular system, wherein predicting the coronary plaque vulnerability includes calculating an adverse plaque characteristic based on results of the one or more of image characteristics analysis, geometrical analysis, computational fluid dynamics analysis, and structural mechanics analysis of the anatomical image data; and reporting, using the processor, the calculated adverse plaque characteristic.

The present invention provides a computer device and a computer-implemented method to quantify the extent of functional coronary artery disease. In addition, the invention provides a computer device for determining the functional pattern of coronary disease in a mammal. It is shown that a mismatch in the extent of CAD between anatomical and physiological evaluations is predictable for an improvement in epicardial conductance with percutaneous revascularization. More particularly the invention provides methods to select a mammal suffering from coronary disease to benefit from a percutaneous coronary intervention.

Provided is a non-contact blood flow observation apparatus that enables speedy and clear observation of states of blood flow in a contactless manner. This non-contact blood flow observation apparatus 1 includes an image acquirer 2 that acquires a first image 2im that is a moving image or a series of still images of a region including a blood vessel, and an image processor 3 that correlates a different color with each gradation of brightness in advance, creates a second image 3im by assigning the color corresponding to the brightness for each singular or plurality of pixels in the first image 2im, and displays the second image 3im that is a moving image or a series of still images on a display device 5.

An image processing apparatus includes a processor. The processor is configured to: set a plurality of tracking points uniformly arranged in a first image that is one of the time series of images; track each of the tracking points from the first image to a second image and determine the success or failure in tracking each of the tracking points, the second image being an image at a different time from the first image among the time series of images; estimate an image plane of the second image by perspective projection transformation using the tracking points tracked successfully; correct the positions of the tracking points failed to be tracked on the second image by back projection to the image plane; and perform image registration on the second image based on the plurality of tracking points to generate a registration image.

Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

A method for performing flow analysis in a target volume of a moving organ having a long axis, such as the heart, from 4D MR Flow volumetric image data set of such organ, wherein such data set comprises structural information and three-directional velocity information of the target volume over time, the devices, program products and methods comprising, under control of one or more computer systems configured with specific executable instructions: a) deriving from the 4D MR Flow volumetric image data set at least one derived image data set related to the long axis of the moving organ, for example, by using a multi planar reconstruction; b) determining at least one feature of interest in the 4D MR Flow volumetric image data set or in said derived image data set. The feature of interest may be determined, for example, by receiving input from a user or by performing automatic detection steps on the 4D MR Flow volumetric image data set; c) tracking the feature of interest within the 4D MR Flow volumetric image data set or in the derived image data set; d) determining the spatial orientation over time of a plane containing the feature of interest in the 4D MR Flow volumetric image data set; e) performing quantitative flow analysis using velocity information on the plane as determined in step d). A corresponding device and computer program are also disclosed.

It will be appreciated by persons skilled in the art that the present invention is not limited to what has been particularly shown and described hereinabove. Rather, the scope of the present invention includes both combinations and subcombinations of the various features described hereinabove, as well as variations and modifications thereof that are not in the prior art, which would occur to persons skilled in the art upon reading the foregoing description.

A system (100) includes a computer readable storage medium (122) with computer executable instructions (124), including: a biophysical simulator component (126) configured to determine a fractional flow reserve index. The system further includes a processor (120) configured to execute the biophysical simulator component (126) to determine the fractional flow reserve index with spectral volumetric image data. The system further includes a display configured to display the determine fractional flow reserve index.

Systems and methods are disclosed for correcting for artificial deformations in anatomical modeling. One method includes obtaining an anatomic model; obtaining information indicating a presence of an artificial deformation of the anatomic model; identifying a portion of the anatomic model associated with the artificial deformation; estimating a non-deformed local area corresponding to the portion of the anatomic model; and modifying the portion of the anatomic model associated with the artificial deformation, based on the estimated non-deformed local area.

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.