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.

A remote photoplethysmography (RPPG) system for estimating vital signs of a person is provided. The RPPG system is configured to receive a set of imaging photoplethysmography (iPPG) signals measured from different regions of a skin of a person. The RPPG system is further configured to determine frequency coefficients at the frequency bins of the quantized frequency spectrum of the measured iPPG signals by minimizing a distance between the measured iPPG signals and corresponding iPPG signals reconstructed from the determined frequency coefficients, while enforcing joint sparsity of the determined frequency coefficients subject to the sparsity level constraint, such that the determined frequency coefficients of different iPPG signals have the non-zero values at the same frequency bins; and output one or a combination of the determined frequency coefficients, the iPPG signals reconstructed from the determined frequency coefficients, and a vital sign signal corresponding to the reconstructed iPPG signals.

A system and method for automatically analyzing placenta insufficiency in a curved topographical ultrasound image slice is provided. The method includes acquiring, by an ultrasound system, an ultrasound volume of a placental anatomy section, the ultrasound volume comprising color Doppler information. The method includes extracting, by at least one processor of the ultrasound system, a topographical ultrasound image slice at a distance below an inner surface of the placental anatomy section. The topographical ultrasound image slice is curved in all three dimensions and includes the color Doppler information. The method includes analyzing, by the at least one processor, the color Doppler information of the topographical ultrasound image slice to generate perfusion data information. The method includes causing, by the at least one processor, a display system to present the topographical ultrasound image slice with the perfusion data information.

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 system for estimating post-virtual stenting fractional flow reserve (FFR) capable of: receiving geometrical parameters of a blood vessel segment, the geometrical parameters comprising first, second and third geometrical parameters; with a proximal end as a reference point, deriving a reference lumen diameter function and calculating a pre-virtual stenting percent diameter stenosis based on the above geometrical parameters and the distance from position along the segment to the reference point; receiving a virtual stenting location; calculating a geometrical parameter of a virtual lumen of the post virtually-stented segment, deriving a post-virtual stenting geometrical parameter difference function and calculating a percent diameter stenosis based on the third geometrical parameter, the virtual stenting location and the reference lumen diameter function; taking derivative difference functions of the post-virtual stenting geometrical parameter difference function in multiple scales; and obtaining FFR based on the multiple scales of derivative difference functions and a maximum post-virtual stenting mean blood flow velocity. Post-virtual stenting FFR is estimated based on changes in percent diameter stenosis and the maximum mean blood flow velocity after virtual stent implantation using a multi-scale calculation method.

An image processing apparatus according to an embodiment comprises processing circuitry configured to acquire morphology image data including a site of a subject and function image data including the site, extract a blood vessel region that corresponds to a blood vessel included in the morphology image data, calculate a fluid index in the blood vessel region, and based on the fluid index, calculate a first function index as an index indicating a function of a tissue to which a nutrient is supplied from the blood vessel, acquire a second function index as an index indicating a function of the tissue based on the function image data, detect a mismatch between the first function index and the second function index, and determine a spatial region that corresponds to the mismatch in the site.

A dynamic analysis system includes an imaging device and an analysis device. The imaging device performs dynamic imaging by emitting radiation to a chest part of a human body, thereby obtaining a series of frame images showing a dynamic state of the chest part. The analysis device includes a controller. The controller (i) selects a first plurality of frame images to be analyzed from the series of frame images obtained by the imaging device, (ii) calculates, based on the first plurality of frame images, a ventilation amount index value that indicates an amount of ventilation of a lung field and a perfusion amount index value that indicates an amount of perfusion of the lung field, and (iii) calculates a ratio of the ventilation amount index value to the perfusion amount index value.

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.

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.

A method and device for determining a flow situation in a vessel are disclosed. According to an embodiment of the method, a first image data set containing image information relating to the vessel is used and a vascular tree of the vessel is segmented based upon the first image data set. An organ is also segmented based upon the first image data set or of a second image data set and the organ is assigned at least one area of a parenchyma of the organ. Via texture analysis, a texture of the area of the organ is determined and, depending on the texture, the area of the organ is assigned a flow characteristic. Depending on the vascular tree and the flow characteristic assigned to the area of the organ, a value of a measured variable characteristic of the flow situation within the vessel is then determined via a numerical method.