A method may include identifying a simulated three-dimensional representation corresponding to an internal anatomy of a subject based on a match between a computed two-dimensional image corresponding to the simulated three-dimensional representation and a two-dimensional image depicting the internal anatomy of the subject. Simulations of the electrical activities measured by a recording device with standard lead placement and nonstandard lead placement may be computed based on the simulated three-dimensional representation. A clinical electrogram and/or a clinical vectorgram for the subject may be corrected based on a difference between the simulations of electrical activities to account for deviations arising from patient-specific lead placement as well as variations in subject anatomy and pathophysiology.

There is provided a medical imaging processing device, comprising: at least one hardware processor executing a code for: iteratively generating instructions for iterative adjustment of presentation parameter(s) of a 2D frame of the 3D anatomical image presented on the display, for creating a sequence of adapted 2D frames of the 3D anatomical image, the instructions transmitted from the medical imaging processing device to a physical input interface of at least one of the client terminal and display, for each respective 2D frame: capturing the respective 2D frame from video signals transmitted from the client terminal to the display, analyzing the respective captured 2D frame for extraction of a 2D anatomical image, analyzing the respective captured 2D frame to identify metadata element(s), converting the metadata element(s) into converted metadata value(s), and formatting the extracted 2D anatomical images and associated converted metadata values for reconstruction of the 3D anatomical image.

A method and apparatus for monitoring a human or animal subject in a room using video imaging of the subject and analysis of the video image to detect and quantify movement of the subject and to derive an estimate of vital signs such as heart rate or breathing rate. The method includes techniques for de-correlating global intensity variations such as sunlight changes, compensating for noise, eliminating areas not of interest in the image, and quickly and automatically finding regions of interest for detecting subject movement and estimating vital signs. A logic machine is used for interpreting detected movement of the subject, and an artificial neural network is used to calculate a confidence measure for the vital signs estimates from signal quality indices. The confidence measure may be used with a normal density filter to output estimates of the vital signs.

A method and apparatus for monitoring a human or animal subject in a room using video imaging of the subject and analysis of the video image to detect and quantify movement of the subject and to derive an estimate of vital signs such as heart rate or breathing rate. The method includes techniques for de-correlating global intensity variations such as sunlight changes, compensating for noise, eliminating areas not of interest in the image, and quickly and automatically finding regions of interest for detecting subject movement and estimating vital signs. A logic machine is used for interpreting detected movement of the subject, and an artificial neural network is used to calculate a confidence measure for the vital signs estimates from signal quality indices. The confidence measure may be used with a normal density filter to output estimates of the vital signs.

A plurality of image projections are acquired at faster than cardiac rate. A spatiotemporal reconstruction of cardiac frequency angiographic phenomena in three spatial dimensions is generated from two dimensional image projections using physiological coherence at cardiac frequency. Complex valued methods may be used to operate on the plurality of image projections to reconstruct a higher dimensional spatiotemporal object. From a plurality of two spatial dimensional angiographic projections, a 3D spatial reconstruction of moving pulse waves and other cardiac frequency angiographic phenomena is obtained. Reconstruction techniques for angiographic data obtained from biplane angiography devices are also provided herein.

A first acquisition unit acquires stent regions from each of three-dimensional images. A second acquisition unit acquires blood vessel regions from each of the three-dimensional images. A positioning unit acquires a first positioning result by positioning the blood vessel regions for each of the three-dimensional images. A deviation information acquisition unit acquires deviation information indicating a deviation of a stent from a blood vessel between the three-dimensional images based on the stent regions for the three-dimensional images and a deformation vector which is the first positioning result.

Methods, systems, and computer readable media are provided for processing medical images. One or more prior medical images are aligned with a current medical image. Image subtraction between the current medical image and the one or more prior medical images is performed to produce one or more difference images. The one or more difference images are applied to a machine learning model to determine a presence or an absence of a medical condition.

An angiogram is a study of blood vessels where an angiographic chemical contrast agent is injected while a sequence of images (typically x-rays) are obtained. The contrast pattern on the sequence of images provides information about the vascular anatomy and physiology. The discovery that contrast in blood vessels varies at cardiac frequency in magnitude and phase, which may be visualized as a spatiotemporal reconstruction of cardiac frequency angiographic phenomena, enables a set of processes for increasing the signal to noise ratio or equivalently the informational content of an angiogram. In this invention, the organization of cardiac frequency magnitude and phase enables equivalent information on anatomy and physiology to be obtained with less dose of injected chemical contrast agent, less x-ray dose, and/or less navigation of the injecting catheter within blood vessels. The cardiac frequency magnitude and phase is organized so that the arterial and venous subsystems of circulation have coherence at cardiac frequency. This enables processes for diagnosing deficits of circulation that involve alterations in the transit of blood from the arterial to the venous subsystems of circulation. Furthermore, the discovery of cardiac frequency magnitude and phase organization enables the design and manufacture of lighter and more portable angiography equipment.

An ophthalmic apparatus that may include a processor; and a memory storing computer-readable instructions therein, the computer-readable instructions, when executed by the processor, causing the ophthalmic apparatus to perform: acquiring a two-dimensional tomographic image of the subjected eye; calculating a preoperative shape of the subjected eye based on a preoperative two-dimensional tomographic image of a preoperative subjected eye acquired by the acquiring of the two-dimensional tomographic image; calculating a postoperative shape of the subjected eye based on a postoperative two-dimensional tomographic image of a postoperative subjected eye acquired by the acquiring of the two-dimensional tomographic image; and calculating a displacement amount between a first reference axis obtained from the preoperative two-dimensional tomographic image of the preoperative subjected eye and a second reference axis obtained from the postoperative two-dimensional tomographic image of the postoperative subjected eye, based on the calculated preoperative shape and the calculated postoperative shape.

An image analysis apparatus includes a processor including hardware. The processor extracts parts from each of a first image and a second image acquired after the first image, each of the extracted parts including an annular peripheral portion and a central portion having a color different from a color of the peripheral portion. The processor also sets the central portion as the analysis object region and calculates a brightness decrease degree of the analysis object region in the second image relative to the analysis object region in the first image.