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 quantitative method for nuclear medicine heart image and an electronic device are provided. The method is adapted for multi-pinhole SPECT images or SPECT/CT images. The method includes a radionuclide physical decay correction, a scatter correction, a geometry distortion correction, a data truncation compensation, a tissue attenuation correction, an image space resolution recovery, a noise removal, a pixel value conversion, a myocardial blood flow quantitative calculation, an intra-scan patient movement correction and a blood flow condition evaluation. Accordingly, a quantitative SPECT reconstructed image of a heart is obtained, and an absolute quantization of the myocardial blood flow is calculated to measure the myocardial blood flow quantitatively according to the quantitative SPECT reconstructed image. In addition, a blood flow condition diagram according to a number of indicators is established, and a myocardial blood flow condition is evaluated according to a quantization result of myocardial blood flow and the blood flow condition diagram.

Systems and methods for scanning near infrared (NIR) and visible light images and creating co-registered images are provided. A system can include a visible light image capturing device, an near infrared image capturing device, a housing unit, a light source configured to emit light at multiple wavelengths, and a processor configured to use image segmentation algorithms to measure a target issue or wound, detect hemodynamic signals, and combine the visible light image and a hemodynamic image to create a single image.

A method for analyzing digital holographic microscopy (DHM) data for hematology applications includes receiving a plurality of DHM images acquired using a digital holographic microscopy system. One or more connected components are identified in each of the plurality of DHM images and one or more training white blood cell images are generated from the one or more connected components. A classifier is trained to identify a plurality of white blood cell types using the one or more training white blood cell images. The classifier may be applied to a new white blood cell image to determine a plurality of probability values, each respective probability value corresponding to one of the plurality of white blood cell types. The new white blood cell image and the plurality of probability values may then be presented in a graphical user interface.

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 CT-based clinical decision support system provides coronary decision support. With or without CT-FFR, a machine learnt predictor predicts the clinical decision for the patient based on input from various sources. Using the machine learnt predictor provides more consistent and comprehensive consideration of the available information. The clinical decision support may be provided prior to review of coronary CT data by a radiologist and/or treating physician, providing a starting point or recommendation that may be used by the radiologist and/or treating physician.

Methods and systems are provided for assessing the presence of functionally significant stenosis in one or more coronary arteries, further known as a severity of vessel obstruction. The methods and systems can implement a prediction phase that comprises segmenting at least a portion of a contrast enhanced volume image data set into data segments corresponding to wall regions of the target organ, and analyzing the data segments to extract features that are indicative of an amount of perfusion experiences by wall regions of the target organ. The methods and systems can obtain a feature-perfusion classification (FPC) model derived from a training set of perfused organs, classify the data segments based on the features extracted and based on the FPC model, and provide, as an output, a prediction indicative of a severity of vessel obstruction based on the classification of the features.

A medical imaging system configured to link acquired images to markers or tags on an anatomical illustration, based, at least in part on spatial and anatomical data associated with the acquired image. The medical imaging system may be further configured to generate a diagnostic report including the anatomical illustration containing the markers. The diagnostic report may allow a user to select a marker to view information associated with an acquired image and/or the acquired image. Multiple images may be associated with a marker, and/or multiple markers may be associated with an image. A set of 2D and/or 3D anatomical illustrations may be generated which contains markers from multiple diagnostic reports and updated automatically for an individual patient's anatomical model by the application to reflect measurements and/quantitative findings related to organ, tissue, and vessel size, location, deformation, and/or obstruction.

An apparatus that senses temperature from a digital infrared sensor is described. A digital signal representing a temperature without conversion from analog is transmitted from the digital infrared sensor received by a microprocessor and converted to body core temperature by the microprocessor.

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.