A feature value related to a positional relationship between a vortex vein position and a characteristic point on a fundus image is computed. The image processing method provided includes a step of analyzing a choroidal vascular image and estimating a vortex vein position, and a step of computing a feature value indicating a positional relationship between the vortex vein position and a position of a particular site on a fundus.

A system and method for generating a parametric map of a subject's brain includes receiving non-contrast computed tomography (NCCT) imaging data and receiving computed tomography perfusion (CTP) data. The method further includes creating a baseline image by utilizing the NCCT data and generating a parametric map using the CTP data and the baseline image.

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, perform computational fluid dynamics analysis, facilitate assessment of risk of heart disease and coronary artery disease, enhance drug development, determine a CAD risk factor goal, provide atherosclerosis and vascular morphology characterization, and determine indication of myocardial risk, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

Provided are methods for estimating a Reserve Strength Ratio in a segment of a blood vessel or a lymphatic vessel. In some embodiments, the methods include providing a multiphase Digital Imaging and Communications in Medicine (DICOM) stack of computed tomography (CT) or magnetic resonance (MR) images of a blood vessel or a lymphatic vessel to software, wherein the stack of DICOM images is organized by phase; providing the output from the software to a Model Segmentation procedure in which the first phase of the DICOM stack (1st phase) is segmented to create the Geometric Model and finite element mesh of the 1st phase and a map of Local Thickness Measure; uploading a mesh created for the first phase onto the DICOM image volume; mapping each voxel position of the mesh for the first phase to all the subsequent meshes using an optical flow (OF) algorithm; creating deformed meshes at all phases from the maps of displaced nodes; estimating local curvature at each node location for all the phases using a finite difference method; evaluating the local deformation at each phase from the meshes corresponding to all the phases using an element approach; calculating local thickness at each node for all the phases using the deformation calculation at each phase and the thickness measured at the first phase and using the assumption of incompressibility for the aortic wall; and calculating the local principal stresses for each element from an extension of Laplace's equation applied to the local principal directions of curvatures, whereby the Reserve Strength Ratio in a segment of a blood vessel or a lymphatic vessel is estimated. Also provided are methods for predicting an increased risk of rupture of a blood vessel or a lymphatic vessel, methods for identifying subjects as being at risk for rupture of a blood vessel or a lymphatic vessel, and computer program products with computer executable instructions embodied in computer readable medium for performing the methods disclosed herein.

Apparatus and methods are described including placing at least a portion of a blood sample within a sample chamber (52), and acquiring microscopic images of the portion of the blood sample. Candidates of a given entity within the blood sample are identified, within the microscopic image. At least some of the candidates as being the given entity are validated, by performing further analysis of the candidates. A count of the candidates of the given entity is compared to a count of the validated candidates of the given entity, and at least the portion of the sample is invalidated from being used for performing at least some measurements upon the sample, at least partially based upon a relationship between the count of candidates and the count of validated candidates. Other applications are also described.

Techniques for label-free determination of a value of at least one blood property are presented. The techniques may utilize a device that includes an optical objective including at least one lens, at least a first light source situated so as to provide light to a body part at a location that is off-center from a central axis of the objective, at least a first electronic detector situated to receive light gathered by the optical objective and generate image data, at least one electronic processor communicatively coupled to the first electronic detector, the at least one electronic processor configured to determine the value of the at least one blood property based at least in part on the image data, and an output interface communicatively coupled to the at least one electronic processor and configured to provide the value of the at least one blood property.

In accordance with embodiments of this disclosure, a computational simulation platform for assessing impact of coronary artery bypass grafting comprises a computer-implemented method that includes: generating patient-specific three-dimensional (3D) reconstructions of path lines for a patient's heart, ascending aorta, aortic arch, descending thoracic aorta, great vessels, coronary arteries and their major branches based on noninvasive imaging; performing virtual CABG by modifying the patient-specific 3D reconstructions to computationally add path lines for one or more bypass grafts; performing post-virtual CABG computational fluid dynamic (CFD) studies under computational resting and stress conditions; and assessing hemodynamic impact of virtual CABG on the resting and hyperemic flow of diseased native coronary arteries and virtual bypass grafts.

The present invention relates to the field of medical monitoring, and in particular non-contact monitoring of one or more physiological parameters in a region of a patient during surgery. Systems, methods, and computer readable media are described for generating a pulsation field and/or a pulsation strength field of a region of interest (ROI) in a patient across a field of view of an image capture device, such as a video camera. The pulsation field and/or the pulsation strength field can be generated from changes in light intensities and/or colors of pixels in a video sequence captured by the image capture device. The pulsation field and/or the pulsation strength field can be combined with indocyanine green (ICG) information regarding ICG dye injected into the patient to identify sites where blood flow has decreased and/or ceased and that are at risk of hypoxia.

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 time sequenced series of optical images of a patient is obtained at a rate faster than cardiac frequency, wherein the time sequenced series of images capture one or more physical properties of intrinsic contrast. A cross-correland signal from the patient is obtained. A cross-correlated wavelet transform analysis is applied to the time sequenced series of optical images to yield a spatiotemporal representation of cardiac frequency phenomena. The cross-correlated wavelet transform analysis comprises performing a wavelet transform on the time-sequenced series of optical images to obtain a wavelet transformed signal, cross-correlating the wavelet transformed signal with the cross-correland signal to obtain a cross-correlated signal, filtering the cross-correlated signal at cardiac frequency to obtain a filtered signal, and performing an inverse wavelet transform on the filtered signal to obtain a spatiotemporal representation of the time sequenced series of optical images. Images of the cardiac frequency phenomena are generated.