Provided is a highly reliable technique for the evaluation of ischemic conditions. A preferred embodiment is a nuclear medicine measurement protocol in which the administration of a radiopharmaceutical agent and radiation measurement are performed twice at rest and under stress. In the nuclear medicine measurement protocol, radiation collection is performed without radiopharmaceutical agent administration before the second radiopharmaceutical agent administration, and the result is used to correct the nuclear medicine measurement result after the second radiopharmaceutical agent administration.

Provided is a novel technique for quantitatively evaluating tracer accumulation for nuclear medicine examinations of the heart. In a preferred embodiment, the radiation count information obtained by myocardial nuclear medicine measurement is normalized using a value relating to the size of the heart. In a preferred embodiment, the pixel value of each pixel of myocardial nuclear medicine image data is converted into standardized uptake values (SUV) capable of being represented by [SUV=Tissue radioactivity concentration/(Administered radiation dose/Value relating to size of heart)]. The value relating to the size of the heart may be a myocardial weight, for example.

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 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.

Apparatus and methods are described including, using a computer processor, automatically identifying whether a given pixel within an image corresponds to a portion of an object. A set of concentric circles that are disposed around the pixel are sampled, and a first function is applied to each of the circles such that the circles are defined by a first set of rotationally invariant descriptors. A second function is applied to the set of circles to generate a second set of descriptors, each of which represents a difference between respective pairs of the circles. A third function is applied such that the second set of descriptors becomes rotationally invariant. The processor identifies whether the given pixel corresponds to the portion of the object, based upon the first and second sets of rotationally invariant descriptors. Other applications are also described.

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, 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.

Systems and methods for analyzing pathologies utilizing quantitative imaging are presented herein. Advantageously, the systems and methods of the present disclosure utilize a hierarchical analytics framework that identifies and quantify biological properties/analytes from imaging data and then identifies and characterizes one or more pathologies based on the quantified biological properties/analytes. This hierarchical approach of using imaging to examine underlying biology as an intermediary to assessing pathology provides many analytic and processing advantages over systems and methods that are configured to directly determine and characterize pathology from underlying imaging data.

The present application provides quinoline-3-carboxamide compounds covalently linked to a label for use in the diagnosis of an inflammatory disease at local site. The above mentioned compounds can be used to detect or image accumulation of S100A9 in the body of a subject at sites of inflammation, using in vivo non-invasive molecular imaging techniques for the detection of said compounds. Accordingly, labeled quinoline-3-carboxamide compounds can be applied to evaluate the risk of a subject of developing an inflammatory disease and to follow the progress of the disease.

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, 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.

There is provided a system for determining the state of dementia by using an image differentiation technique and a cognitive test score together with each other.

A system includes: a first input module configured to acquire a first evaluation index based on data regarding the physical state of a brain of a subject; a second input module configured to acquire a second evaluation index based on data regarding the function of the brain of the subject; and an estimation module configured to estimate the state of dementia of the subject based on an evaluation value obtained by a first evaluation function having the first evaluation index and the second evaluation index as its variables.

A method of forming a probability map is disclosed. According to one embodiment, a method may include: (1) obtaining multiple measures of multiple imaging parameters for every stop of a moving window on an image, wherein two neighboring ones of the stops of the moving window are partially overlapped with each other; (2) obtaining first probabilities of an event for the stops of the moving window by matching the measures of the imaging parameters to a classifier; and (3) obtaining second probabilities of the event for multiple voxels of a probability map based on information associated with the first probabilities.