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Quantification of brain glucose metabolism by 18F-FDG PET with real-time arterial and image-derived input function in mice

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Cardiac output

In cardiac physiology, cardiac output (CO), also known as heart output and often denoted by the symbols , , or , is the volumetric flow rate of the heart's pumping output: that is, the volume of blood being pumped by a single ventricle of the heart, per unit time (usually measured per minute). Cardiac output (CO) is the product of the heart rate (HR), i.e. the number of heartbeats per minute (bpm), and the stroke volume (SV), which is the volume of blood pumped from the left ventricle per beat; thus giving the formula: Values for cardiac output are usually denoted as L/min.

Oxygen-18

Oxygen-18 (18O, Ω) is a natural, stable isotope of oxygen and one of the environmental isotopes. 18O is an important precursor for the production of fluorodeoxyglucose (FDG) used in positron emission tomography (PET). Generally, in the radiopharmaceutical industry, enriched water (H218O) is bombarded with hydrogen ions in either a cyclotron or linear accelerator, producing fluorine-18. This is then synthesized into FDG and injected into a patient. It can also be used to make an extremely heavy version of water when combined with tritium (hydrogen-3): 3H218O or T218O.

Principal component analysis

Principal component analysis (PCA) is a popular technique for analyzing large datasets containing a high number of dimensions/features per observation, increasing the interpretability of data while preserving the maximum amount of information, and enabling the visualization of multidimensional data. Formally, PCA is a statistical technique for reducing the dimensionality of a dataset. This is accomplished by linearly transforming the data into a new coordinate system where (most of) the variation in the data can be described with fewer dimensions than the initial data.

Pattern recognition

Pattern recognition is the automated recognition of patterns and regularities in data. While similar, pattern recognition (PR) is not to be confused with pattern machines (PM) which may possess (PR) capabilities but their primary function is to distinguish and create emergent pattern. PR has applications in statistical data analysis, signal processing, , information retrieval, bioinformatics, data compression, computer graphics and machine learning.

Machine learning

Machine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.

Deep learning

Deep learning is part of a broader family of machine learning methods, which is based on artificial neural networks with representation learning. The adjective "deep" in deep learning refers to the use of multiple layers in the network. Methods used can be either supervised, semi-supervised or unsupervised.

Coronary stent

A coronary stent is a tube-shaped device placed in the coronary arteries that supply blood to the heart, to keep the arteries open in the treatment of coronary heart disease. It is used in a procedure called percutaneous coronary intervention (PCI). Coronary stents are now used in more than 90% of PCI procedures. Stents reduce angina (chest pain) and have been shown to improve survival and decrease adverse events in an acute myocardial infarction. Similar stents and procedures are used in non-coronary vessels (e.

Softmax function

The softmax function, also known as softargmax or normalized exponential function, converts a vector of K real numbers into a probability distribution of K possible outcomes. It is a generalization of the logistic function to multiple dimensions, and used in multinomial logistic regression. The softmax function is often used as the last activation function of a neural network to normalize the output of a network to a probability distribution over predicted output classes, based on Luce's choice axiom.

Arteriovenous fistula

An arteriovenous fistula is an abnormal connection or passageway between an artery and a vein. It may be congenital, surgically created for hemodialysis treatments, or acquired due to pathologic process, such as trauma or erosion of an arterial aneurysm. Hereditary hemorrhagic telangiectasia is a condition where there is direct connection between arterioles and venules without intervening capillary beds, at the mucocutaneous region and internal bodily organs. Those who are affected by this conditions usually do not experience any symptoms.

Decision tree learning

Decision tree learning is a supervised learning approach used in statistics, data mining and machine learning. In this formalism, a classification or regression decision tree is used as a predictive model to draw conclusions about a set of observations. Tree models where the target variable can take a discrete set of values are called classification trees; in these tree structures, leaves represent class labels and branches represent conjunctions of features that lead to those class labels.