Essays about: "Expectation Maximization algorithm."
Showing result 1 - 5 of 28 essays containing the words Expectation Maximization algorithm..
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1. Effects of reconstruction parameters on the image quality and quantification of PET images from PET/MRI and PET/CT systems
University essay fromAbstract : Aim: To study how reconstruction parameters affect the positron emission tomography (PET) image quality and quantitative results for the different lesion to background radioactivity ratios in three different PET systems. Introduction: Multimodality imaging that combines magnetic resonance imaging (MRI) or computed tomography (CT) with a PET system can produce medical images containing both functional and anatomical information. READ MORE
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2. Spatiotemporal PET reconstruction with Learned Registration
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Because of the long acquisition time of Positron Emission Tomography scanners, the reconstructed images are blurred by motion. We hereby propose a novel motion-correction maximum-likelihood expectation-maximization algorithm integrating 3D movements between the different gates estimated by a neural network trained on synthetic data with contrast invariance. READ MORE
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3. Fault Clustering With Unsupervised Learning Using a Modified Gaussian Mixture Model and Expectation Maximization
University essay from Linköpings universitet/FordonssystemAbstract : When a fault is detected in the engine, the check engine light will come on. After that, it is often up to the mechanic to diagnose the engine fault. Manual fault classification by a mechanic can be time-consuming and expensive. READ MORE
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4. An Analysis of Markov Regime-Switching Models for Weather Derivative Pricing
University essay from Linköpings universitet/Tillämpad matematik; Linköpings universitet/Tekniska fakultetenAbstract : The valuation of weather derivatives is greatly dependent on accurate modeling and forecasting of the underlying temperature indices. The complexity and uncertainty in such modeling has led to several temperature processes being developed for the Monte Carlo simulation of daily average temperatures. READ MORE
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5. Implementing and Evaluating sparsification methods in probabilistic networks
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : Most queries on probabilistic networks assume a possible world semantic, which causes an exponential increase in execution time. Deterministic networks can apply sparsification methods to reduce their sizes while preserving some structural properties, but there have not been any equivalent methods for probabilistic networks until recently. READ MORE
