Sökning: "Expectation-Maximization algorithm"

Visar resultat 1 - 5 av 28 uppsatser innehållade orden Expectation-Maximization algorithm.

1. 1. Effects of reconstruction parameters on the image quality and quantification of PET images from PET/MRI and PET/CT systems

   Master-uppsats,

   Författare :Ali Amena Hussain; [2022-03-09]
   Nyckelord :Medical physics; PET CT; PET MRI; OSEM; BPL; NEMA IQ; positron emission tomography; magnetic resonance imaging; computed tomography; ordered Subset Expectation Maximization; The Bayesian Penalized Likelihood;

   Sammanfattning : 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. LÄS MER

3. 2. Spatiotemporal PET reconstruction with Learned Registration

   Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Pierre Meyrat; [2022]
   Nyckelord :PET; Tomographic reconstruction; Deep Learning; MLEM; PET; Tomografisk rekonstruktion; Deep Learning; MLEM;

   Sammanfattning : 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. LÄS MER

4. 3. Fault Clustering With Unsupervised Learning Using a Modified Gaussian Mixture Model and Expectation Maximization

   Master-uppsats, Linköpings universitet/Fordonssystem

   Författare :Kevin Lindström; [2021]
   Nyckelord :;

   Sammanfattning : 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. LÄS MER

5. 4. An Analysis of Markov Regime-Switching Models for Weather Derivative Pricing

   Kandidat-uppsats, Linköpings universitet/Tillämpad matematik; Linköpings universitet/Tekniska fakulteten

   Författare :Fredrik Gerdin Börjesson; [2021]
   Nyckelord :Weather derivatives; temperature modeling; Markov switching models; Lévy processes; expectation-maximization algorithm; generalized hyperbolic distributions; Monte Carlo simulation;

   Sammanfattning : 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. LÄS MER

7. 5. Implementing and Evaluating sparsification methods in probabilistic networks

   Kandidat-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Oskar Dahlin; [2020]
   Nyckelord :;

   Sammanfattning : 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. LÄS MER