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Ensemble of Deep Convolutional Neural Networks with Monte Carlo Dropout Sampling for Automated Image Segmentation Quality Control and Robust Deep Learning Using Small Datasets

Recent progress on deep learning (DL)-based medical image segmentation can enable fast extraction of clinical parameters for efficient clinical workflows. However, current DL methods can still fail and require manual visual inspection of outputs, which is time-consuming and diminishes the advantages of automation. For clinical applications, it is essential to develop DL approaches that can not onl

Impact of Drinking Water Treatment and Pipe Biofilms on Bacterial Dynamics in the Distribution System

This thesis addresses drinking water quality and microbiology in full-scale drinking water distribution systems (DWDSs). It examines how UV irradiation and slow sand filters (SSFs) alter the water bacteriome, and how the biofilm in the DWDS affects the drinking water quality.In addition, the effects of installing a combined ultra­filtration and coagulation treatment stage on the pipe biofilm com­m

Hybrid model of an evaporative gas turbine power plant utilizing physical models and artificial neural networks

Traditionally, when process identification, monitoring and diagnostics are carried out for power plants and engines, physical modeling such as heat and mass balances, gas path analysis, etc. is utilized to keep track of the process. This type of modeling both requires and provides considerable knowledge of the process. However, if high accuracy of the model is required, this is achieved at the exp

Hyperpolarized MRI, functional MRI, MR spectroscopy and CEST to provide metabolic information in vivo

Access to metabolic information in vivo using magnetic resonance (MR) technologies has generally been the niche of MR spectroscopy (MRS) and spectroscopic imaging (MRSI). Metabolic fluxes can be studied using the infusion of substrates labeled with magnetic isotopes, with the use of hyperpolarization especially powerful. Unfortunately, these promising methods are not yet accepted clinically, where

Comparison of short axis and long axis acquisitions of T1 and extracellular volume mapping using MOLLI and SASHA in patients with myocardial infarction and healthy volunteers

Background: Although previous studies have examined the impact of slice position in volumetric measurements in Cardiovascular Magnetic Resonance (CMR) imaging, very limited data are available today comparing T1 and Extra-Cellular Volume (ECV) measurements from short and long axis acquisitions. The purpose of this study was to investigate the impact of slice position and orientation on T1 and ECV m

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https://www.lu.se/sites/www.lu.se/files/11fc6802.pdf - 2026-05-14