Search for dissertations about: "thesis in medical statistics"

Showing result 11 - 15 of 426 swedish dissertations containing the words thesis in medical statistics.

  2. 11. Statistical assessment of genomic variability in tumours and bacterial communities

    Author : Anna Rehammar; Chalmers tekniska högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; somatic mutations; hierarchical Bayesian modelling; cancer genetics; high-throughput sequencing; metagenomics; personalised diagnostics;

    Abstract : Current high-throughput DNA sequencing technologies have the ability to generate large amounts of high-resolution genomic data. The high dimensionality in combination with the substantial levels of technical errors and biological variability typically present in the data make, however, the analysis challenging. READ MORE

  4. 12. Wastewater discharges and microbial variability in a surface water source

    Author : Johan Åström; Chalmers tekniska högskola; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; faecal indicators; pathogens; drinking-water; microbial risk assessment; variability; rainfall; catchment; wastewater; surface water; Hazardous events;

    Abstract : Planning for drinking-water safety in surface waters includes a systematic assessment of hazards in the catchment, and microbial contamination is considered a major health risk. The aim of this thesis was to identify and characterize microbial hazardous events reported for River Göta älv, Sweden. READ MORE

  5. 13. Combining Shape and Learning for Medical Image Analysis

    Author : Jennifer Alvén; Chalmers tekniska högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; feature-based registration; convolutional neural networks; conditional random fields; medical image segmentation; random decision forests; machine learning; multi-atlas segmentation; medical image registration; shape models;

    Abstract : Automatic methods with the ability to make accurate, fast and robust assessments of medical images are highly requested in medical research and clinical care. Excellent automatic algorithms are characterized by speed, allowing for scalability, and an accuracy comparable to an expert radiologist. READ MORE

  6. 14. Maximum likelihood estimation in signal analysis of MR spectroscopy

    Author : Pia Löthgren; Sveriges lantbruksuniversitet; Sveriges lantbruksuniversitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES;

    Abstract : Proton magnetic resonance spectroscopy (MRS) is used to determine the concentration of metabolites in organic tissues, or to study metabolic changes in a non-invasive way. The complex-valued magnetic resonance spectroscopy signals are assumed to be disturbed by additive white noise. READ MORE

  7. 15. The PET sampling puzzle : intelligent data sampling methods for positron emission tomography

    Author : Klara Leffler; Jun Yu; Ida Häggström; Zhiyong Zhou; Saikat Chatterjee; Umeå universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; sparse signal processing; compressed sensing; Poisson denoising; positron emission tomography PET ; sinogram denoising; sinogram inpainting; deep learning; matematisk statistik; Mathematical Statistics;

    Abstract : Much like a backwards computed Sudoku puzzle, starting from the completed number grid and working ones way down to a partially completed grid without damaging the route back to the full unique solution, this thesis tackles the challenges behind setting up a number puzzle in the context of biomedical imaging. By leveraging sparse signal processing theory, we study the means of practical undersampling of positron emission tomography (PET) measurements, an imaging modality in nuclear medicine that visualises functional processes within the body using radioactive tracers. READ MORE