Sökning: "image registration"

Visar resultat 1 - 5 av 100 avhandlingar innehållade orden image registration.

  1. 1. Image Filtering Methods for Biomedical Applications

    Detta är en avhandling från Uppsala : Acta Universitatis Upsaliensis

    Författare :M. Khalid Khan Niazi; Uppsala universitet.; Uppsala universitet.; [2011]
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Digital image analysis; Image filtering; Intensity inhomogeneity correction; Empirical mode decomposition; Particle Swarm optimization; Image registration; Computerized Image Processing; Datoriserad bildbehandling;

    Sammanfattning : Filtering is a key step in digital image processing and analysis. It is mainly used for amplification or attenuation of some frequencies depending on the nature of the application. Filtering can either be performed in the spatial domain or in a transformed domain. LÄS MER

  2. 2. Robust Image Registration for Improved Clinical Efficiency Using Local Structure Analysis and Model-Based Processing

    Detta är en avhandling från Linköping : Linköping University Electronic Press

    Författare :Daniel Forsberg; Linköpings universitet.; Linköpings universitet.; Linköpings universitet.; [2013]
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Image registration; deformable models; scoliosis; visualization; volume rendering; adaptive regularization; GPGPU; CUDA;

    Sammanfattning : Medical imaging plays an increasingly important role in modern healthcare. In medical imaging, it is often relevant to relate different images to each other, something which can prove challenging, since there rarely exists a pre-defined mapping between the pixels in different images. LÄS MER

  3. 3. Combining Shape and Learning for Medical Image Analysis

    Detta är en avhandling från Gothenburg : Chalmers tekniska högskola

    Författare :Jennifer Alvén; [2020]
    Nyckelord :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;

    Sammanfattning : 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. LÄS MER

  4. 4. A Multidimensional Filtering Framework with Applications to Local Structure Analysis and Image Enhancement

    Detta är en avhandling från Institutionen för medicinsk teknik

    Författare :Björn Svensson; Hans Knutsson; Mats Andersson; Oleg Burdakov; Abhir Bhalerao; [2008]
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Medical image science; multidimensional filtering; image enhancement; image registration; image segmentation; filter networks; graphics processing units GPU ; TECHNOLOGY Other technology Medical engineering; TEKNIKVETENSKAP Övriga teknikvetenskaper Medicinsk teknik;

    Sammanfattning : Filtering is a fundamental operation in image science in general and in medical image science in particular. The most central applications are image enhancement, registration, segmentation and feature extraction. LÄS MER

  5. 5. Improving Multi-Atlas Segmentation Methods for Medical Images

    Detta är en avhandling från Gothenburg : Chalmers tekniska högskola

    Författare :Jennifer Alvén; [2017]
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Supervised learning; semantic segmentation; multi-atlas segmentation; conditional random fields; label fusion; feature-based registration; image registration; random decision forests; convolutional neural networks; medical image segmentation;

    Sammanfattning : Semantic segmentation of organs or tissues, i.e. delineating anatomically or physiologically meaningful boundaries, is an essential task in medical image analysis. One particular class of automatic segmentation algorithms has proved to excel at a diverse set of medical applications, namely multi-atlas segmentation. LÄS MER