Sökning: "Image segmentation"

Visar resultat 1 - 5 av 127 avhandlingar innehållade orden Image segmentation.

  1. 1. Automatic Virus Identification using TEM Image Segmentation and Texture Analysis

    Detta är en avhandling från Uppsala : Acta Universitatis Upsaliensis

    Författare :Gustaf Kylberg; Uppsala universitet.; Uppsala universitet.; [2014]
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; image analysis; image processing; virus identification; transmission electron microscopy; texture analysis; texture descriptors; Computerized Image Processing; Datoriserad bildbehandling;

    Sammanfattning : Viruses and their morphology have been detected and studied with electron microscopy (EM) since the end of the 1930s. The technique has been vital for the discovery of new viruses and in establishing the virus taxonomy. Today, electron microscopy is an important technique in clinical diagnostics. LÄS MER

  2. 2. Graph-based Methods for Interactive Image Segmentation

    Detta är en avhandling från Uppsala : Acta Universitatis Upsaliensis

    Författare :Filip Malmberg; Uppsala universitet.; Uppsala universitet.; [2011]
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Digital image analysis; Interactive image segmentation; Fuzzy image segmentation; Image foresting transform; Graph labeling; Graph cuts; Computerized Image Processing; Datoriserad bildbehandling;

    Sammanfattning : The subject of digital image analysis deals with extracting relevant information from image data, stored in digital form in a computer. A fundamental problem in image analysis is image segmentation, i.e., the identification and separation of relevant objects and structures in an image. LÄS MER

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

    Detta är en avhandling från ; Chalmers tekniska högskola; Gothenburg

    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

  4. 4. Segmentation Methods for Medical Image Analysis Blood vessels, multi-scale filtering and level set methods

    Detta är en avhandling från Linköping : Linköping University Electronic Press

    Författare :Gunnar Läthén; Linköpings universitet.; Linköpings universitet.; Linköpings universitet.; [2010]
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Image segmentation; Medical image analysis; Level set method; Quadrature filter; Multi-scale; TECHNOLOGY Information technology Image analysis; TEKNIKVETENSKAP Informationsteknik Bildanalys;

    Sammanfattning : Image segmentation is the problem of partitioning an image into meaningful parts, often consisting of an object and background. As an important part of many imaging applications, e.g. face recognition, tracking of moving cars and people etc, it is of general interest to design robust and fast segmentation algorithms. LÄS MER

  5. 5. Fast Methods for Vascular Segmentation Based on Approximate Skeleton Detection

    Detta är en avhandling från Uppsala : Acta Universitatis Upsaliensis

    Författare :Kristína Lidayová; Uppsala universitet.; Uppsala universitet.; [2017]
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; medical image analysis; automatic skeleton extraction; vascular segmentation; coverage segmentation; convolutional neural network classifier; CT angiography; Computerized Image Processing; Datoriserad bildbehandling;

    Sammanfattning : Modern medical imaging techniques have revolutionized health care over the last decades, providing clinicians with high-resolution 3D images of the inside of the patient's body without the need for invasive procedures. Detailed images of the vascular anatomy can be captured by angiography, providing a valuable source of information when deciding whether a vascular intervention is needed, for planning treatment, and for analyzing the success of therapy. LÄS MER