Search for dissertations about: "image processing application"

Showing result 1 - 5 of 204 swedish dissertations containing the words image processing application.

  2. 1. Adapting Deep Learning for Microscopy: Interaction, Application, and Validation

    Author : Ankit Gupta; Carolina Wählby; Ida-Maria Sintorn; Ola Spjuth; Andreas Hellander; Philip Kollmannsberger; Uppsala universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Deep Learning; Microscopy; Human-in-the-Loop; Semi-Supervised Learning; Application-Specific Analysis; Image Classification; Image-to-Image Translation; Template Matching; Computerized Image Processing; Datoriserad bildbehandling;

    Abstract : Microscopy is an integral technique in biology to study the fundamental components of life visually. Digital microscopy and automation have enabled biologists to conduct faster and larger-scale experiments with a sharp increase in the data generated. READ MORE

  4. 2. Image Filtering Methods for Biomedical Applications

    Author : M. Khalid Khan Niazi; Ewert Bengtsson; Ingela Nyström; Lucas J. van Vliet; Uppsala universitet; []
    Keywords : 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;

    Abstract : 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. READ MORE

  5. 3. Inverse problems in signal processing : Functional optimization, parameter estimation and machine learning

    Author : Pol del Aguila Pla; Joakim Jaldén; Yonina C. Eldar; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; inverse problems; signal processing; machine learning; biomedical imaging; optimization; proximal optimization; regularization; mathematical modeling; identifiability; likelihood; logconcavity; immunoassays; convolutional coding; functional analysis; abstract inference; learned iterations; unrolled algorithms; Electrical Engineering; Elektro- och systemteknik;

    Abstract : Inverse problems arise in any scientific endeavor. Indeed, it is seldom the case that our senses or basic instruments, i.e., the data, provide the answer we seek. READ MORE

  6. 4. Image processing on optimal volume sampling lattices : Thinking outside the box

    Author : Elisabeth Schold Linnér; Robin Strand; Ewert Bengtsson; Alexandre Falcão; Uppsala universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; BCC; FCC; aliasing; distance transform; segmentation; Computerized Image Processing; Datoriserad bildbehandling;

    Abstract : This thesis summarizes a series of studies of how image quality is affected by the choice of sampling pattern in 3D. Our comparison includes the Cartesian cubic (CC) lattice, the body-centered cubic (BCC) lattice, and the face-centered cubic (FCC) lattice. READ MORE

  7. 5. Automated Tissue Image Analysis Using Pattern Recognition

    Author : Jimmy Azar; Anders Hast; Ewert Bengtsson; Martin Simonsson; Marco Loog; Uppsala universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; tissue image analysis; pattern recognition; digital histopathology; immunohistochemistry; paired antibodies; histological stain evaluation; Computerized Image Processing; Datoriserad bildbehandling;

    Abstract : Automated tissue image analysis aims to develop algorithms for a variety of histological applications. This has important implications in the diagnostic grading of cancer such as in breast and prostate tissue, as well as in the quantification of prognostic and predictive biomarkers that may help assess the risk of recurrence and the responsiveness of tumors to endocrine therapy. READ MORE