Search for dissertations about: "image processing feature"

Showing result 1 - 5 of 96 swedish dissertations containing the words image processing feature.

  2. 1. 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

  4. 2. 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

  5. 3. Image and Data Analysis for Biomedical Quantitative Microscopy

    Author : Damian J. Matuszewski; Ida-Maria Sintorn; Carolina Wählby; Peter Horvath; Uppsala universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; high-content screening; drug selection; DNA content histogram; manual image annotation; deep learning; convolutional neural networks; hardware integration; Computerized Image Processing; Datoriserad bildbehandling;

    Abstract : This thesis presents automatic image and data analysis methods to facilitate and improve microscopy-based research and diagnosis. New technologies and computational tools are necessary for handling the ever-growing amounts of data produced in life science. READ MORE

  6. 4. 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

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

    Author : Jennifer Alvén; Chalmers tekniska högskola; []
    Keywords : 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;

    Abstract : 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. READ MORE