Now showing items 1-6 of 6

  • Categorical embedding with Deep Learning.

    Η.Μ.U, School of Engineering (ScENG), Electrical and Computer Engineering Dept
    Authors: Giannakos, Iakovos
    Thesis advisor: Tsiknakis, Emmanouil; Koumakis, Eleftherios; Marias, Konstantinos
    Publication Date: 2021-02-04
    The study conducted in the framework of the dissertation on "Categorical embedding with deep learning". To clarify, the purpose of the dissertation is to study and implement a word-embedding neural network for genomic data ...
  • Categorization of medical images with modern techniques of visual and image processing methods.

    Η.Μ.U, School of Engineering (ScENG), Electrical and Computer Engineering Dept
    Authors: Melissianos, Vasileios
    Thesis advisor: Marias, Konstantinos
    Publication Date: 2020-05-07
    Mammogram-based diagnosis of breast cancer is hard especially in high tissue density areas of the breast. In addition, Additionally, breast density type has been linked with increased risk of breast cancer calling for ...
  • Texture kinetics and multiscale texture analysis for predicting breast cancer treatment response.

    Η.Μ.U, School of Engineering (ScENG), Electrical and Computer Engineering Dept
    Authors: Skepasianos, Iraklis
    Thesis advisor: Marias, Konstantinos
    Publication Date: 2020-03-31
    Evaluation of tumor response has been extensively investigated using a wide variety of manual and computer assisted methods. Oncologists are using the Response evaluation criteria in solid tumors (RECIST) and World Health ...
  • Gene expression analysis using deep learning.

    Η.Μ.U, School of Engineering (ScENG), Electrical and Computer Engineering Dept
    Authors: Panagiotakis, Georgios
    Thesis advisor: Marias, Konstantinos
    Publication Date: 2021-05-11
    The present work outlines the basic aspects of artificial intelligence in the field of bioinformatics and in particular the use of neural networks for the analysis of gene expressions. In the first stage, introductory ...
  • Signal quantification from florescent histopathological images and machine learning applications for their categorization.

    Η.Μ.U, School of Engineering (ScENG), Electrical and Computer Engineering Dept
    Authors: Papagiannakis, Stylianos
    Thesis advisor: Marias, Konstantinos
    Publication Date: 2024-01-16
    The quantification and categorization of fluorescence images constitutes a challenging goal nowadays due to the lack of a specific software. Clinicians are required to manually select and delineate regions of interest in ...
  • Comparison of radiomics image analysis software.

    Η.Μ.U, School of Engineering (ScENG), Electrical and Computer Engineering Dept
    Authors: Markodimitrakis, Emmanouil
    Thesis advisor: Marias, Konstantinos
    Publication Date: 2020-11-16
    Radiomics techniques have revolutionized medical image processing, as they have the ability to export large numbers texture and shape characteristics with the ultimate goal, accurate diagnosis, segmentation and categorization ...