Thesis
Machine Learning for Biomedical Applications: From Crowdsourcing to Deep Learning
, 2017
Abstract
Aimed at improving machine learning algorithms by incorporating domain-specific knowledge, we develop a set of mathematical and technical methods that cope with different conditions of data abundance, reliable labels, and class balance. Proposed methods are evaluated for various biomedical applications, in particular, Tomographic Reconstruction and Noise Reduction in Cryo-Electron Tomography, Mitotic figure Detection in Breast Cancer Histology Images, and Visual Perception in Interventional Imaging.
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Cite (BibTeX)
@phdthesis{albarqouni2017machine,
author = {Albarqouni, Shadi},
school = {Technische Universität München},
title = {Machine Learning for Biomedical Applications: From Crowdsourcing to Deep Learning},
year = {2017}
}