Papadakis, Emanuel I.2017-06-232017-06-23December 22015-12December 2Portions of this document appear in: B. Ozcan, D. Labate, D. Jimenez, and M. Papadakis, "Directional and non-directional representations for the characterization of neuronal morphology," Wavelets XV (2013), SPIE Proc. 8858. doi:10.1117/12.2024777. Copyright 2013 Society of Photo Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, or modification of the contents of the publication are prohibited. B. Ozcan, P. Negi, F. Laezza, M. Papadakis, and D. Labate, "Automated detection of soma location and morphology in neuronal network cultures," PLoS ONE 10(4): e0121886 (2015). doi:10.1371/journal.pone.0121886 D. Labate, F. Laezza, P. Negi, B. Ozcan, and M. Papadakis, "Efficient processing of fluorescence images using directional multiscale representations," Mathematics Modelling of Natural. Phenomena 9(5) (2014): 177-193. doi:10.1051/mmnp/20149512http://hdl.handle.net/10657/1829Recent advances in high-resolution fluorescence microscopy have enabled the system- atic study of morphological changes in large populations of cells induced by chemical and genetic perturbations, facilitating the discovery of signaling pathways underlying diseases and the development of new pharmacological treatments. In these studies, though, quantifi- cation and analysis of morphological features are for the vast majority processed manually, slowing data processing significantly and limiting the information gained to a descriptive level. As an example, automated identification of the primary components of a neuron and extraction of its features are essential steps in many quantitative studies of neuronal net- works. Recent advances in applied harmonic analysis, especially in the area of multiscale representations, offer a variety of techniques and ideas which have potential to impact this field of scientific investigation. Motivated by the properties of directional multiscale rep- resentations, the focus of this thesis is to introduce a new notion, directional ratio, which is a multiscale quantitative measure, capable of distinguishing isotropic from anisotropic structures and the characterization of local isotropy. Another part of the dissertation illustrates the application of directional ratio. In partic- ular, we present an algorithm for automated soma extraction and separation of contiguous somas. Our numerical experiments show that this approach is reliable and efficient to detect and segment somas.application/pdfengThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. UH Libraries has secured permission to reproduce any and all previously published materials contained in the work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).Image analysisSoma SegmentationDirectional ratioNeuronal morphology2017-06-23Thesisborn digital