Digital image analysis of cells and computational tools for the study of mechanism of RSV entry to human bronchial epithelium

Respiratory Syncytial Virus (RSV) is one of the pathogens with the highest prevalence in upper and lower respiratory tract infections. The available information about the epidemiology of this virus in our environment is limited and its knowledge is very important to plan or carry out preventive and / or therapeutic interventions. The objective of this research is to perform a morphological characterization and statistical analysis that contribute to explain the heterogeneity of the RSV infection, using digital image processing and computational tools. The main results of this work are: * A framework for software development applied to cell image analysis, which includes a Spiral-based model and their techniques and artifacts. This methodology allows incorporating the step of the spiral methodology to the stages of digital image processing. * A new method for cell segmentation in fluorescence microscopy images. The proposed approach combines the well-known Marker-Controlled Watershed algorithm (MC-Watershed) with a new method of two-step based on Watershed (SM-Watershed). * A statistical analysis to determine the existence of correlation between morphological features and the presence of viral infection concluding that the predictors (Size, circularity, edge and LCD) do not determine the infection (although they are slightly associated with it).

• Autores: Gamarra Acosta, Margarita Rosa
• Tipo de recurso: Doctoral thesis
• Fecha de publicación: 2019
• Institución: Universidad del Norte
• Repositorio: Repositorio Uninorte
• Idioma: eng
• OAI Identifier: oai:manglar.uninorte.edu.co:10584/13329
• Acceso en línea: http://hdl.handle.net/10584/13329
• Palabra clave: Ingeniería de software; Programación de sistemas (Computadores); Procesamiento de imágenes -- Técnicas digitales; Medicina -- Procesamiento de datos
• Rights: openAccess
• License: https://creativecommons.org/licenses/by/4.0/