Please use this identifier to cite or link to this item: http://hdl.handle.net/10609/82134
Title: Segmentación de núcleos celulares en imágenes de microscopía ayudados por redes neuronales convolucionales
Author: García Seisdedos, David
Tutor: Alférez, Santiago  
Others: Universitat Oberta de Catalunya
Abstract: The aim of this project is to develop a bioinformatics tool to detect and isolate cell nuclei. The developed model performs detection and segmentation in three steps. First, an initial segmentation of the raw image is carried out. Second, the fragments obtained are classified by means of a convolutional neural network (CNN) into three groups: mono-nuclei, poly-nuclei or non-nuclear artifacts. Third, the artifacts will be removed and the polynuclear fragments will be segmented and will be analyzed from the second step again. Thus, the main problem - accumulation of nuclei - is subdivided by recursiveness into simpler sub-problems.
Keywords: machine learning
convolutional neural network
microscopy
Document type: info:eu-repo/semantics/masterThesis
Issue Date: 2-Jul-2018
Publication license: http://creativecommons.org/licenses/by-nc-nd/3.0/es/  
Appears in Collections:Trabajos finales de carrera, trabajos de investigación, etc.

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