Application of fuzzy techniques to biomedical images
The main goal of this work is to bring together Fuzzy Logic techniques and Biomedical images analysis, linking this two fields through an image segmentation problem approached by a Fuzzy c-Means algorithm. This work has two main cores. The first one is a formal structural analysis of some Fuzzy Logi...
| Autor: | |
|---|---|
| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2012 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2099.1/15839 |
| Acceso en línea: | https://hdl.handle.net/2099.1/15839 |
| Access Level: | acceso abierto |
| Palabra clave: | Fuzzy logic Imaging systems in medicine Image processing--Digital techniques Lògica difusa Imatges mèdiques Imatges--Processament--Tècniques digitals Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial Àrees temàtiques de la UPC::Ciències de la salut::Medicina::Diagnòstic per la imatge |
| Sumario: | The main goal of this work is to bring together Fuzzy Logic techniques and Biomedical images analysis, linking this two fields through an image segmentation problem approached by a Fuzzy c-Means algorithm. This work has two main cores. The first one is a formal structural analysis of some Fuzzy Logic concepts within the theory of Indistinguishabilitty Operators. The main actors of this part will be indistinguishability operators, sets of extensional fuzzy subsets, upper approximation operators and lower approximation operators. All these concepts will be explained in depth further in this work. The second core is a practical application of the Fuzzy c-Means algorithm to segmentate biomedical images of mammographies and bone marrow microscopical captures. |
|---|