Please use this identifier to cite or link to this item:
Title: Análisis de la motilidad intestinal utilizando Convolutional Deep Neural Network y la cápsula endoscópica
Author: Martínez, Pablo (Martínez Martínez)
Director/Tutor: Seguí Mesquida, Santi
Keywords: Visió per ordinador
Reconeixement de formes (Informàtica)
Treballs de fi de grau
Processament digital d'imatges
Càpsula endoscòpica
Motilitat gastrointestinal
Xarxes neuronals (Informàtica)
Computer vision
Pattern recognition systems
Computer software
Bachelor's thesis
Digital image processing
Capsule endoscopy
Gastrointestinal motility
Neural networks (Computer science)
Issue Date: 27-Jun-2015
Abstract: Capsule endoscopy is a diagnostic technique that opens a wide field of research in the clinical area. Through the capsule, videos of the entire digestive tract can be obtained, as it is ingested by the patient. There are many projects related to the data extraction of these videos, one of them, a Convolutional Deep Neural Network which is able to classify images of the small intestine in six different classes. Nevertheless, since the v ́ıdeo is obtained until it's able to be processed by the Convolutional Deep Neural Network, a set of operations are needed. In the first part of this document, an approach to get this work done is proposed. In the second part, the results of the neural network are used to create an application that tries to find sequences in videos and segment the videos based on that sequences.
Note: Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2015, Director: Santi Seguí Mesquida
Appears in Collections:Treballs Finals de Grau (TFG) - Enginyeria Informàtica

Files in This Item:
File Description SizeFormat 
memoria.pdfMemòria12.11 MBAdobe PDFView/Open

This item is licensed under a Creative Commons License Creative Commons