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End of Degree Project (TFG)   

 

2021

Design and implementation of a classification system for neuropathology microscopy images based on deep learning techniques (Ref: Neuro).

Microscopy images of the nervous system tissue are used to assist the diagnosis of disease. This Master Thesis addresses the design and development of a solution based on deep learning techniques to detect the presence of disease in these microscopy images. To that extend, an annotated database with images provided by the Hospital de Almería will be also created.

We are looking for students with experience with Python and Deep Learning Tools ( Keras, Tensorflow, PyTorch, …)

Contact person: Julián Cabrera, This email address is being protected from spambots. You need JavaScript enabled to view it.

 

Design and implementation of an annotation tool for echocardiograms to assist Kawasaki disease identification (Ref: Kawasaki).

The Kawasaki disease is the most common heart condition affecting young children, usually under five years old, in developed countries. The disease is responsible for the damages of blood vessels all over the body and results in vasculitis, myocarditis and coronary dilation causing long term heart complications. Therefore, it is essential to be able to detect the disease at an early state.

One of the methods used to detect Kawasaki disease is by the analysis of the echocardiograms of the heart. In the Grupo de Tratamiento de Imágenes we have already developed a platform to assist Kawasaki disease diagnosis. This Mater Thesis addresses the design and implementation of an annotation tool for the echocardiograms, and its integration with the platform.

This Master Thesis will be done in collaboration with Hospital 12 de Octubre.

We are looking for students with experience with Python. Experience with Deep Learning Tools ( Keras, Tensorflow, PyTorch, …) is a plus.

Contact person: Julián Cabrera, This email address is being protected from spambots. You need JavaScript enabled to view it.

 

Design and implementation of a multiview capture system (Ref: Multiview).

Free Viewpoint Video is an immersive multimedia system that provides the user the capability to move freely on a scene that is captured by a multiview set up of cameras. The objective of this Master Thesis is to design and develop a multiview capture system using IDS industrial cameras and their SW libraries.

We are looking for students with experience in C++ and Linux.

Contact person: Julián Cabrera, This email address is being protected from spambots. You need JavaScript enabled to view it.

 

2018

Análisis de estrategias de codificación para imágenes lightfield.

Análisis de las soluciones actuales para la codificación de imágenes lightfield/plenópticas, y posible adaptación de esquemas de compresión existentes a las características particulares de las imágenes capturadas por cámaras lightfield/plenópticas.

Herramientas / Entorno de programación: Matlab, software de codificadores existentes.

Para obtener más información contactar con Pablo Carballeira López 

   

Desarrollo de una herramienta con interfaz gráfica para el diseño de configuraciones de cámaras para vídeo Free Viewpoint.

Desarrollo de una herramienta software con interfaz gráfica basada en un modelo de percepción subjetiva de vídeo Free Viewpoint. El objetivo de esta herramienta es guiar el diseño de estructuras de cámaras para vídeo Super MultiView (SMV) y Free-Navigation (FN), mediante la aplicación de un modelo de percepción subjetiva de este tipo de vídeos.

Herramientas / Entorno de programación: C++, OpenCV, Qt.

Para obtener más información contactar con Pablo Carballeira López