Thesis

Doctoral Thesis: Deep learning methods for extraction of neuroimage markers in the prognosis of brain pathologies

By Albert Clèrigues Garcia Supervised by Dr. Xavier Lladó / Dr. Arnau Oliver / Dr. Sergi Valverde   Abstract This PhD thesis focuses on improving the extraction of neuroimage markers for the prognosis and outcome prediction of neurological pathologies such as ischemic stroke, Alzheimer’s disease (AD) and multiple sclerosis (MS)….

Doctoral Thesis: Underwater 3D Sensing using Structured Light: Development of an Underwater Laser Scanner and a Non-Rigid Point Cloud Registration Method

By Miguel Castillón Sánchez Supervised by Dr.Pere Ridao Rodríguez / Dr. Josep Forest Collado   Abstract Accurate underwater 3D perception is essential to advance towards the automation of expensive, dangerous and/or time-consuming tasks, such as the inspection, maintenance and repair of off-shore industrial sites. Accurate underwater 3D sensors can potentially have…

DOCTORAL THESIS: Automated 3D object recognition in underwater scenarios for manipulation

By Khadidja Himri Supervised by Dr.Pere Ridao / Dr.Nuno Gracias   Abstract In recent decades, the rapid development of intelligent vehicle and 3D scanning technologies has led to a growing interest in applications based on 3D point data processing, with many applications such as augmented reality or robot manipulation and obstacle…

DOCTORAL THESIS: Underwater Image-Based 3D Reconstruction With Quality Estimation

By Klemen Istenic Supervised by Dr.Rafael García Campos/ Dr.Ricardo Estrela Gracias   Abstract Despite the undeniable importance of the marine ecosystem, vast areas of the seabed remain largely unexplored. Accurate and detailed 3D models of the environment yield high added value to any marine survey, as such results convey immense information…

DOCTORAL THESIS: Deep learning for atrophy quantification in brain magnetic resonance imaging

By Jose Bernal Moyano Supervised by Dr. Arnau Oliver / Dr. Xavier Lladó   Abstract Cerebral atrophy is a neuroimaging feature of ageing and diverse brain pathologies that indicate of loss of neurons and their connections. Its quantification plays a fundamental role in neuroinformatics since it permits studying brain development, diagnosing brain…

DOCTORAL THESIS: Automatic segmentation of brain structures in magnetic resonance images using deep learning techniques

By Kaisar Kushibar Supervised by Dr. Sergi Valverde / Dr. Arnau Oliver / Dr. Xavier Lladó   Abstract The sub-cortical brain structures are located beneath the cerebral cortex and in- clude the thalamus, caudate, putamen, pallidum, hippocampus, amygdala, and ac- cumbens structures. These bilateral structures – symmetrically located within the left…

DOCTORAL THESIS: Deep learning methods for automated detection of new multiple sclerosis lesions in longitudinal magnetic resonance images

By Mostafa Salem Supervised by Prof. Joaquim Salvi / Prof. Xavier Lladó   Abstract Multiple sclerosis (MS) is an inflammatory disease of the central nervous system, which is characterized by the presence of lesions in the brain and the spinal cord. Magnetic resonance imaging (MRI) has become a core para-clinical tool…

DOCTORAL THESIS: Online 3D View Planning for Autonomous Underwater Exploration

By Eduard Vidal Garcia Supervised by Dr. Marc Carreras / Dr. Narcís Palomeras   Abstract Autonomous underwater vehicles (AUVs) are currently used in many different applications, such as near-bottom mapping, manipulation or inspection. Most of the time, these tasks are planned in advance using prior information about the environment where the…