Thesis

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…

DOCTORAL THESIS: Computer Aided Detection for Breast Lesion in Ultrasound and Mammography

By Richa Agarwal Supervised by Dr. Robert Martí Marly  /  Dr. Oliver Fernando Diaz Montesdeoca   / Dr. Xavier Lladó Bardera     Abstract In the field of breast cancer imaging, traditional Computer Aided Detection (CAD) systems were designed using limited computing resources and used scanned films (poor image quality), resulting in…

DOCTORAL THESIS: Automated brain structure segmentation in magnetic resonance images of multiple sclerosis patients.

By Sandra González Villà Supervised by Dr. Xavier Lladó Bardera  / Dr.  Arnau Oliver Malagelada   Abstract This thesis is focused on the automated segmentation of the brain structures in magnetic resonance images, applied to multiple sclerosis (MS) patients. This disease is characterized by the presence of demyelinating lesions in…