Thesis

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 diseases, assessing their progression, and determining the effective- ness of novel treatments to counteract these brain diseases. However, this is…

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 and right hemispheres – are involved in systematic activities such as emotion, pleasure, memory and hormone production. Their deviations in…

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 for diagnosing and predicting long-term disability and treatment response in MS patients. It has been accepted that dissemination in time…

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 robot will operate. When this prior information does not exist, robotic exploration algorithms can be used so that the robot…

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 less robust application process. Currently, with the advancements in technologies, it is possible to perform 3D imaging and also acquire…

DOCTORAL THESIS: Advanced Underwater Vehicle Manipulation through Real-Time Motion Planning

By Dina Nagui Youakim Isaac Supervised by Dr. Pere Ridao     Abstract A key challenge in autonomous mobile manipulation is the ability to determine in real-time how to safely execute complex tasks when placed in an unknown world. Motion Planning has been widely used in terrestrial and aerial robots to cope with such challenges, while it stayed unexplored for underwater intervention. In the last few years, Intervention Autonomous Underwater Vehicles…

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 the brain, that appear as focal low signal intensity areas in the T1-weighted sequence, which is the most frequently used…

DOCTORAL THESIS: 3D Underwater SLAM Using Sonar and Laser Sensors

By Albert Palomer Vila Supervised by Dr. Pere Ridao, Dr. Josep Forest i Dr. David Ribas   Abstract The 3D perception and mapping problem are very closely related with the robot localization and has not been yet solved up to a degree that allow AUVs to interact with complex environments safely. By providing AUVs with better 3D perception and improving their localization the usage of AUVs in tasks such as…