Web-based application for medical imaging management 

    Mata Miquel, Christian (Date of defense: 2015-07-24)

    Prostate and breast cancer are the most common cause of cancers in men and women, respectively. Medical imaging plays an important role in breast and prostate cancer detection and evaluation. Then to prove that our web-based ...

    Simultaneous localization and mapping using single cluster probability hypothesis density filters 

    Lee, Chee Sing (Date of defense: 2015-09-01)

    The majority of research in feature-based SLAM builds on the legacy of foundational work using the EKF, a single-object estimation technique. Because feature-based SLAM is an inherently multi-object problem, this has led ...

    Automated brain tissue segmentation of magnetic resonance images in multiple sclerosis 

    Valverde Valverde, Sergi (Date of defense: 2016-06-14)

    L'objectiu principal d'aquesta tesi és el desenvolupament d'un nou mètode de segmentació totalment automàtic capaç de mesurar amb precisió el volum cerebral en imatges de pacients d'EM amb lesions. El mètode que hem proposat ...

    Automated methods on magnetic resonance brain imaging in multiple sclerosis 

    Roura Pérez, Eloy (Date of defense: 2016-07-01)

    In this thesis, we have focused on the image pre-processing in order to enhance the image information. The main aspects of this enhancement rely on removing any image noise and correcting any intensity bias induced by the ...

    Glandular tissue pattern analysis through multimodal MRI-mammography registration 

    García Marcos, Eloy (Date of defense: 2018-04-05)

    Breast cancer is the most common cancer among women worldwide. Several studies have shown that the combination of the different medical image modalities, such as the x-ray mammography and the magnetic resonance imaging ...

    Deep learning for atrophy quantification in brain magnetic resonance imaging 

    Bernal Moyano, Jose (Date of defense: 2020-10-27)

    The quantification of cerebral atrophy is fundamental in neuroinformatics since it permits diagnosing brain diseases, assessing their progression, and determining the effectiveness of novel treatments to counteract them. ...

    Underwater image-based 3D reconstruction with quality estimation 

    Istenič, Klemen (Date of defense: 2021-03-25)

    This thesis addresses the development of resources for accurate scaling and uncertainty estimation of image-based 3D models for scientific purposes based on data acquired with monocular or unsynchronized camera systems in ...

    Automated 3D object recognition in underwater scenarios for manipulation 

    Himri, Khadidja (Date of defense: 2021-12-10)

    In recent decades, the rapid development of intelligent vehicle and 3D scanning tecnologies has led to a growing interest in applications based on 3D point data processing, with many applications such as augmented reality ...

    Underwater 3d sensing using structured light: development of an underwater laser scanner and a non-rigid point cloud registration method 

    Castillón Sánchez, Miguel (Date of defense: 2023-02-10)

    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 ...

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

    Clèrigues Garcia, Albert (Date of defense: 2023-02-13)

    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). ...