Institut de Recerca en Visió per Computador i Robòtica

L'Institut de Recerca en Visió per Computador i Robòtica (ViCOROB) és un institut de recerca en els àmbits de: Anàlisi de la Imatge Mèdica, Anàlisi de la Imatge Multimèdia, Percepció 3D en entorns industrials, Visió subaquàtica, Robòtica subaquàtica i Intel·ligència artificial.


Si sou doctor o doctora de la Universitat de Girona i voleu publicar la vostra tesi a TDX, contacteu amb tdx@udg.edu. Per a més informació consulteu les preguntes més freqüents.

Envíos recientes

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

Clèrigues Garcia, Albert (Fecha de defensa: 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). ...

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

Castillón Sánchez, Miguel (Fecha de defensa: 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 ...

Automated 3D object recognition in underwater scenarios for manipulation 

Himri, Khadidja (Fecha de defensa: 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 image-based 3D reconstruction with quality estimation 

Istenič, Klemen (Fecha de defensa: 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 ...

Deep learning for atrophy quantification in brain magnetic resonance imaging 

Bernal Moyano, Jose (Fecha de defensa: 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. ...

Glandular tissue pattern analysis through multimodal MRI-mammography registration 

García Marcos, Eloy (Fecha de defensa: 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 ...

Automated methods on magnetic resonance brain imaging in multiple sclerosis 

Roura Pérez, Eloy (Fecha de defensa: 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 ...

Automated brain tissue segmentation of magnetic resonance images in multiple sclerosis 

Valverde Valverde, Sergi (Fecha de defensa: 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 ...

Simultaneous localization and mapping using single cluster probability hypothesis density filters 

Lee, Chee Sing (Fecha de defensa: 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 ...

Web-based application for medical imaging management 

Mata Miquel, Christian (Fecha de defensa: 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 ...