Browsing Departament d'Arquitectura i Tecnologia de Computadors by Subject "616.8"

Now showing items 1-7 of 7

Atlas-based segmentation of multiple sclerosis lesions in magnetic resonance imaging

Cabezas Grebol, Mariano (Date of defense: 2013-07-16)

This thesis deals with the segmentation of brain magnetic resonance imaging applied to multiple sclerosis patients. This disease is characterised by the presence of white matter lesions in this image modality. After a ...

Automated brain structure segmentation in magnetic resonance images of multiple sclerosis patients

González-Villà, Sandra (Date of defense: 2019-05-31)

This thesis is focused on the automated segmentation of the brain structures in magnetic resonance images, applied to multiple sclerosis patients. This disease is characterized by the presence of lesions, which affect the ...

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 ...

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

Kushibar, Kaisar (Date of defense: 2020-07-20)

This PhD thesis focuses on the development of deep learning based methods for accurate segmentation of the sub-cortical brain structures from MRI. First, we have proposed a 2.5D CNN architecture that combines convolutional ...

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. ...

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

Salem, Mostafa (Date of defense: 2020-02-13)

This thesis is focused on developing novel and fully automated methods for the detection of new multiple sclerosis (MS) lesions in longitudinal brain magnetic resonance imaging (MRI). First, we proposed a fully automated ...

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). ...