Homogeneity based segmentation and enhancement of Diffusion Tensor Images : a white matter processing framework

In diffusion magnetic resonance imaging (DMRI) the Brownian motion of the water molecules, within biological tissue, is measured through a series of images. In diffusion tensor imaging (DTI) this diffusion is represented using tensors. DTI describes, in a non-invasive way, the local anisotropy pattern enabling the reconstruction of the nervous fibers - dubbed tractography. DMRI constitutes a powerful tool to analyse the structure of the white matter within a voxel, but also to investigate the anatomy of the brain and its connectivity. DMRI has been proved useful to characterize brain disorders, to analyse the differences on white matter and consequences in brain function. These procedures usually involve the virtual dissection of white matters tracts of interest. The manual isolation of these bundles requires a great deal of neuroanatomical knowledge and can take up to several hours of work. This thesis focuses on the development of techniques able to automatically perform the identification of white matter structures. To segment such structures in a tensor field, the similarity of diffusion tensors must be assessed for partitioning data into regions, which are homogeneous in terms of tensor characteristics. This concept of tensor homogeneity is explored in order to achieve new methods for segmenting, filtering and enhancing diffusion images. First, this thesis presents a novel approach to semi-automatically define the similarity measures that better suit the data. Following, a multi-resolution watershed framework is presented, where the tensor field’s homogeneity is used to automatically achieve a hierarchical representation of white matter structures in the brain, allowing the simultaneous segmentation of different structures with different sizes. The stochastic process of water diffusion within tissues can be modeled, inferring the homogeneity characteristics of the diffusion field. This thesis presents an accelerated convolution method of diffusion images, where these models enable the contextual processing of diffusion images for noise reduction, regularization and enhancement of structures. These new methods are analysed and compared on the basis of their accuracy, robustness, speed and usability - key points for their application in a clinical setting. The described methods enrich the visualization and exploration of white matter structures, fostering the understanding of the human brain

Gelijke behandeling en het College voor de Rechten van de Mens (2016)

Effective Protection of Fundamental Rights in a pluralist worl

Reform scenarios for the EU migration and asylum policy in [the] light of new refugee movements

The progression of EU law: Accommodating change and upholding value

Ongelijkheidscompensatie in het vreemdelingenrecht

Afscheidsrede uitgesproken door Prof. mr. Peter R. Rodrigues bij gelegenheid van zijn emeritaat als hoogleraar op het gebied Immigratierecht aan de Universiteit Leiden op vrijdag 6 oktober 2023Effective Protection of Fundamental Rights in a pluralist worl

Asielaanvragen Roma in Nederland, Een vrijwel onneembare drempel

The progression of EU law: Accommodating change and upholding value

De grenzen van het vreemdelingenrecht

De bescherming van fundamentele rechten in een integrerend Europ

De minderjarige vreemdeling: het kind van de rekening?

Effective Protection of Fundamental Rights in a pluralist worl

Tijdsdruk bij opleggen vreemdelingenbewaring

The progression of EU law: Accommodating change and upholding value

The best interests of the child in EU family reunification law: A plea for more guidance on the role of article 24(2) charter

The best interests of the child should be a primary consideration in all actions concerning children. This cornerstone of international children’s rights has been codified in Article 24(2) of the Charter of Fundamental Rights of the European Union. In eu family reunification law, the best interests of the child are mentioned in Directive 2003/86/ec on the right to family reunification. However, in the case law of the Court of Justice of the European Union, this concept is not systematically applied in the various types of family reunification cases. In this contribution it is argued that, although the contexts of family reunification cases may be different, from the perspective of the diverse international obligations of the Member States, it would be preferable if the Court systematically involved the best interests of the child concept in all family reunification cases.The progression of EU law: Accommodating change and upholding value

Extrapolating fiber crossings from DTI data : can we gain the same information as HARDI?

High angular resolution diffusion imaging (HARDI) has proven to better characterize complex intra-voxel structures compared to its predecessor diffusion tensor imaging (DTI). However, the benefits from the modest acquisitions and significantly higher signal-to-noise ratios (SNRs) of DTI make it more attractive for use in clinical research. In this work we use contextual information derived from DTI data, to obtain similar crossing information as from HARDI data. We conduct synthetic phantom validation under different angles of crossing and different SNRs. We corroborate our findings from the phantom study to real human data. We show that with extrapolation of the contextual information the obtained crossings are the same as the ones from the HARDI data, and the robustness to noise is significantly better