Annemie Ribbens

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The location and extent of white matter lesions on magnetic resonance imaging (MRI) are important criteria for diagnosis, follow-up and prognosis of multiple sclerosis (MS). Clinical trials have shown that quantitative values, such as lesion volumes, are meaningful in MS prognosis. Manual lesion delineation for the segmentation of lesions is, however,(More)
Healthy ageing coincides with a progressive decline of brain gray matter (GM) ultimately affecting the entire brain. For a long time, manual delineation-based volumetry within predefined regions of interest (ROI) has been the gold standard for assessing such degeneration. Voxel-Based Morphometry (VBM) offers an automated alternative approach that, however,(More)
PURPOSE To validate the reproducibility of a chemical shift imaging (CSI) acquisition protocol with parallel imaging, using automated repositioning software. MATERIALS AND METHODS Ten volunteers were imaged three times on two different 3 Tesla (T) MRI scanners, receiving anatomical imaging and two identical CSI measurements, using automated repositioning(More)
Population analysis of brain morphology from magnetic resonance images contributes to the study and understanding of neurological diseases. Such analysis typically involves segmentation of a large set of images and comparisons of these segmentations between relevant subgroups of images (e.g., "normal" versus "diseased"). The images of each subgroup are(More)
Automated methods for image segmentation, image registration, clustering of images and probabilistic atlas construction are of great interest in medical image analysis. In this work, we propose a model where these different aspects are combined in one comprehensive probabilistic framework. The framework is formulated as an EM optimization algorithm.(More)
OBJECTIVE The identification of a biomarker with prognostic value is an unmet need in multiple sclerosis (MS). The objective of this study was to investigate a possible association of HLA genotype with disease status and progression in MS, based on comprehensive and sensitive clinical and magnetic resonance imaging (MRI) parameters to measure disease(More)
Purpose: Lesion volume is a meaningful measure in multiple sclerosis (MS) prognosis. Manual lesion segmentation for computing volume in a single or multiple time points is time consuming and suffers from intra and inter-observer variability. Methods: In this paper, we present MSmetrix-long: a joint expectation-maximization (EM) framework for two time point(More)
INTRODUCTION As neurodegeneration is recognized as a major contributor to disability in multiple sclerosis (MS), brain atrophy quantification could have a high added value in clinical practice to assess treatment efficacy and disease progression, provided that it has a sufficiently low measurement error to draw meaningful conclusions for an individual(More)