Publications
Chosen filters:
Chosen filters:
Genetic markers for species conservation and timber tracking: Development of microsatellite primers for the tropical African tree species Prioria balsamifera and Prioria oxyphylla Meise Botanic Garden KU Leuven
Research Highlights: Two novel sets of polymorphic microsatellite markers were developed for Prioria balsamifera and Prioria oxyphylla through high-throughput sequencing. Validation in two populations of each species proved the utility of the developed primers to estimate genetic diversity at population level. Background and Objectives: Prioria balsamifera and Prioria oxyphylla are tropical tree species from Central Africa. They produce a ...
Electrical source imaging of interictal spikes using multiple sparse volumetric priors for presurgical epileptogenic focus localization Ghent University Vrije Universiteit Brussel
Evaluation of Three MRI-Based Anatomical Priors for Quantitative PET Brain Imaging KU Leuven
In emission tomography, image reconstruction and therefore also tracer development and diagnosis may benefit from the use of anatomical side information obtained with other imaging modalities in the same subject, as it helps to correct for the partial volume effect. One way to implement this, is to use the anatomical image for defining the a-priori distribution in a maximum-a-posteriori (MAP) reconstruction algorithm. In this contribution, we ...
Evaluation of different MRI-based anatomical priors for PET brain imaging KU Leuven
Image reconstruction in emission tomography may benefit from the use of anatomical side information obtained with other imaging modalities in the same subject. One way to implement this, is to use the anatomical image for defining the a-priori distribution in a maximum-a-posteriori reconstruction algorithm. In this contribution, we use the PET-SORTEO Monte Carlo simulator to evaluate three different anatomical priors for PET brain imaging, using ...
Material-Specific Chromaticity Priors Hasselt University
Recent advances in machine learning have enabled the recognition of high-level categories of materials with a reasonable accuracy. With these techniques, we can construct a per-pixel material labeling from a single image. We observe that groups of high-level material categories have distinct chromaticity distributions. This fact can be used to predict the range of the absolute chromaticity values of objects, provided the material is correctly ...