Université catholique de Louvain

About: Université catholique de Louvain is a education organization based out in Louvain-la-Neuve, Belgium. It is known for research contribution in the topics: Population & Catalysis. The organization has 25319 authors who have published 57360 publications receiving 2172080 citations. The organization is also known as: University of Louvain & UCLouvain.

Registration of 3-d intraoperative MR images of the brain using a finite-element biomechanical model

Abstract: We present a new algorithm for the nonrigid registration of three-dimensional magnetic resonance (MR) intraoperative image sequences showing brain shift. The algorithm tracks key surfaces of objects (cortical surface and the lateral ventricles) in the image sequence using a deformable surface matching algorithm. The volumetric deformation field of the objects is then inferred from the displacements at the boundary surfaces using a linear elastic biomechanical finite-element model. Two experiments on synthetic image sequences are presented, as well as an initial experiment on intraoperative MR images showing brain shift. The results of the registration algorithm show a good correlation of the internal brain structures after deformation, and a good capability of measuring surface as well as subsurface shift. We measured distances between landmarks in the deformed initial image and the corresponding landmarks in the target scan. Cortical surface shifts of up to 10 mm and subsurface shifts of up to 6 mm were recovered with an accuracy of 1 mm or less and 3 mm or less respectively.

Multiparametric imaging of biological systems by force-distance curve-based AFM.

Abstract: A current challenge in the life sciences is to understand how biological systems change their structural, biophysical and chemical properties to adjust functionality. Addressing this issue has been severely hampered by the lack of methods capable of imaging biosystems at high resolution while simultaneously mapping their multiple properties. Recent developments in force-distance (FD) curve–based atomic force microscopy (AFM) now enable researchers to combine (sub)molecular imaging with quantitative mapping of physical, chemical and biological interactions. Here we discuss the principles and applications of advanced FD-based AFM tools for the quantitative multiparametric characterization of complex cellular and biomolecular systems under physiological conditions.

Using pedotransfer functions to estimate the van Genuchten-Mualem Soil Hydraulic Properties: a review.

Abstract: We reviewed the use of the van Genuchten–Mualem (VGM) model to parameterize soil hydraulic properties and for developing pedotransfer functions (PTFs). Analysis of literature data showed that the moisture retention characteristic (MRC) parameterization by setting shape parameters m = 1 − 1/ n produced the largest deviations between fitted and measured water contents for pressure head values between 330 (log10 pressure head [pF] 2.5) and 2500 cm (pF 3.4). The Schaap–van Genuchten model performed best in describing the unsaturated hydraulic conductivity, K . The classical VGM model using fixed parameters produced increasingly higher root mean squared residual, RMSR, values when the soil became drier. The most accurate PTFs for estimating the MRC were obtained when using textural properties, bulk density, soil organic matter, and soil moisture content. The RMSR values for these PTFs approached those of the direct fit, thus suggesting a need to improve both PTFs and the MRC parameterization. Inclusion of the soil water content in the PTFs for K only marginally improved their prediction compared with the PTFs that used only textural properties and bulk density. Including soil organic matter to predict K had more effect on the prediction than including soil moisture. To advance the development of PTFs, we advocate the establishment of databases of soil hydraulic properties that (i) are derived from standardized and harmonized measurement procedures, (ii) contain new predictors such as soil structural properties, and (iii) allow the development of time-dependent PTFs. Successful use of structural properties in PTFs will require parameterizations that account for the effect of structural properties on the soil hydraulic functions.