3D cerebrovascular segmentation combining fuzzy vessel enhancement and level-sets with anisotropic energy weights.

The aim of this work is to present and evaluate a level-set segmentation approach with vesselness-dependent anisotropic energy weights, which focuses on the exact segmentation of malformed as well as small vessels from time-of-flight (TOF) magnetic resonance angiography (MRA) datasets. In a first step, a vesselness filter is used to calculate the vesselness dataset, which quantifies the likeliness of each voxel to belong to a bright tubular-shaped structure and estimate the corresponding vessel directions from a given TOF dataset. The vesselness and TOF datasets are then combined using fuzzy-logic and used for initialization of a variational level-set method. The proposed level-set model has been extended in a way that the weight of the internal energy is locally adapted based on the vessel direction information. Here, the main idea is to weight the internal energy lower if the gradient direction of the level-set is similar to the direction of the eigenvector extracted by the vesselness filter. Furthermore, an additional vesselness force has been integrated in the level-set formulation. The proposed method was evaluated based on ten TOF MRA datasets from patients with an arteriovenous malformation. Manual segmentations from two observers were available for each dataset and used for quantitative comparison. The evaluation revealed that the proposed method yields significantly better segmentation results than four other state-of-the-art segmentation methods tested. Furthermore, the segmentation results are within the range of the inter-observer variation. In conclusion, the proposed method allows an improved delineation of small vessels, especially of those represented by low intensities and high surface curvatures.

4D blood flow visualization fusing 3D and 4D MRA image sequences.

PURPOSE: To present and evaluate the feasibility of a novel automatic method for generating 4D blood flow visualizations fusing high spatial resolution 3D and time-resolved (4D) magnetic resonance angiography (MRA) datasets. MATERIALS AND METHODS: In a first step, the cerebrovascular system is segmented in the 3D MRA dataset and a surface model is computed. The hemodynamic information is extracted from the 4D MRA dataset and transferred to the surface model using rigid registration where it can be visualized color-coded or dynamically over time. The presented method was evaluated using software phantoms and 20 clinical datasets from patients with an arteriovenous malformation. Clinical evaluation was performed by comparison of Spetzler-Martin scores determined from the 4D blood flow visualizations and corresponding digital subtraction angiographies. RESULTS: The performed software phantom validation showed that the presented method is capable of producing reliable visualization results for vessels with a minimum diameter of 2 mm for which a mean temporal error of 0.27 seconds was achieved. The clinical evaluation based on 20 datasets comparing the 4D visualization to DSA images revealed an excellent interrater reliability. CONCLUSION: The presented method enables an improved combined representation of blood flow and anatomy while reducing the time needed for clinical rating.

Reference-based linear curve fitting for bolus arrival time estimation in 4D MRA and MR perfusion-weighted image sequences.

The bolus arrival time (BAT) based on an indicator dilution curve is an important hemodynamic parameter. As the direct estimation of this parameter is generally problematic, various parametric models have been proposed that describe typical physiological shapes of indicator dilution curves, but it remains unclear which model describes the real physiological background. This article presents a method that indirectly incorporates physiological information derived from the data available. For this, a patient-specific hemodynamic reference curve is extracted, and the corresponding reference BAT is determined. To estimate a BAT for a given signal curve, the reference curve is fitted linearly to the signal curve. The parameters of the fitting process are then used to transfer the reference BAT to the signal curve. The validation of the method proposed based on Monte Carlo simulations showed that the approach presented is capable of improving the BAT estimation precision compared with standard BAT estimation methods by up to 59% while at the same time reduces the computation time. A major benefit of the method proposed is that no assumption about the underlying distribution of indicator dilution has to be made, as it is implicitly modeled in the reference curve.

Proposal of a robust measurement scheme for the nonadiabatic spin torque using the displacement of magnetic vortices.

A spin-polarized current traversing a ferromagnet with continuously varying magnetization exerts a torque on the magnetization. The nonadiabatic contribution to this spin-transfer torque is currently under strong debate, as its value differs by orders of magnitude in theoretical predictions and in measurements. Here, a measurement scheme is presented that allows us to determine the strength of the nonadiabatic spin torque accurately and directly. Analytical and numerical calculations show that the scheme is robust against the uncertainties of the exact current direction and Oersted fields.

Real-space observation of molecular motion induced by femtosecond laser pulses.

Femtosecond laser irradiation is used to excite adsorbed CO molecules on a Cu110 surface; the ensuing motion of individual molecules across the surface is characterized on a site-to-site basis by in situ scanning tunneling microscopy. Adsorbate motion both along and perpendicular to the rows of the Cu110 surface occurs readily, in marked contrast to the behavior seen for equilibrium diffusion processes. The experimental findings for the probability and direction of the molecular motion can be understood as a manifestation of strong coupling between the adsorbates' lateral degrees of freedom and the substrate electronic excitation produced by the femtosecond laser radiation.