Towards ultra-high resolution 3D reconstruction of a whole rat brain from 3D-PLI data

3D reconstruction of the fiber connectivity of the rat brain at microscopic scale enables gaining detailed insight about the complex structural organization of the brain. We introduce a new method for registration and 3D reconstruction of high- and ultra-high resolution (64 $\mu$m and 1.3 $\mu$m pixel size) histological images of a Wistar rat brain acquired by 3D polarized light imaging (3D-PLI). Our method exploits multi-scale and multi-modal 3D-PLI data up to cellular resolution. We propose a new feature transform-based similarity measure and a weighted regularization scheme for accurate and robust non-rigid registration. To transform the 1.3 $\mu$m ultra-high resolution data to the reference blockface images a feature-based registration method followed by a non-rigid registration is proposed. Our approach has been successfully applied to 278 histological sections of a rat brain and the performance has been quantitatively evaluated using manually placed landmarks by an expert.Comment: 9 pages, Accepted at 2nd International Workshop on Connectomics in NeuroImaging (CNI), MICCAI'201

Unoccupied states of individual silver clusters and chains on Ag(111)

Size-selected silver clusters on Ag(111) were fabricated with the tip of a scanning tunneling microscope. Unoccupied electron resonances give rise to image contrast and spectral features which shift toward the Fermi level with increasing cluster size. Linear assemblies exhibit higher resonance energies than equally sized compact assemblies. Density functional theory calculations reproduce the observed energies and enable an assignment of the resonances to hybridized atomic 5s and 5p orbitals with silver substrate states.Comment: 9 pages, 8 figure

Towards patient specific catheter selection: Computation of aortic geometry based on fused MRI data

In coronary angiography, a catheter's tip has to be directed through the aorta towards the ostium - the region where the coronary arteries arise. Due to the anatomical variation in different humans, there is no common catheter which can be used for all patients. Thus, in a trial and error procedure cardiologists find a catheter that fits to the patient's anatomy. To replace this time consuming approach by providing a computer aided planning tool to be used prior to the intervention is the focus of our work. First of all, it is necessary for such a system to derive geometrical parameters for the patient's aorta as well as for the different available catheters. Based thereon, the best fitting catheter can be selected. In this paper, we discuss the first step: the computation of geometrical parameters from the patient's image data. Due to the setting defined by our clinical partner, two MRI data sets are acquired and should be used for the computation. This requires a specific image processing pipeline which we present here and which has to our knowledge not been proposed so far. Furthermore, we show first results obtained for real clinical data sets and discuss the subsequent steps for the development of the catheter selection tool