Form und Filter - Algorithmen der Bilderverarbeitung und Stilanalyse

Die Grundbegriffe Wölfflins lassen sich mit Hilfe digitaler Algorithmen nachmodellieren. Welches Wissen wird damit gewonnen? Auch Wölfflin hat auf mediale Veränderungen reagiert, indem er die Doppel-Projektion von Dias in den binären Differenzen der Grundbegriffe nachbildete. Sie lesen der Projektion zweier Bilder eine historische Differenz aus, die für die Disziplin der Kunstgeschichte grundlegend ist. Ein digitale Nachbildung dieser Differenz wäre tautologisch: sie würde ein gewusstes Wissen wiederholen. Fruchtbar wird der Einsatz digitaler Algorithmen dann, wenn sie nicht nur etwas bekanntes abbilden, sondern wenn man fragt, zu welcher "methodischen Grenzerweiterung" sie beitragen könnten.

A Skull-Stripping Filter for ITK

Skull-stripping (or brain extraction) is an important pre-processing step in neuroimage analysis. This document describes a skull-stripping filter implemented using the Insight Toolkit ITK, which we named itk::StripTsImageFilter. It is a composite filter based on existing ITK classes. The filter has been implemented with usability, robustness, speed and versatility in mind, rather than accuracy. This makes it useful for many pre-processing tasks in neuroimage analysis. This paper is accompanied by the source code, input data and a testing environment.

Modulus method and radial stretch map in the Heisenberg group

We develop a modulus method for surface families inside a domain in the Heisenberg group and we prove that the stretch map between two Heisenberg spherical rings is a minimiser for the mean distortion among the class of contact quasiconformal maps between these rings which satisfy certain boundary conditions.

Ligament origins are preserved in distal radial intraarticular two-part fractures: a computed tomography-based study

Background Operative fixation of intraarticular distal radius fractures is increasingly common. A greater understanding of fracture patterns will aid surgical fixation strategy. Previous studies have suggested that ligamentous insertions may less commonly be involved, but these have included heterogeneous groups of fractures and have not addressed Lister's tubercle. Purpose We hypothesize that fracture lines of distal radial intraarticular 2-part fractures have reproducible patterns. They propagate through the cortical bone between ligament origins and do not involve Lister's tubercle. Methods Axial CT scans of two-part intraarticular distal radius fractures were assessed independently by two examiners. The fractures were mapped onto a grid and the cortical breaches expressed as a percentile of the total radial width or length. The cortical breaches were compared with the ligamentous insertions on the distal and Lister's tubercle. Associated injuries were also documented. Results The cortical breaches occurred between the ligamentous insertions in 85%. Lister's tubercle was not involved in 95% of the fractures. Three major fracture patterns emerged: radial styloid, dorsal, and volar. Each major pattern had two subtypes. Associated injuries were common. Scapholunate dissociation was associated with all types, not just the radial styloid fracture pattern. Conclusions The fracture patterns of two-part intraarticular fractures mostly involved the interligamentous zones. Three major groups were identified: dorsal, volar, and radial styloid. Lister's tubercle was preserved with fractures tending to propagate radial or ulnar to this structure. We suggest conceptualizing fracture fragments as osseo-ligamentous units to aid prediction of fracture patterns and associated injury. Study Design Diagnostic III Level of Evidence 3.

Extended kalman filter for estimation of parameters in nonlinear state-space models of biochemical networks.

It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks.