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In this paper we discuss how the classical geodesic active contours (GAC) model is enhanced by incorporating `prior' information into the scheme. The modified model is applied to biomedical imagery, specifically serial ultrathin electron microscopy sections. The approach used is to apply prior analysis on a training set of data and provide geometric information about the target object during the process of curve evolution. The experimental results and analysis for both synthetic and real images show that the approach performs better than our previous method. It can be implemented semi-automated fashion giving significant improvements compared to a manual approach.

Real-time visualization plays an important role in medical imaging applications such as image-guided surgery, surgical simulation and medical education. For the real-time visualization and the simultaneous overlay of 3D triangulated objects onto live recordings of patient data gathered with fast imaging devices (e.g. from the beating heart) it is essential that the number of triangles used for displaying the meshes are reasonably low. For this purpose, we developed a novel, optimized surface reconstruction algorithm for planar cross sections based on the non-constrained 3D Delaunay triangulation using pre-computed contour data. The proposed method generates 50% fewer triangles for the cardiac images used in our application domain in comparison to standard reconstruction methods from planar cross sections. Besides reducing the number of triangles, our method eliminates 'stair-case' artifacts that can occur between consecutive cross sections for non-uniformly sampled input image data often found in biomedical imaging applications.

Bigot and co-workers have shown that it is possible to estimate velocities of labelled leukocytes by recording their fluorescent response across a 1D line placed orthogonal to flow in a vessel using fast line-scanning in a confocal microscope. However, as ground truth data cannot be recorded, validation of this method is not possible. In this paper, we address this issue by modelling the imaging process and by simulating virtual xt-scans. This approach yields realistic xt-scans for which velocities and positions of particles are known and therefore the performance of the previously proposed particle tracer can be tested and validated.

This paper presents improvements to the geodesic active contour (GAC) model obtained by incorporating user defined prior information into the model itself. Specifically, the stopping function in the GAC model is revised by designing an indicator function derived from a-priori information. The numerical implementation is based on the level set technique. Experimental results illustrate that our approach is efficient and feasible for both artificial and real images. In particular, the proposed method performs well in situations where existing methods are known to fail.

The fast and direct measurement of leukocyte behaviour in microvessels in situ is possible by labelling them with fluorescent compounds and subsequently imaging them by confocal laser scanning microscopy. Using a high-speed single line scanning technique a time dependent trace of leukocytes in microvessels can be recorded (x-t scan). These x-t traces, which are orientated orthogonal to the blood flow, are characterized by distinct, but often noise-affected elliptical streaks, which carry information on speed and frequency of leukocytes crossing the scan line. Here we describe the combination of a confocal laser scanning system and an image analysis software package that allows rapid and reproducible estimation of leukocyte velocities in microvessels

Analyzing dynamic biological systems, such as blood vessel growth in healing wounds or tumour development, requires high spatial and temporal resolution. Intravital fluorescence microscopy allows for longitudinal subcellular imaging, but it requires the use of advanced image analysis tools in order to quantitatively extract the relevant parameters or the topology of the underlying network structure to subsequently model and simulate such a system mathematically. We will present a fast and robust approach that estimates the vessel diameter with a low coefficient of error < 6% in settings that are typical for such in-vivo imaging scenarios with a low signal-to-noise ratio and often sub-optimal and uneven background illumination. The generated vessel network is geometrically cleansed for an optimal topological representation.

The rather general nature of the book title raises many expectations with respect to High Performance Computing (HPC). One is tempted to believe that this book discusses in greater detail the different HPC architectures, their advantages and disadvantages, shows different implementation strategies to make use of the enormous computing power offered by these architectures, lists software packages and libraries helping in parallelizing code, gives tips for benchmarking, talks about compiler issues, batch processing, addresses shared and distributed memory models and overheads associated with inter-process communication. The summary on the back of the book, which states that authors from "leading-edge research groups in the field of scientific computing present their outstanding projects" and "describe their scientific background, their resources requirements with respect to top-level supercomputers, and their methods for efficient utilization of the costly high-performance computing power" just adds to this expectation. Unwrapping the book from its lamination soon reveals that one should have paid more attention to the part 'Munich 2004' within the title. Reading the first pages of the book and the preface shows that the book is a collection of selected status reports that were presented at a workshop in Munich on the 2nd and 3rd of March 2004. The participants of the workshop were all members of the Competence Network for Technical/Scientific High Performance Computing (KONWIHR) working closely together with the Centre for High Performance Computing in Bavaria (HLRB). Although the editors stress the ongoing international collaborations from several research groups within the network, the chosen framework for the book drastically narrows the view on HPC to the KONWIHR perspective. It seems that publishing an official Springer book was much more appealing to the editors than just submitting an internal technical report to the sponsors of KONWIHR, such as the German Research Foundation (DFG) and the Bavarian State Ministry of Science, Research and Arts. Unfortunately, the editors did not make an increased effort to make this a book that focuses on HPC. The articles presented to the reader are highly variable in quality and only a minority meets the expectations raised on HPC. Some articles have not been thoroughly proofread and still contain many typing errors. Some figure legends were not translated into English. The motivation for using HPC was poor and often given as need for speed, but the gain in speed was rarely detailed. Most importantly, the vast majority of articles focus on very specific applications, which require a substantial degree of background knowledge in that particular field. As the book covers "modelling and simulation in the disciplines Biosciences, Chemistry, Chemical Physics, Solid-State Physics, High-Energy Physics, Astrophysics, Geophysics, Computational Fluid Dynamics, and Computer Science" it is impossible to understand every article in greater detail. And finally, although the number of disciplines covered is vast, the book does not give a comprehensive overview on HPC driven research looking at each discipline separately, which is particularly true for the Biosciences. I personally think that the book title should have been chosen with more care clearly reflecting the nature of this book. As many of the presented articles seem to be partly published elsewhere, an electronic version of the collection of reports would have been a more efficient way in disseminating the results of the KONWIHR project. This would have had the additional advantage that the articles could have been electronically searched for specific key words. The book is indeed not suited for somebody generally interested in HPC, but it might be a good point of reference for somebody working on a very similar project than the ones covered by the articles.