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We propose in this paper a boundary finding scheme for biomedical imagery which integrates a region-based method and an edge-based technique. We show that more accurate and robust results may be obtained through seeking a joint solution to the traditional approach of curve evolution. The approach incorporates an energy model based on prior distribution and likelihood into the curve evolution of the geodesic active contour (GAC) method. During curve evolution, we use a decision function to adjust relevant parameters in the model automatically so that the curve can easily avoid 'clutter'. For termination of curve evolution, a stability index is proposed which examines curve evolution convergence to ensure that the curve arrives at the boundary robustly and accurately. The experimental results demonstrate that advantages can be achieved using our approach compared to several classical methods.

This paper considers the termination criterion problem in curve evolution methods. First, we investigate the general scheme of curve evolution methods by analysing energy variation. Then, conventional termination criteria are discussed and some drawbacks are identified. Furthermore, the relationship between stability and convergence is discussed based on the Lax equivalence theorem. We then propose a new termination criterion based on a Bayesian approach and the use of global image information. The application of the proposed criterion in a given curve evolution scheme is presented. Experimental results show that the proposed termination criterion is effective and accurate compared to conventional criteria. In addition, it is successful in alleviating typical difficulties such as premature termination and weak edge leakage because of the use of global information in controlling the termination process.

The comet assay is a sensitive tool for estimation of DNA damage and repair at the cellular level, requiring only a very small number of cells. In comparing the levels of damage or repair in different cell samples, it is possible that small experimental effects could be confounded by different cell cycle states in the samples examined, if sensitivity to DNA damage, and repair capacity, varies with the cell cycle. We assessed this by arresting HeLa cells in various cell cycle stages and then exposing them to ionizing radiation. Unirradiated cells demonstrated significant differences in strand break levels measured by the comet assay (predominantly single-strand breaks) at different cell cycle stages, increasing from G(1) into S and falling again in G(2). Over and above this variation in endogenous strand break levels, a significant difference in susceptibility to breaks induced by 3.5 Gy ionizing radiation was also evident in different cell cycle phases. Levels of induced DNA damage fluctuate throughout the cycle, with cells in G(1) showing slightly lower levels of damage than an asynchronous population. Damage increases as cells progress through S phase before falling again towards the end of S phase and reaching lowest levels in M phase. The results from repair experiments (where cells were allowed to repair for 10 min after exposure to ionizing radiation) also showed differences throughout the cell cycle with G(1)-phase cells apparently being the most efficient at repair and M-phase cells the least efficient. We suggest, therefore, that in experiments where small differences in DNA damage and repair are to be investigated with the comet assay, it may be desirable to arrest cells in a specific stage of the cell cycle or to allow for differential cycle distribution.

Background Mammary gland morphogenesis involves ductal elongation, branching, and budding. All of these processes are mediated by stroma - epithelium interactions. Biomechanical factors, such as matrix stiffness, have been established as important factors in these interactions. For example, epithelial cells fail to form normal acinar structures in vitro in 3D gels that exceed the stiffness of a normal mammary gland. Additionally, heterogeneity in the spatial distribution of acini and ducts within individual collagen gels suggests that local organization of the matrix may guide morphogenesis. Here, we quantified the effects of both bulk material stiffness and local collagen fiber arrangement on epithelial morphogenesis. Results The formation of ducts and acini from single cells and the reorganization of the collagen fiber network were quantified using time-lapse confocal microscopy. MCF10A cells organized the surrounding collagen fibers during the first twelve hours after seeding. Collagen fiber density and alignment relative to the epithelial surface significantly increased within the first twelve hours and were a major influence in the shaping of the mammary epithelium. The addition of Matrigel to the collagen fiber network impaired cell-mediated reorganization of the matrix and increased the probability of spheroidal acini rather than branching ducts. The mechanical anisotropy created by regions of highly aligned collagen fibers facilitated elongation and branching, which was significantly correlated with fiber organization. In contrast, changes in bulk stiffness were not a strong predictor of this epithelial morphology. Conclusions Localized regions of collagen fiber alignment are required for ductal elongation and branching suggesting the importance of local mechanical anisotropy in mammary epithelial morphogenesis. Similar principles may govern the morphology of branching and budding in other tissues and organs.

The granule cells of the dentate gyrus give rise to thin unmyelinated axons, the mossy fibers. They form giant presynaptic boutons impinging on large complex spines on the proximal dendritic portions of hilar mossy cells and CA3 pyramidal neurons. While these anatomical characteristics have been known for some time, it remained unclear whether functional changes at mossy fiber synapses such as long-term potentiation (LTP) are associated with structural changes. Since subtle structural changes may escape a fine structural analysis when the tissue is fixed by using aldehydes and is dehydrated in ethanol, rapid high-pressure freezing (HPF) of the tissue was applied. Slice cultures of hippocampus were prepared and incubated in vitro for two weeks. Then, chemical LTP (cLTP) was induced by the application of 25 mM tetraethylammonium (TEA) for 10 min. Whole-cell patch clamp recordings from CA3 pyramidal neurons revealed a highly significant potentiation of mossy fiber synapses when compared to control conditions before the application of TEA. Next, the slice cultures were subjected to HPF, cryosubstitution, and embedding in Epon for a fine-structural analysis. When compared to control tissue, we noticed a significant decrease of synaptic vesicles in mossy fiber boutons and a concomitant increase in the length of the presynaptic membrane. On the postsynaptic side, we observed the formation of small, finger-like protrusions, emanating from the large complex spines. These short protrusions gave rise to active zones that were shorter than those normally found on the thorny excrescences. However, the total number of active zones was significantly increased. Of note, none of these cLTP-induced structural changes was observed in slice cultures from Munc13-1 deficient mouse mutants showing severely impaired vesicle priming and docking. In conclusion, application of HPF allowed us to monitor cLTP-induced structural reorganization of mossy fiber synapses.

Despite recent progress in fluorescence microscopy techniques, electron microscopy (EM) is still superior in the simultaneous analysis of all tissue components at high resolution. However, it is unclear to what extent conventional fixation for EM using aldehydes results in tissue alteration. Here we made an attempt to minimize tissue alteration by using rapid high-pressure freezing (HPF) of hippocampal slice cultures. We used this approach to monitor fine-structural changes at hippocampal mossy fiber synapses associated with chemically induced long-term potentiation (LTP). Synaptic plasticity in LTP has been known to involve structural changes at synapses including reorganization of the actin cytoskeleton and de novo formation of spines. While LTP-induced formation and growth of postsynaptic spines have been reported, little is known about associated structural changes in presynaptic boutons. Mossy fiber synapses are assumed to exhibit presynaptic LTP expression and are easily identified by EM. In slice cultures from wildtype mice, we found that chemical LTP increased the length of the presynaptic membrane of mossy fiber boutons, associated with a de novo formation of small spines and an increase in the number of active zones. Of note, these changes were not observed in slice cultures from Munc13-1 knockout mutants exhibiting defective vesicle priming. These findings show that activation of hippocampal mossy fibers induces pre- and postsynaptic structural changes at mossy fiber synapses that can be monitored by EM.

Erwin Schrodinger pointed out in his 1944 book “What is Life” that one defining attribute of biological systems seems to be their tendency to generate order from disorder defying the second law of thermodynamics. Almost parallel to his findings, the science of complex systems was founded based on observations on physical and chemical systems showing that inanimate matter can exhibit complex structures although their interacting parts follow simple rules. This is explained by a process known as self-organization and it is now widely accepted that multi-cellular biological organisms are themselves self-organizing complex systems in which the relations among their parts are dynamic, contextual and interdependent. In order to fully understand such systems, we are required to computationally and mathematically model their interactions as promulgated in systems biology. The preponderance of network models in the practice of systems biology inspired by a reductionist, bottom-up view, seems to neglect, however, the importance of bidirectional interactions across spatial scales and domains. This approach introduces a shortcoming that may hinder research on emergent phenomena such as those of tissue morphogenesis and related diseases, such as cancer. Another hindrance of current modeling attempts is that those systems operate in a parameter space that seems far removed from biological reality. This misperception calls for more tightly coupled mathematical and computational models to biological experiments by creating and designing biological model systems that are accessible to a wide range of experimental manipulations. In this way, a comprehensive understanding of fundamental processes in normal development or of aberrations, like cancer, will be generated.

The comet assay is a technique used to quantify DNA damage and repair at a cellular level. In the assay, cells are embedded in agarose and the cellular content is stripped away leaving only the DNA trapped in an agarose cavity which can then be electrophoresed. The damaged DNA can enter the agarose and migrate while the undamaged DNA cannot and is retained. DNA damage is measured as the proportion of the migratory 'tail' DNA compared to the total DNA in the cell. The fundamental basis of these arbitrary values is obtained in the comet acquisition phase using fluorescence microscopy with a stoichiometric stain in tandem with image analysis software. Current methods deployed in such an acquisition are expected to be both objectively and randomly obtained. In this paper we examine the 'randomness' of the acquisition phase and suggest an alternative method that offers both objective and unbiased comet selection. In order to achieve this, we have adopted a survey sampling approach widely used in stereology, which offers a method of systematic random sampling (SRS). This is desirable as it offers an impartial and reproducible method of comet analysis that can be used both manually or automated. By making use of an unbiased sampling frame and using microscope verniers, we are able to increase the precision of estimates of DNA damage. Results obtained from a multiple-user pooled variation experiment showed that the SRS technique attained a lower variability than that of the traditional approach. The analysis of a single user with repetition experiment showed greater individual variances while not being detrimental to overall averages. This would suggest that the SRS method offers a better reflection of DNA damage for a given slide and also offers better user reproducibility.

When using a non-rigid registration scheme, it is possible that bias is introduced during the registration process of consecutive sections. This bias can accumulate when large series of sections are to be registered and can cause substantial distortions of the scale space of individual sections thus leading to significant measurement bias. This paper presents an automated scheme based on Markov Chain Monte Carlo (MCMC) techniques to estimate and eliminate registration bias. For this purpose, a hierarchical model is used based on the assumption that (a) each section has the same, independent probability to be deformed by the sectioning and therefore the subsequent registration process and (b) the varying bias introduced by the registration process has to be balanced such that the average section area is preserved forcing the average scale parameters to have a mean value of 1.0.

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.

Angiogenic sprouts at the leading edge of an expanding vascular plexus are recognised as major regulators of the structure of the developing network. Early in sprout development, a vascular lumen is often evident which communicates with the parent vessel while the distal tip is blind-ended. Here we describe the temporal evolution of blind-ended vessels (BEVs) in a small wound made in the panniculus carnosus muscle of a mouse viewed in a dorsal skin-fold window-chamber model with intra-vital microscopy during the most active period of angiogenesis (days 5-8 after injury). Although these structures have been mentioned anecdotally in previous studies, we observed BEVs to be frequent, albeit transient, features of plexus formation. Plasma leakage into the surrounding extracellular matrix occurring from these immature conduits could play an important role in preparing hypoxic tissue for vascular invasion. Although sprout growth is likely to be regulated by its flow environment, the parameters regulating flow into and through BEVs have not been characterised in situ. Longitudinal data from individual animals show that the number of BEVs filled with plasma alone peaks at day 7, when they can exceed 150 microm in length. Additionally, BEVs greater than 40 microm in length are more likely to be filled with stationary erythrocytes than with plasma alone. Using a mathematical model, we show how the flux of 150 kD fluorinated (FITC-) dextran through an individual plasma-filled BEV is related to its geometry being determined primarily by its surface area; by fitting theoretical intensity values to experimental data we assess the permeability of the vessel to FITC-dextran. Plasma skimming provides a mechanistic explanation for the observation that BEVs with larger surface area are more likely to recruit erythrocytes.

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.