Stefan Wörz

Deterministic and probabilistic approaches for tracking virus particles in time-lapse fluorescence microscopy image sequences

Modern developments in time-lapse fluorescence microscopy enable the observation of a variety of processes exhibited by viruses. The dynamic nature of these processes requires the tracking of viruses over time to explore spatial-temporal relationships. In this work, we developed deterministic and probabilistic approaches for multiple virus tracking in multi-channel fluorescence microscopy images. The deterministic approaches follow a traditional two-step paradigm comprising particle localization based on either the spot-enhancing filter or 2D Gaussian fitting, as well as motion correspondence based on a global nearest neighbor scheme. Our probabilistic approaches are based on particle filters. We describe approaches based on a mixture of particle filters and based on independent particle filters. For the latter, we have developed a penalization strategy that prevents the problem of filter coalescence (merging) in cases where objects lie in close proximity. A quantitative comparison based on synthetic image sequences is carried out to evaluate the performance of our approaches. In total, eight different tracking approaches have been evaluated. We have also applied these approaches to real microscopy images of HIV-1 particles and have compared the tracking results with ground truth obtained from manual tracking. It turns out that the probabilistic approaches based on independent particle filters are superior to the deterministic schemes as well as to the approaches based on a mixture of particle filters.

Segmentation and Quantification of Human Vessels Using a 3-D Cylindrical Intensity Model

We introduce a new approach for 3-D segmentation and quantification of vessels. The approach is based on a 3-D cylindrical parametric intensity model, which is directly fitted to the image intensities through an incremental process based on a Kalman filter. Segmentation results are the vessel centerline and shape, i.e., we estimate the local vessel radius, the 3-D position and 3-D orientation, the contrast, as well as the fitting error. We carried out an extensive validation using 3-D synthetic images and also compared the new approach with an approach based on a Gaussian model. In addition, the new model has been successfully applied to segment vessels from 3-D MRA and computed tomography angiography image data. In particular, we compared our approach with an approach based on the randomized Hough transform. Moreover, a validation of the segmentation results based on ground truth provided by a radiologist confirms the accuracy of the new approach. Our experiments show that the new model yields superior results in estimating the vessel radius compared to previous approaches based on a Gaussian model as well as the Hough transform.

Localization of anatomical point landmarks in 3D medical images by fitting 3D parametric intensity models.

We introduce a new approach for the localization of 3D anatomical point landmarks based on 3D parametric intensity models which are directly fit to the image. We propose an analytic intensity model based on the Gaussian error function in conjunction with 3D rigid transformations as well as deformations to efficiently model tip-like structures of ellipsoidal shape. The approach has been successfully applied to accurately localize anatomical landmarks in 3D MR and 3D CT image data. We have also compared the experimental results with the results of a previously proposed 3D differential operator. It turns out that the new approach significantly improves the localization accuracy.

Elastic registration of electrophoresis images using intensity information and point landmarks

A key technique for protein analysis is the geometric alignment of gel electrophoresis images. While in previous work either intensity- or landmark-based approaches have been used for the registration of electrophoresis images, we here introduce a scheme incorporating both intensity and landmark information. With this approach, point landmarks are localized using a model fitting scheme and this geometric information is combined with intensity information for elastic image registration. By experiments on the basis of electrophoresis images of different levels of complexity, we demonstrate that the intensity information alone is generally not sufficient to accurately register corresponding images. However, it turns out that the incorporation of landmarks significantly improves the registration accuracy. This is supported by quantitative results.

A model for the self-organization of exit sites in the endoplasmic reticulum.

Exit sites (ES) are specialized domains of the endoplasmic reticulum (ER) at which cargo proteins of the secretory pathway are packaged into COPII-coated vesicles. Although the essential COPII proteins (Sar1p, Sec23p-Sec24p, Sec13p-Sec31p) have been characterized in detail and their sequential binding kinetics at ER membranes have been quantified, the basic processes that govern the self-assembly and spatial organization of ERES have remained elusive. Here, we have formulated a generic computational model that describes the process of formation of ERES on a mesoscopic scale. The model predicts that ERES are arranged in a quasi-crystalline pattern, while their size strongly depends on the cargo-modulated kinetics of COPII turnover – that is, a lack of cargo leads to smaller and more mobile ERES. These predictions are in favorable agreement with experimental data obtained by fluorescence microscopy. The model further suggests that cooperative binding of COPII components, for example mediated by regulatory proteins, is a key factor for the experimentally observed organism-specific ERES pattern. Moreover, the anterograde secretory flux is predicted to grow when the average size of ERES is increased, whereas an increase in the number of (small) ERES only slightly alters the flux.

Respiratory motion compensation for CT-guided interventions in the liver

Computed tomography (CT) guided minimally invasive procedures in the liver, such as tumor biopsy and thermal ablation therapy, require precise targeting of hepatic structures that are subject to breathing motion. To facilitate needle placement, we introduced a navigation system which uses needle-shaped optically tracked navigation aids and a real-time deformation model to continuously estimate the position of a moving target. In this study, we assessed the target position estimation accuracy of our system in vitro with a custom-designed respiratory liver motion simulator. Several real-time compatible transformations were compared as a basis for the deformation model and were evaluated in a set of experiments using different arrangements of three navigation aids in two porcine and two human livers. Furthermore, we investigated different placement strategies for the case where only two needles are used for motion compensation. Depending on the transformation and the placement of the navigation aids, our system yielded a root mean square (RMS) target position estimation error in the range of 0.7 mm to 2.9 mm throughout the breathing cycle generated by the motion simulator. Affine transformations and spline transformations performed comparably well (overall RMS < 2 mm) and were considerably better than rigid transformations. When two navigation aids were used for motion compensation instead of three, a diagonal arrangement of the needles yielded the best results. This study suggests that our navigation system could significantly improve the clinical treatment standard for CT-guided interventions in the liver.

Physics-based elastic registration using non-radial basis functions and including landmark localization uncertainties

We introduce a new approximation approach for landmark-based elastic image registration using Gaussian elastic body splines (GEBS). We formulate an extended energy functional related to the Navier equation under Gaussian forces which allows to individually weight the landmarks according to their localization uncertainties. These uncertainties are characterized either by scalar weights or by weight matrices representing isotropic or anisotropic errors. Since the approach is based on a physical deformation model, cross-effects in elastic deformations can be taken into account. Moreover, with Gaussian forces we have a free parameter to control the locality of the transformation for improved registration of local geometric image differences. We demonstrate the applicability of our scheme based on analytic experiments, 3D CT images from the Truth Cube experiment, as well as 2D MR images of the brain. From the experiments it turned out that the new approximating GEBS approach achieves more accurate registration results in comparison to previously proposed interpolating GEBS as well as interpolating and approximating TPS.

PML induces compaction, TRF2 depletion and DNA damage signaling at telomeres and promotes their alternative lengthening.

ABSTRACT The alternative lengthening of telomeres (ALT) mechanism allows cancer cells to escape senescence and apoptosis in the absence of active telomerase. A characteristic feature of this pathway is the assembly of ALT-associated promyelocytic leukemia (PML) nuclear bodies (APBs) at telomeres. Here, we dissected the role of APBs in a human ALT cell line by performing an RNA interference screen using an automated 3D fluorescence microscopy platform and advanced 3D image analysis. We identified 29 proteins that affected APB formation, which included proteins involved in telomere and chromatin organization, protein sumoylation and DNA repair. By integrating and extending these findings, we found that APB formation induced clustering of telomere repeats, telomere compaction and concomitant depletion of the shelterin protein TRF2 (also known as TERF2). These APB-dependent changes correlated with the induction of a DNA damage response at telomeres in APBs as evident by a strong enrichment of the phosphorylated form of the ataxia telangiectasia mutated (ATM) kinase. Accordingly, we propose that APBs promote telomere maintenance by inducing a DNA damage response in ALT-positive tumor cells through changing the telomeric chromatin state to trigger ATM phosphorylation.

3D Geometry-Based Quantification of Colocalizations in Multichannel 3D Microscopy Images of Human Soft Tissue Tumors

We introduce a new model-based approach for automatic quantification of colocalizations in multichannel 3D microscopy images. The approach uses different 3D parametric intensity models in conjunction with a model fitting scheme to localize and quantify subcellular structures with high accuracy. The central idea is to determine colocalizations between different channels based on the estimated geometry of the subcellular structures as well as to differentiate between different types of colocalizations. A statistical analysis was performed to assess the significance of the determined colocalizations. This approach was used to successfully analyze about 500 three-channel 3D microscopy images of human soft tissue tumors and controls.

Measurements of lenticulostriate arteries using 7T MRI: new imaging markers for subcortical vascular dementia

Recent studies have demonstrated that ultra-high resolution MRA imaging using 7 Tessla (T) MRI can be employed to noninvasively visualize the lenticulostriate arteries (LSA) that supply the basal ganglia and internal capsule. Subcortical vascular dementia (SVaD) is believed to involve these regions from an early stage. We investigated whether LSA abnormalities measured by 7T MRA correlate with MRI ischemia markers and neuropsychological/motor deficits. A total of 24 subjects (12 with SVaD, 12 normal controls (NC)) were imaged with 3T and 7T MRIs. We assessed the severity of white matter hyperintensities (WMH) and the number of lacunes and microbleeds (MB) by visually inspecting images obtained from conventional 3T MRI. We also analyzed three-dimensional models of the measured LSAs obtained from 7T MRI. Compared to the NC, the SVaD subjects had fewer branches of LSAs and greater radii of LSAs. The number of branches was correlated with the number of lacunes. The number of branches was correlated with the delayed recall scores on Reys Complex Figure Test (RCFT). While not quite reaching statistical significance, the immediate recall, recognition scores on the RCFT, recognition scores on the Seoul Verbal Learning Test, and the word and color readings of Stroop trended in the direction of correlation with the number of branches, as well as with the extrapyramidal scores. Our findings suggest that LSA imaging using 7T MRI might be a potent candidate for the detection of SVaD.