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To achieve a detailed understanding of processes in biological systems, cellular features must be quantified in the three-dimensional (3D) context of cells and organs. We described use of the intrinsic root coordinate system (iRoCS) as a reference model for the root apical meristem of plants. iRoCS enables direct and quantitative comparison between the root(More)
In this paper, we aim for detection and segmentation of Ara-bidopsis thaliana cells in volumetric image data. To this end, we cluster the training samples by their size and aspect ratio and learn a detector and a shape model for each cluster. While the detector yields good cell hypotheses, additionally aligning the shape model to the image allows to better(More)
Numerical simulation plays an important role in product design. Its accuracy relays on a detailed description of geometry, material models, load and boundary conditions. This paper focuses on a new approach of FEM material modeling of three commercially available molding compounds. Curing shrinkage, modulus of elasticity and coefficient of thermal expansion(More)
In this paper internal stress state measurements in a large molded electronic control unit are discussed. Measurements were done during transfer molding process in a high volume production environment. In addition, the effect of the post mold cure (PMC) was investigated. Tests were done utilizing piezoresistive stress sensors and thin film strain gages. For(More)
In this paper, we propose a method for accurate detection and segmentation of cells in dense plant tissue of Arabidopsis Thaliana. We build upon a system that uses a top down approach to yield the cell segmentations: A discriminative detection is followed by an elastic alignment of a cell template. While this works well for cells with a distinct appearance,(More)
Absorption and refraction induced signal attenuation can seriously hinder the extraction of quantitative information from confocal microscopic data. This signal attenuation can be estimated and corrected by algorithms that use physical image formation models. Especially in thick heterogeneous samples, current single view based models are unable to solve the(More)
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