Tag Archives: Technology Ettention

NOTOX

NOTOX is one of the building block projects of the European research initiative SEURAT (safety evaluation ultimately replacing animal testing) funded by EU-FP7 HEALTH programme and the European Cosmetics Association (Cosmetics Europe). The total funding for the cluster projects is 50 million €. This initiative with six projects as building blocks aims at the common strategy “towards the replacement of current repeated dose systemic toxicity testing in human safety assessment”.

Tomographic reconstruction of an electron tomography tilt series. Image from [1].

DFKI Participated in NOTOX by providing high performance implementations of iterative tomographic reconstruction algorithms for electron tomography using the Ettention software package.

[1] T. Dahmen et al., The Ettention software package, Ultramicroscopy 161 (2016) 110–118.

Ettention

Ettention is a software package for tomographic reconstruction in electron tomography. It implements the algorithms simultaneous algebraic reconstruction technique (SART), simultaneous iterative reconstruction technique (SIRT) and a generic, block-iterative reconstruction algorithm. Ettention is written in C++ and internally uses OpenCL to run on a large number of high-performance computing.

Tomographic reconstructions performed using the Ettention software package. Images from [1].

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Computational 3D Imaging

Team Computational 3D Imaging

The team conducts bleeding edge research on algorithmic questions with different applications in microscopy and three-dimensional imaging. The broader research question is: how can one obtain a maximum of information about a sample? Hereby, we consider several aspects of 3D imaging. How can we incorporate different kind of prior knowledge about the microscope, the specimen, or the physics of image formation into reconstruction algorithms to obtain better reconstructions from existing projections? What are optimal recording schemes to obtain 3D information? Specifically, how can adaptive sampling schemes augment the information content of a dataset already during the acquisition? And finally: how can simulations be used to make  physical quantities that can not easily be observed directly, appear in a three-dimensional dataset. For example, can we use finite element simulations to enhance a tomogram with residual stress vectors?

Scanning Electron Microscope image of cast iron acquired using an adaptive scanning method.

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