Project ASTOR_NOVAIPE/ KIT

ASTOR / NOVA

  • contact:

    Dr. Andreas Kopmann

  • funding:

    BMBF Verbundforschung

  • Partner:

     KIT-ITIV, KIT-IPE, KIT-IPS, TU Darmstadt, U Heidelberg, HZG

  • startdate:

    2013

  • enddate:

    2020

X-ray tomography provides a unique opportunity to visualize internal structures of optically dense materials. But analyzing such 3D volumes is time consuming and technically challenging. The projects ASTOR and NOVA aim to establish efficient tools for data analysis of high-throughput tomography by combing optimized data acquisition and processing, semi-automated data analysis and the creation of an online-portal providing easy access and 3D-visualization.

ASTOR – Arthropod Structure revealed by ultrafast Tomography and Online Reconstruction

X-rays and tomography provide the opportunity to visualize internal structures of optically dense materials in 3D. The invention of synchrotron-X-ray-microtomography was the onset of a new era of morphological research on microscopically small animals (e.g. micro-arthropods). Analyzing such 3D-data is time consuming and technically challenging. Especially the automation of classification processes needs close cooperation of biologists and image processing experts. Using the most speciose animal group on earth (arthropods) as a model system, the network for functional morphology and systematics aims to establish and standardize measuring parameters to meet the needs of a broad range of biological research. This will be achieved by optimizing data acquisition and processing, semi-automation of data analysis (reconstruction and segmentation/classification) and the creation of an online-portal providing easy access, 3D-visualization and semi-automatic analyses of the data using cloud technologies.

 

Publications:

  • Low-latency Big Data Visualisation - Tan Jerome, Nicholas PhD thesis, Faculty of Electrical Engineering and Information Technology, Karlsruhe Institute of Technology, 2019. Abstract Exploring large and complex data sets is a crucial factor in a digital library framework. To find a specific data set within a large repository, visualisation can help to validate the content apart from the textual description. However, ...
  • The NOVA project: Maximizing beam time efficiency through synergistic analyses of SRμCT data - Schmelzle S. et al., in Proceedings of SPIE - The International Society for Optical Engineering, 10391 (2017), 103910P.