Hon Prof. Hans-Christian Hege

hege@zib.de


Projects as a project leader

  • F-AP7

    Modeling synaptic connectivity in anatomically realistic neural networks

    Hon Prof. Hans-Christian Hege

    Project heads: Hon Prof. Hans-Christian Hege
    Project members: -
    Duration: 01.07.2014 - 31.12.2015
    Status: completed
    Located at: Konrad-Zuse-Zentrum für Informationstechnik Berlin

    Description

    The goal of the NeuroConnect project is
    • to generate anatomically realistic 3D neural network models,
    • to provide tools to analyze such models and
    • to extract information for numerical simulations of neural activity, particularly the synaptic connectivity.

    This requires the development of new methods to effectively specify, visualize, and quantify the information of interest in these potentially large (>500k neurons) and complex neural networks, as well as efficient data structures to represent and process this data. Methods to extract the anatomical data underlying the network model and the modeling approach have been developed in the past Cortex In Silico project.

    http://www.zib.de/projects/modeling-synaptic-connectivity-anatomically-realistic-neural-networks
  • A-CH8

    X-ray based anatomy reconstruction with low radiation exposure

    Hon Prof. Hans-Christian Hege / Dr. Martin Weiser / Dr.-Ing. Stefan Zachow

    Project heads: Hon Prof. Hans-Christian Hege / Dr. Martin Weiser / Dr.-Ing. Stefan Zachow
    Project members: Dennis Jentsch
    Duration: 01.06.2014 - 31.05.2017
    Status: running
    Located at: Konrad-Zuse-Zentrum für Informationstechnik Berlin

    Description

    Medical imaging is essential in diagnostics and surgery planning. For representation of bony structures different imaging modalities are used; the leading methods are X-ray projection (projectional radiography) and CT. Disadvantage of these imaging techniques is the ionization caused by X-rays, particularly in CT, where the dose is 250-500 times higher than in classic X-ray projection. From the clinical perspective therefore one would like to replace CT acquisitions by a few possible X-ray projections. The project deals with the ill-posed inverse problem of 3D reconstruction of bony structures from 2D radiographs. Virtual radiographs are generated from virtual bone structure models; these are compared with clinical patient images and incrementally changed until a sufficiently accurate bone model is found whose virtual projections fit to the measured data. By using a statistical shape model as prior knowledge it is possible to formulate a well-posed optimization problem in a Bayesian setting. Using gradient methods and multilevel/multiresolution methods for both the reconstruction parameters and image data, good computational performance is achieved. Uncertainty quantification techniques can be applied to describe the spatially varying accuracy of the reconstructed model. Finding best X-ray projections (recording directions) minimizing both uncertainty and radiation exposure leads to a design of experiments problem. Two flavors of this design optimization are considered: An all-at-once approach finding the best image acquisition setup before any X-ray projections are performed, and a sequential approach determining the best next projection direction based on the accumulated knowledge gained from the previously taken images.

    http://www.zib.de/projects/x-ray-based-anatomy-reconstruction-low-radiation-exposure
  • F-AP8

    In vivo and in silico analyses in humans: Cartilage loading of patients' individual knees - the role of soft tissue structures

    Hon Prof. Hans-Christian Hege / Dr. Martin Weiser

    Project heads: Hon Prof. Hans-Christian Hege / Dr. Martin Weiser
    Project members: -
    Duration: 01.10.2014 - 30.09.2018
    Status: running
    Located at: Konrad-Zuse-Zentrum für Informationstechnik Berlin

    Description

    While a relationship between knee joint laxity and osteoarthritis is often assumed, the exact mechanism is not yet fully understood. It is not clear how stabilization by either the cross ligaments or muscle forces affect the local cartilage stress and strain. We develop a comprehensive analysis tool for individual patients. On one hand, we couple a dynamic multibody model to a quasistatic contact solver for the cartilage and validate it against in vivo measurement data from patient groups at Charite. On the other hand, we develop visualization and statistical analysis tools that allow to understand the impact of anatomical variation and cross ligament loss on the mechanical loading of cartilage and correlate this to osteoarthritis progression.

    http://www.zib.de/projects/vivo-and-silico-analyses-humans-cartilage-loading-patients%E2%80%99-individual-knees-%E2%80%93-role-soft-tissue
  • F-AP14

    Modeling Synaptic Connectivity in Anatomically Realistic Neural Networks

    Hon Prof. Hans-Christian Hege

    Project heads: Hon Prof. Hans-Christian Hege
    Project members: -
    Duration: 01.01.2016 - 31.12.2017
    Status: running
    Located at: Konrad-Zuse-Zentrum für Informationstechnik Berlin

    Description

    The goal of the NeuroConnect project is
    • to generate anatomically realistic 3D neural network models,
    • to provide tools to analyze such models and
    • to extract information for numerical simulations of neural activity, particularly the synaptic connectivity.

    This requires the development of new methods to effectively specify, visualize, and quantify the information of interest in these potentially large (>500k neurons) and complex neural networks, as well as efficient data structures to represent and process this data. Methods to extract the anatomical data underlying the network model and the modeling approach have been developed in the past Cortex In Silico project.

    http://www.zib.de/projects/modeling-synaptic-connectivity-anatomically-realistic-neural-networks