Dr. Rainald Ehrig

PI ECMath Project CHx3 und DFG Project Knee Laxity

Zuse Institute Berlin (ZIB)
Takustr. 7
14195 Berlin
+49 (0) 30 84185-282

Research focus

Numerical Mathematics
Systems Biology

Projects as a project leader

  • CH13

    Empirical Bayes methods for patient-specific prediction and control of pharmacological interventions

    Dr. Rainald Ehrig / Prof. Dr. Susanna Röblitz

    Project heads: Dr. Rainald Ehrig / Prof. Dr. Susanna Röblitz
    Project members: Dr Ilja Klebanov
    Duration: -
    Status: running
    Located at: Konrad-Zuse-Zentrum für Informationstechnik Berlin


    One of the main goals of mathematical modeling related to medical applications is to obtain patient-specific parametrizations and model predictions. In clinical practice, however, the number of available measurements for single patients is usually limited due to time and cost restrictions. This hampers the process of making patient-specific predictions about the outcome of a treatment. On the other hand, data are often available for many patients, in particular if extensive clinical studies have been performed. Empirical Bayes methods can provide a solution to this controversy. Instead of applying Bayes’ rule to each measurement separately, these methods usually boil down to combining all measurements in order to construct an informative prior as a first step and then using this prior for the Bayesian inference of the individual parametrizations in a second step.

  • GV-AP6

    Dynamic Multi-modal Knee Joint Registration for the Analysis of Knee Laxity

    Dr. Rainald Ehrig / Dr.-Ing. Stefan Zachow

    Project heads: Dr. Rainald Ehrig / Dr.-Ing. Stefan Zachow
    Project members: -
    Duration: 01.06.2014 - 31.05.2017
    Status: completed
    Located at: Konrad-Zuse-Zentrum für Informationstechnik Berlin


    Changes in limb or joint anatomy, e.g. due to injury or surgery, may lead to functional impairment. Accurate measurement of skeletal kinematics provides the key to understanding the role of joint instabilities on the onset and progression of degenerative diseases. The aim of the project is to measure knee joint motion in vivo and to identify and characterize joint laxity. In order to assess relative motion of knee joint structures, dynamic medical imaging techniques are used. Possible options are fluoroscopy, dynamic CT, and MRI. The most practical approach is fluoroscopic imaging due to the possibility of imaging knee joint structures during physical exercises at affordable costs. One of the challenges addressed in this project is the reconstruction of anatomical structures from 2D images. Via a combination of MRI and fluoroscopy data and based on the developed 3D reconstruction techniques within the project '3D From Xray' we will assess and improve skin marker-based methods for assessing skeletal dynamics and joint centers.