Jörn Schulz

Statistical Shape Analysis with Applications to Medical Imaging
email: jorn.schulz(at)uit.no
Telephone: +47 456 96 867

Research interests:

My current main research focuses on the statistical analysis and modeling of shapes of 3D objects such as organs in medical imaging with application to segmentation e.g. of the prostate from MR or CT images.

The key point of statistical shape analysis is the introduction of prior knowledge to cope the lack of image contrast between adjacent tissues in medical images where surgical intervention or treatment planning are based on a precise description of internal organs such as the prostate.

This context includes developing of a reasonable object parameterization as much as working with nonlinear high dimension low sample size data. This open a wide area for new nonlinear statistical approaches to perform similar techniques like Principal Component Analysis (PCA) and Distance Weighted Discrimination (DWD) on manifolds.

Furthermore I am interested generally in image analysis, multivariate statistic, Bayesian statistics, non-parametric models as for example adaptive weights smoothing and several kinds of mathematical questions.

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