Helmuth Schramm

A Dual Dynamic Programming Approach to the Detection of Spine Boundaries

Spine boundary is one of the key landmarks for quantifying deformities of pathological spines. In this paper, we propose a new approach to the detection of spine boundaries. We integrate two dynamic programming procedures into a single one to enable constraints between the left and right parts of the boundary to be enforced. This dual dynamic programming approach detects two boundary curves at the same time. Moreover we propose to use angular limits in a piecewise linear model as a new smoothness constraint. This leads to a computationally efficient way of introducing high order priors. Experimental results show a very robust performance of the method.

Method for intensity correction in CR mosaic by combined nonlinear and linear transformations

In this paper, we present a method to correct for intensity artifacts in mosaic composition of Computed Radiography (CR) images. The white band artifacts not only distort diagnostic information, but also cause visual disturbances in the examination by physicians. We propose a hybrid method to enhance the image intensity and to correct the brightness differences. A nonlinear transformation method is presented for enhancement, whereas a linear regression method is utilized to compensate for the intensity differences between the white band and normal exposure regions. A knowledge-based method is proposed which can autonomously decide whether the nonlinear enhancement step needs to be bypassed, since in some cases over-enhancement may result from the correction algorithm. Experimental results with different images are presented to show the effectiveness of the proposed method.