H.-P. Muller

Publications of H.-P. Muller

• Open magnetic and electric graphic analysis

  Authors: H.-P. Muller, I. Decesaris, M. Demelis, L. Marzetti, A. Pasquarelli, S.N. Erne, A.C. Ludolph, J. Kassubek

  Engineering in Medicine and Biology Magazine, IEEE. 06/2005;

  In this article, a novel analysis technique, open magnetic and electric graphic analysis (OMEGA), is described and is applied to combine MEG and fMRI measurements in a motor task. The study wasIn this article, a novel analysis technique, open magnetic and electric graphic analysis (OMEGA), is described and is applied to combine MEG and fMRI measurements in a motor task. The study was intended to demonstrate how, within OMEGA, the localization of brain activation can be complemented by integrated analysis of human multimodal functional (MEG, fMRI) and anatomical (MRI) measurements. The OMEGA software provides an analysis platform for user-independent, fast, and reproducible multimodal analysis in one single software environment. The implementation of OMEGA allows the analyst to receive comprehensive MEG/fMRI results in a matter of minutes after the measurements have been completed. With OMEGA, the clinical researcher gets comprehensive information in a quick and standardized approach about the sites and the time course of neurological activation, which is useful for clinical applications and diagnostics.

• New methods in fMRI analysis

  Authors: H.-P. Muller, E. Kraft, A. Ludolph, S.N. Erne

  Engineering in Medicine and Biology Magazine, IEEE. 10/2002;

  Hierarchical cluster analysis improves signal-to-noise ratio compared to standard techniques. In this work we present a new approach for improving the SNR in fMRI. The special implementation of theHierarchical cluster analysis improves signal-to-noise ratio compared to standard techniques. In this work we present a new approach for improving the SNR in fMRI. The special implementation of the voxel-based motion-correction algorithms allows for very fast and precise correction of head movements in the frame of the selected model. The hierarchical cluster analysis has proven to be a useful tool for the increase of the SNR of the functional results. As these tools and established deterministic and statistical functional analysis tools are implemented in one software platform (FAMIS), direct comparison between the results becomes feasible. As each analysis result can be obtained within seconds and the user can switch between the display for the different results, direct comparison between the methods can be performed. Deterministic analysis leads to an activation concept that is independent from the noise level, and vice versa the statistical analysis leads to an activation concept where the activation is intended as deviation from noise and in such way the activation becomes related to the noise level. The deterministic methods exclude true positive results with increasing noise, and the statistical methods include false positive results with increasing noise. Nevertheless, the decision regarding which of the methods should be the method of choice for fMRI analysis is not the subject of this work.