Ralph Brecheisen

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Fiber tracking of diffusion tensor imaging (DTI) data offers a unique insight into the three-dimensional organisation of white matter structures in the living brain. However, fiber tracking algorithms require a number of user-defined input parameters that strongly affect the output results. Usually the fiber tracking parameters are set once and are then(More)
Using combinations of different volumetric datasets is becoming more common in scientific applications, especially medical environments such as neurosurgery where multiple imaging modalities are required to provide insight to both anatomical and functional structures in the brain. Such data sets are usually in different orientations and have different(More)
Diffusion Tensor Imaging (DTI) and fiber tracking provide unique insight into the 3D structure of fibrous tissues in the brain. However, the output of fiber tracking contains a significant amount of uncertainty accumulated in the various steps of the processing pipeline. Existing DTI visualization methods do not present these uncertainties to the end-user.(More)
Given the fact that clinical bedside examinations can have a high rate of misdiagnosis, machine learning techniques based on neuroimaging and electrophysiological measurements are increasingly being considered for comatose patients and patients with unresponsive wakefulness syndrome, a minimally conscious state or locked-in syndrome. Machine learning(More)
Fiber tracking based on diffusion weighted Magnetic Resonance Imaging (dMRI) allows for noninvasive reconstruction of fiber bundles in the human brain. In this chapter, we discuss sources of error and uncertainty in this technique, and review strategies that afford a more reliable interpretation of the results. This includes methods for computing and(More)
BACKGROUND Taking multiple anthropometric measurements for the description of body proportions in an accurate way is a time-consuming procedure that requires specific tools and skills. This is why we developed an alternative method based on digital photography for taking these measurements which is faster and easier to use, to make anthropometry more(More)
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