Florian Weiler

• Medical imaging is nowadays capable of non-invasively displaying the human brain in manifold ways. Computer assisted analysis of such data has become a highly active area of research. Today, there exists a wealth of published methods addressing a broad spectrum of medical questions. Considering the maturity to which this field of research has grown by now raises expectations that most basic problems should actually be solved and even many of the more complex task should at least be manageable. However, looking at the role of image-based quantification in everyday clinical practice, draws a completely different picture. The de-facto standard approach in diagnostic radiology is a purely qualitative reading through human experts. Quantification, if used at all, is typically limited to simple measurements on single image-slices. Without debate, there exists a huge gap between what would be potentially possible as defined by the scientific state-of-the-art, and clinical reality. This PhD thesis addresses this situation. It studies three general concepts aiming at objective image assessment: 1) quantification; 2) interactive segmentation; 3) interactive data-visualization. For each of these concepts, an exemplary application is chosen, and a novel method is proposed with a focus on fulfilling requirements that, if not met, would prevent integration into clinical workflows. First, I present a method for robust assessment of upper-spinal cord atrophy, a parameter which has been successfully correlated to several clinical markers in the context of multiple sclerosis. Second, I present two novel interactive tools for segmenting individual gyri of the brain and regions-of-interest in DTI data. Finally, I present an example of how interactive 3D visualizations combined with efficient tools for exploration of image data can support the planning process of complex neurosurgical interventions.