Magnetic Resonance Imaging (MRI) is an indispensable diagnostic and monitoring tool for many neurological and psychiatric diseases - especially due to its excellent soft tissue contrast. Conventional MR signal intensity units, however, are predominantly qualitative and are influenced by the acquisition technique as well as by the MRI hard- and software. Moreover, anatomical information in digital images is not contained in the absolute image intensity values but depends on the regional relationship between intensities. We thus require formidable computational effort in concert with heuristic approaches to derive quantitative information at image post-processing.

The extraction of quantitative data from MR images is a central prerequisite to increase diagnostic accuracy, decrease the variability and subjectivity of image analysis, increase automation of data reporting, and finally, to strengthen the association of imaging findings with other biological and clinical parameters. For this reason, development, standardization, optimization and application of MRI acquisition protocols and post-processing methods allowing to extract quantitative imaging metrics are subject of our ongoing research. Our current research topics include: advanced tissue characterization, analyses of different contrast mechanisms, identification of image-based biomarkers and development of standardization or data homogenization pipelines.

qbig closely collaborates with the Medical Image Analysis Center (MIAC) AG, the AMT (Adaptable MRI Technology) lab, the CIAN (Center for medical Image Analysis and Navigation), the ThINk (Translational Imaging in Neurology) group at the Department of Biomedical Engineering and the Departments of Neurology and Radiology at the University Hospital of Basel. The lab is supported by the SNSF.