Dorit Merhof works as an Assistant Professor for Visual Computing at the University of Konstanz, Germany.
Title: Reconstruction and Visualization of Neuronal Pathways from Diffusion Tensor Data
Abstract: For diagnosis and surgical planning, magnetic resonance imaging (MRI) has become an important source of medical data. About a decade ago, a novel MRI technique called diffusion tensor imaging (DTI) evolved. Due to its ability to reflect the location and structure of fibrous tissue such as white matter in vivo, this technique has gained increasing interest in different research disciplines.
For neurosurgery, DTI data is of high value since information about the location and the course of white matter tract systems is provided, thus supporting the anatomical information obtained from MRI. White matter tracts, i.e. motor or sensory pathways, are important structures within the human brain. In order to avoid neurological deficits after brain surgery, these fiber tracts must remain intact. However, the reconstruction of neuronal structures from DTI data is a non-trivial task due to the complex tensor information that is captured per voxel. For this reason, extensive research has been conducted in recent years in order to develop techniques for the processing and visualization of DTI tensor data.
In this talk, new techniques for the reconstruction and visualization of white matter tracts are presented which contribute to current research. The different approaches were developed in collaboration with neurosurgeons and are intended to support preoperative planning and intraoperative guidance in surgical interventions. For this purpose, a DTI toolbox comprising dataset processing, tensor reconstruction, filtering techniques, fiber tracking and connectivity analysis, hull algorithms and different visualization approaches has been developed. In future, the research currently conducted in the field of DTI will contribute to the further improvement of planning in neurosurgery and to the reduction of the inherent risk of postoperative neurological deficits for the patients.
