Illustrative visualization of cardiac and aortic blood flow from 4D MRI data

Abstract

In the last years, illustrative methods have found their way into flow visualization since they communicate difficult information in a comprehensible way. This is of great benefit especially in domains where the audience does not necessarily have flow expertise. One such domain is the medical field where the development of 4D MR imaging (for in-vivo 3D blood flow measurement) lead to an increased demand for easy flow analysis techniques. The goal and the challenge is to transfer the data into simple visualizations supporting the physician with flow interpretation and decision making. In this work, we take one step towards this goal. We present an approach for the illustrative visualization of steady flow features occurring in 4D MRI data of heart and aorta. Like shown in manually created illustrations, we restrict our visualization to the main data characteristics and do not depict every flow detail. The input for our method are flow features extracted from a dataset's complete set of streamlines with the help of line predicates. We create an abstract depiction of these line bundles by selecting a set of bundle representatives reflecting the most important flow aspects. These lines are rendered as three-dimensional arrows that are fused in areas where they represent the same flow. Since vortices are another important flow information for a physician, we identify these regions in the 4D MRI data and display them as unobtrusive, tube-like structures. A hatching texture provides for a visual effect of rotational blood flow. By applying our illustration technique to diverse flow structures of several 4D MRI datasets, we demonstrate that the abstract visualization is useful to gain an easier insight into the data. Feedback of medical experts confirmed the usefulness and revealed limitations of our work. The images are restricted to the essential flow features and, therefore, clearer and less cluttered. Our method has great potential and offers many possible applications, e.g., in comparative visualization and also beyond the medical domain.