Recent advances in medical imaging acquisition enable unprecedented opportunities for diagnostic assessment and treatment monitoring. Nevertheless, these advances do not automatically lead to benefits for patient care. There are significant obstacles to overcome regarding human interaction before clinical usefulness can be achieved. The overall objective of this project is: To significantly raise the usability for visualization of complex medical data sets through methods based on continuous adaptation to the tasks and cognitive processes of the end user. The proposed adaptation approach is intended to reduce the cognitive overload while retaining all relevant information and all interaction possibilities. This aim aligns with the overall vision for a visualization system to be a seamless extension of the human cognitive process. The project´s application area is Direct Volume Rendering (DVR) of multivariate data (having several values per data point). The area is chosen partly because of the important emerging acquisition techniques producing such data, partly because of the usage complexity being a huge challenge yet to be met. The proposed project has a cross-disciplinary character, including medical, visualization and human-computer interaction aspects. In the greater perspective, the project does not only aim to contribute to improved visualization solutions, but also to spur improvement of the cognitive strategies employed to solve clinical tasks.
Full Professor at Chalmers, Computer Science and Engineering (Chalmers), Interaction Design (Chalmers)
Funding Chalmers participation during 2012–2016