A craniotomy is a procedure were a neurosurgeon has to open the skull to gain direct access to the brain. When a brain tumor has to be removed from a patient, the craniotomy position is of great importance. This mostly defines the access path from the skull surface to the tumor and thus also what healthy brain tissue will be removed to access to the tumor itself. To minimize the amount of important brain structures that are removed, the craniotomy has to be carefully planned. This is a complex procedure, where a neurosurgeon is required to mentally reconstruct spatial relations of important brain structures to avoid these as much as possible.

We propose a visualization using augmented reality which may assist in the planning of a craniotomy. In this visualization the goal is to show important brain structures aligned with the physical position of the patient. This should allow better perception of the spatial relations of these structures and thus assist the neurosurgeon. Additionally to the visualization of the structures, we created a heat map that is projected on top of the skull. This should give a quick overview of in which areas there are many important structures between the tumor and the skull surface, and should therefore be avoided.

User studies were conducted amongst neurosurgeons and surgeons from other fields to evaluate the proposed visualization. We found that many of the participants indeed thought that the visualization can assist in surgery. For the specific case of craniotomy planning, several improvements have to be made on the heat map before it can be useful. Nevertheless, the visualization of the structures in itself can assist neurosurgeons in the planning of a craniotomy. Although more work has be performed at practical aspects of the visualization to make it ready for clinical experiments.

ProRail uses multiple custom built software applications to control the train infrastructure in the Netherlands. At this moment these applications experience downtime when they are updated. This interrupts processes that are related to controlling the train services. ProRail asked us to redesign an existing application in such a way that updates can be applied with zero downtime.

To solve this problem we use redundancy with automatic load balancing. We compared multiple solutions and we chose to use Docker’s swarm functionality. We then redesigned the non-critical application Brugkijker, an application to monitor trains approaching a bridge. In the end we could successfully run multiple instances of Brugkijker in Docker and show how the application can be incrementally updated, inducing no downtime for the service as a whole and without losing data coming from upstream. This proposed approach can be used by ProRail to make other noncritical and critical applications highly available.