Visualizing inner structures in multimodal volume data

With the evolution of medical image acquisition techniques, the capacity and fidelity of image-based diagnosis were extended. The current trend is to acquire information using multiple sources to help medical diagnosis, but the integration of the multivariate data into a single 3D representation is non-trivial. Techniques for the visualization of multimodal volume data have been developed with the goal of finding suitable strategies to integrate characteristics of multiple data sets into a single visual representation. Likewise, several techniques are dedicated to the exploration of different ways of incorporating seeing-through capabilities into volume rendering techniques. This paper presents a new approach to visualize inner structures in multimodal volume data, which is based in the utilization of cutting tools.