Volumetric peeling: feature centric visualization using membership functions

Surgeons often desire a volume visualization where a region of interest (vessels, tumor) is isolated and viewed with complete clarity in relation to neighboring landmarks. A method to fade the landmarks/ surrounding structures in relation to the region of interest is desired as it provides context and an appreciation of the surgical approach. Current methods for generating these visualizations are either cumbersome (clip--planes) or require significant preprocessing (segmentation). Transfer functions, which can provide this visualization, are limited to datasets where a relation between voxel intensities and structures exists. We present a powerful, easy-to-use method for exploring volumetric data by controlling visibility according to membership volumes. These membership volumes facilitate a plethora of effects that cannot be achieved using conventional classification methods such as transfer functions. The membership volumes allow assignment of optical properties based on a combination of spatial and intensity criteria. Various membership functions, ranging from analytical to distance map based are shown. Through the use of Boolean operations in pixel shaders, we demonstrate several examples of interactive real-time visualization using our method.