Volumetric data for scientific purposes and applications are made increasingly available with novel modes of acquisition and modelling, which need to be visualised in order to understand the data and derive structured insight. Various methods for volume visualisation exist, while a persisting challenge is the interaction and delineation of object of interest within the data. Transfer functions, commonly used in medical visualisation, are the established means of interaction, which are cognitively challenging to setup and understand. This article presents new approaches for the coupled visualisation of volumetric data and their statistical derivatives to support the interactive data exploration. The presented techniques improve the means of volumetric data exploration in scientific disciplines and application cases for which established transfer function techniques are inadequate, such as structuraland petroleum geology.
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