A central topic in scientific visualization is the transfer function (TF) for volume rendering.
The TF serves a fundamental role in translating scalar and multivariate data into color and …

We present a technique to synthesize and analyze volume-rendered images using
generative models. We use the Generative Adversarial Network (GAN) framework to …

In this paper, we introduce the concept of isosurface similarity maps for the visualization of
volume data. Iso‐surface similarity maps present structural information of a volume data set …

In this paper, we present an effective and scalable system for multivariate volume data
visualization and analysis with a novel transfer function interface design that tightly couples …

In volume visualization, a transfer function tailored for one volume usually does not work for
other similar volumes without careful tuning. This process can be tedious and time …

The transfer function is crucial for direct volume rendering (DVR) to create an informative
visual representation of volumetric data. However, manually adjusting the transfer function to …

In this paper, we present an effective transfer function (TF) design for multivariate volume,
providing tightly coupled views of parallel coordinates plot (PCP), MDS-based dimension …

In the direct volume rendering (DVR), it often takes a long time for a novice to manipulate the
transfer function (TF) and analyze the volume data. To lessen the difficulty in volume …

Multi-dimensional transfer functions are widely used to provide appropriate data
classification for direct volume rendering. Nevertheless, the design of a multi-dimensional …

Finding good transfer functions for rendering medical volumes is difficult, non-intuitive, and
time-consuming. We introduce a clustering-based framework for the automatic generation of …