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 …

Visual Computing for Medicine, Second Edition, offers cutting-edge visualization techniques
and their applications in medical diagnosis, education, and treatment. The book includes …

We present a differentiable volume rendering solution that provides differentiability of all
continuous parameters of the volume rendering process. This differentiable renderer is used …

Designing volume visualizations showing various structures of interest is critical to the
exploratory analysis of volumetric data. The last few years have witnessed dramatic …

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 …

Transfer function (TF) design is a central topic in direct volume rendering. The TF
fundamentally translates data values into optical properties to reveal relevant features …

Complex volume rendering tasks require high‐dimensional transfer functions, which are
notoriously difficult to design. One solution to this is to learn transfer functions from scribbles …

In this paper, we present a novel feature extraction approach called FLDA for unsteady flow
fields based on Latent Dirichlet allocation (LDA) model. Analogous to topic modeling in text …

In this paper, we propose a novel machine learning-based voxel classification method for
highly-accurate volume rendering. Unlike conventional voxel classification methods that …

The 2D transfer function based on scalar value and gradient magnitude (SG-TF) is popularly
used in volume rendering. However, it is plagued by the boundary-overlap** problem …