2D Histogram based volume visualization: combining intensity and size of anatomical structures

Abstract

Surgical planning requires 3D volume visualizations based on transfer functions (TF) that assign optical properties to volumetric image data. Two-dimensional TFs and 2D histograms may be employed to improve overall performance. Anatomical structures were used for 2D TF definition in an algorithm that computes a new structure-size image from the original data set. The original image and structure-size data sets were used to generate a structure-size enhanced (SSE) histogram. Alternatively, the gradient magnitude could be used as second property for 2D TF definition. Both types of 2D TFs were generated and compared using subjective evaluation of anatomic feature conspicuity. Experiments with several medical image data sets provided SSE histograms that were judged subjectively to be more intuitive and better discriminated different anatomical structures than gradient magnitude-based 2D histograms. In clinical applications, where the size of anatomical structures is more meaningful than gradient magnitude, the 2D TF can be effective for highlighting anatomical structures in 3D visualizations.