Visual Analytics of Group Differences in Tensor Fields: Application to Clinical DTI

TL;DR

This paper introduces a visual analytics system for exploring group differences in tensor fields, combining quantitative hypothesis testing with visualization to interpret complex DTI data, revealing new clinical insights.

Contribution

The paper presents a novel integrated visual analytics framework for tensor field analysis that combines statistical testing with visualization, specifically applied to clinical DTI data.

Findings

Identified previously unknown group differences in SLE using the system.

Enabled detailed interpretation of tensor differences through linked visualizations.

Facilitated hypothesis generation and exploration in tensor data analysis.

Abstract

We present a visual analytics system for exploring group differences in tensor fields with respect to all six degrees of freedom that are inherent in symmetric second-order tensors. Our framework closely integrates quantitative analysis, based on multivariate hypothesis testing and spatial cluster enhancement, with suitable visualization tools that facilitate interpretation of results, and forming of new hypotheses. Carefully chosen and linked spatial and abstract views show clusters of strong differences, and allow the analyst to relate them to the affected structures, to reveal the exact nature of the differences, and to investigate potential correlations. A mechanism for visually comparing the results of different tests or levels of smoothing is also provided. We carefully justify the need for such a visual analytics tool from a practical and theoretical point of view. In close collaboration with our clinical co-authors, we apply it to the results of a diffusion tensor imaging study of systemic lupus erythematosus, in which it revealed previously unknown group differences.