Detection and Visual Analysis of Pathological Abnormalities in Diffusion Tensor Imaging with an Anomaly Lens
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Date
2023
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
In clinical practice, Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) is usually evaluated by visual inspection of grayscale maps of Fractional Anisotropy or mean diffusivity. However, the fact that those maps only contain part of the information that is captured in DT-MRI implies a risk of missing signs of disease. In this work, we propose a visualization system that supports a more comprehensive analysis with an anomaly score that accounts for the full diffusion tensor information. It is computed by comparing the DT-MRI scan of a given patient to a control group of healthy subjects, after spatial coregistration. Moreover, our system introduces an Anomaly Lens which visualizes how a user-specified region of interest deviates from the controls, indicating which aspects of the tensor (norm, anisotropy, mode, rotation) differ most, whether they are elevated or reduced, and whether their covariation matches the covariances within the control group. Applying our system to patients with metachromatic leukodystrophy clearly indicates regions affected by the disease, and permits their detailed analysis.
Description
CCS Concepts: Visualization application domains -> Visual analytics; Life and medical sciences -> Health informatics
@inproceedings{10.2312:evs.20231041,
booktitle = {EuroVis 2023 - Short Papers},
editor = {Hoellt, Thomas and Aigner, Wolfgang and Wang, Bei},
title = {{Detection and Visual Analysis of Pathological Abnormalities in Diffusion Tensor Imaging with an Anomaly Lens}},
author = {Bareth, Marlo and Groeschel, Samuel and Gruen, Johannes and Pretzel, Pablo and Schultz, Thomas},
year = {2023},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-219-6},
DOI = {10.2312/evs.20231041}
}