Uncertainty-aware Brain Lesion Visualization
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Date
2020
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
A brain lesion is an area of tissue that has been damaged through injury or disease. Its analysis is an essential task for medical researchers to understand diseases and find proper treatments. In this context, visualization approaches became an important tool to locate, quantify, and analyze brain lesions. Unfortunately, image uncertainty highly effects the accuracy of the visualization output. These effects are not covered well in existing approaches, leading to miss-interpretation or a lack of trust in the analysis result. In this work, we present an uncertainty-aware visualization pipeline especially designed for brain lesions. Our method is based on an uncertainty measure for image data that forms the input of an uncertainty-aware segmentation approach. Here, medical doctors can determine the lesion in the patient's brain and the result can be visualized by an uncertainty-aware geometry rendering. We applied our approach to two patient datasets to review the lesions. Our results indicate increased knowledge discovery in brain lesion analysis that provides a quantification of trust in the generated results.
Description
@inproceedings{10.2312:vcbm.20201176,
booktitle = {Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {KozlÃková, Barbora and Krone, Michael and Smit, Noeska and Nieselt, Kay and Raidou, Renata Georgia},
title = {{Uncertainty-aware Brain Lesion Visualization}},
author = {Gillmann, Christina and Saur, Dorothee and Wischgoll, Thomas and Hoffmann, Karl-Titus and Hagen, Hans and Maciejewski, Ross and Scheuermann, Gerik},
year = {2020},
publisher = {The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-109-0},
DOI = {10.2312/vcbm.20201176}
}