Intuitive Error Space Exploration of Medical Image Data in Clinical Daily Routine

Authors

Christina Gillmann
Pablo Arbeláez
José Tiberio Hernández Peñaloza
Hans Hagen
Thomas Wischgoll, Wright State University - Main CampusFollow

Document Type

Conference Proceeding

Publication Date

6-12-2017

Abstract

Medical image data can be affected by several image errors. These errors can lead to uncertain or wrong diagnosis in clinical daily routine. A large variety of image error metrics are available that target different aspects of image quality forming a highdimensional error space, which cannot be reviewed trivially. To solve this problem, this paper presents a novel error space exploration technique that is suitable for clinical daily routine. Therefore, the clinical workflow for reviewing medical data is extended by error space cluster information, that can be explored by user-defined selections. The presented tool was applied to two real-world datasets to show its effectiveness.

Comments

Presented at the 19th EG/VGTC Conference of Visualization (EuroVis 2017), Barcelona, Spain, June 12-16, 2017.

Repository Citation

Gillmann, C., Arbeláez, P., Peñaloza, J. T., Hagen, H., & Wischgoll, T. (2017). Intuitive Error Space Exploration of Medical Image Data in Clinical Daily Routine. .
https://corescholar.libraries.wright.edu/cse/493

DOI

10.2312/eurovisshort.20171148