ParaGlyder: Probe-driven Interactive Visual Analysis for Multiparametric Medical Imaging Data
| Autor: | Noeska N. Smit, Ingfrid S. Haldorsen, Stefan Bruckner, Eric Mörth |
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| Rok vydání: | 2020 |
| Předmět: |
Computer science
business.industry 020207 software engineering 02 engineering and technology medicine.disease Machine learning computer.software_genre Primary tumor 030218 nuclear medicine & medical imaging Domain (software engineering) 03 medical and health sciences Tumor detection 0302 clinical medicine Interactive visual analysis Voxel 0202 electrical engineering electronic engineering information engineering medicine Artificial intelligence Medical imaging data business computer |
| Zdroj: | Advances in Computer Graphics ISBN: 9783030618636 CGI |
| DOI: | 10.1007/978-3-030-61864-3_29 |
| Popis: | Multiparametric imaging in cancer has been shown to be useful for tumor detection and may also depict functional tumor characteristics relevant for clinical phenotypes. However, when confronted with datasets consisting of multiple values per voxel, traditional reading of the imaging series fails to capture complicated patterns. These patterns of potentially important imaging properties of the parameter space may be critical for the analysis, but standard approaches do not deliver sufficient details. Therefore, in this paper, we present an approach that aims to enable the exploration and analysis of such multiparametric studies using an interactive visual analysis application to remedy the trade-offs between details in the value domain and in spatial resolution. This may aid in the discrimination between healthy and cancerous tissue and potentially highlight metastases that evolved from the primary tumor. We conducted an evaluation with eleven domain experts from different fields of research to confirm the utility of our approach. |
| Databáze: | OpenAIRE |
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