TY  - CONF
AU  - Singh, Devesh
AU  - Dyrba, Martin
A3  - Maier, Andreas
A3  - Deserno, Thomas M.
A3  - Handels, Heinz
A3  - Maier-Hein, Klaus
A3  - Palm, Christoph
A3  - Tolxdorff, Thomas
TI  - Computational Ontology and Visualization Framework for the Visual Comparison of Brain Atrophy Profiles
CY  - Wiesbaden
PB  - Springer Fachmedien Wiesbaden
M1  - DZNE-2024-00331
SN  - 978-3-658-44036-7 (print)
T2  - Informatik aktuell
SP  - 149 - 154
PY  - 2024
N1  - Missing Journal: = 2628-8958 (import from CrossRef Book Series, Journals: pub.dzne.de)
AB  - Alzheimer’s disease (AD) accounts for more than two-thirds of all dementia cases. Existing MRI volumetry tools summarize pathology found within brain MRI scans. However, they often lack methods for aggregating information at different brain abstraction levels, and lack an intuitive visualizations.We propose a computational pipeline for quantifying hierarchical volumetric deviations and generating interactive summary visualizations. We collected N=3115 MRI scans from five different data cohorts. We used the FastSurferCNN tool to obtain brain region segmentations and estimate their raw volumes. First, we created a semantic model, encoding hierarchical anatomical relationships in the web ontology language (OWL) model and a computational framework for aggregating volumetric deviations. Second,we developed a visualization framework, providing interactive visual ‘sunburst’ summary plots. The summary plots can highlight mean-group or single-subject atrophy profiles, enhancing visual comparison of atrophy profiles with different AD phases. Our pipeline could assist clinicians in discovering brain pathologies or subgroups in an interpretable and reliable manner.
T2  - German Conference on Medical Image Computing
CY  - 10 Mar 2024 - 12 Mar 2024, Erlangen (Germany)
Y2  - 10 Mar 2024 - 12 Mar 2024
M2  - Erlangen, Germany
LB  - PUB:(DE-HGF)8 ; PUB:(DE-HGF)7
DO  - DOI:10.1007/978-3-658-44037-4_43
UR  - https://pub.dzne.de/record/268788
ER  -