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| Home > Publications Database > Computational Ontology and Visualization Framework for the Visual Comparison of Brain Atrophy Profiles |
| Contribution to a conference proceedings/Contribution to a book | DZNE-2024-00331 |
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2024
Springer Fachmedien Wiesbaden
Wiesbaden
ISBN: 978-3-658-44036-7 (print), 978-3-658-44037-4 (electronic)
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Please use a persistent id in citations: doi:10.1007/978-3-658-44037-4_43
Abstract: 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.
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