This thesis is about hippocampus-based quantitative imaging biomarkers for the prediction of dementia.
The research focussed on the following aspects of the biomarkers:
1) robust segmentation of brain structures on scans with varying acquisition protocols,
2) the predictive value of hippocampal volume, shape, and texture for dementia,
3) spatially aware regression of shape data using P-spline based regression, and
4) a workflow framework for large-scale extraction of biomarkers.

Additional Metadata
Keywords image analysis, dementia, MRI, shape, neuroimaging, magnetic resonance imaging, alzheimer’s disease, diagnosis, prediction, prospective
Promotor W.J. Niessen (Wiro) , M. de Bruijne (Marleen)
Publisher Erasmus University Rotterdam
ISBN 978-94-6332-268-3
Persistent URL hdl.handle.net/1765/102960
Series ASCI dissertation series
Note This work was carried out in the ASCI graduate school. ASCI dissertation series number 383.
Citation
Achterberg, H.C. (2017, December 6). Quantitative Imaging Biomarkers for Hippocampus-based Dementia Prediction (No. 383). ASCI dissertation series. Erasmus University Rotterdam. Retrieved from http://hdl.handle.net/1765/102960