Automated shape modeling and analysis of brain ventricles : findings in the spectrum from normal cognition to Alzheimer disease
Ferrarini, L.
Citation
Ferrarini, L. (2008, March 19). Automated shape modeling and analysis of brain ventricles : findings in the spectrum from normal cognition to Alzheimer disease. Retrieved from https://hdl.handle.net/1887/12654
Version: Corrected Publisher’s Version
License: Licence agreement concerning inclusion of doctoral thesis in the Institutional Repository of the University of Leiden
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S TELLINGEN
1. Variations in biological shapes can reasonably be described by statistical models over a large popu- lation of similar instances. This manuscript
2. Volume and area measurements were originally used for such studies, but recently more sophisticated shape based techniques have been used to identify statistical differences in the shape of a particular organ in different subject groups. Golland et al., IPMI 2001
3. Growing and Adaptive MEshes (GAMES) are used to model different instances of similar objects, addressing the problem of point correspondence in a straightforward way. Because of its generality, GAMES can easily be applied to the modeling of different organs. This manuscript
4. Quantitative analysis of ventricular shape changes is a powerful tool to estimate atrophy in periven- tricular structures. This manuscript This manuscript
5. The intensity contrast between white and gray matter structures decreases considerably with age, making it a more difficult and less accurate task to delineate periventricular structures in MR. On the other hand, the contrast between CSF and the remaining parenchyma stays sharp in elderly, allowing automatic tools to reliably segment ventricular CSF. This manuscript
6. Therapies developed to slow down the cognitive decline have been proved more effective if admin- istered during the early stage of the disease: consequently, biomarkers for early diagnosis are highly desirable. This manuscript
7. The ideal surrogate MR marker should be able to detect a fundamental feature of Alzheimer’s neu- ropathology, be diagnostically sensitive and specific through validation in neuropathologically con- firmed cases, and be precise with good test-retest reproducibility for monitoring the therapeutic ef- fects on the pathology. Kantarci et al., NeuroRX 2004
8. So far, there is no established method to predict progression to Alzheimer’s disease in individuals with MCI. New tools to aid in the diagnostic work-up of individuals with MCI would be of fundamental public-health importance. Hansson et al., Lancet Neurol 2006
9. Quality of any work comes from the passion you put in it.
10. Information is the resolution of uncertainty. Claude Shannon
11. Einstein was a giant. His head was in the clouds, but his feet were on the ground. Those of us who are not so tall have to choose! Richard Feynman
12. Science is all about modeling reality as we perceive it.
Automated Shape Modeling and Analysis of Brain Ventricles L. Ferrarini
