Abstract
IntroductionA geostatistical approach to characterize MS-lesion patterns based on their geometrical properties is presented. MethodsA dataset of 259 binary MS-lesion masks in MNI space was subjected to directional variography. A model function was fit to express the observed spatial variability in x, y, z directions by the geostatistical parameters Range and Sill. ResultsParameters Range and Sill correlate with MS-lesion pattern surface complexity and total lesion volume. A scatter plot of ln(Range) versus ln(Sill), classified by pattern anisotropy, enables a consistent and clearly arranged presentation of MS-lesion patterns based on geometry: the so-called MS-Lesion Pattern Discrimination Plot. ConclusionsThe geostatistical approach and the graphical representation of results are considered efficient exploratory data analysis tools for cross-sectional, follow-up, and medication impact analysis.
| Item Type: | Journal article |
|---|---|
| Faculties: | Mathematics, Computer Science and Statistics > Statistics |
| Subjects: | 500 Science > 510 Mathematics |
| URN: | urn:nbn:de:bvb:19-epub-38034-5 |
| ISSN: | 2162-3279 |
| Language: | English |
| Item ID: | 38034 |
| Date Deposited: | 04. May 2017 13:11 |
| Last Modified: | 04. Nov 2020 14:45 |

