Publication Type |
journal article |
School or College |
<blank> |
Department |
<blank> |
Creator |
Gerig, Guido |
Other Author |
Joshi, S.; Fletcher, P. T.; Gorczowski, K.; Xu, S.; Pizer, S. M.; Styner, M. |
Title |
Statistics of populations of images and its embedded objects: driving applications in neuroimaging |
Date |
2006-01-01 |
Description |
Work in progress towards modeling shape statistics of multi-object complexes is presented. Constraints defined by the set of objects such as a compact representation of object shape relationships and correlation of shape changes might have advantages for automatic segmentation and group discrimination. We present a concept for statistical multi-object modeling and discuss the major challenges which are a reduction to a small set of descriptive features, calculation of mean and variability via curved statistics, the choice of aligning sets of multiple objects, and the problem of describing the statistics of object pose and object shape and their interrelationship. Shape modeling and analysis is demonstrated with an application to a longitudinal autism study, with shape modeling of sets of 10 subcortical structures in a population of 20 subjects. |
Type |
Text |
Publisher |
Institute of Electrical and Electronics Engineers (IEEE) |
First Page |
1120 |
Last Page |
1123 |
Language |
eng |
Bibliographic Citation |
Gerig, G., Joshi, S., Fletcher, P. T., Gorczowski, K., Xu, S., Pizer, S. M., & Styner, M. (2006). Statistics of populations of images and its embedded objects: driving applications in neuroimaging. Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI), 1120-3. |
Rights Management |
(c) 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. |
Format Medium |
application/pdf |
Format Extent |
369,600 bytes |
Identifier |
uspace,19271 |
ARK |
ark:/87278/s6gx7mp7 |
Setname |
ir_uspace |
ID |
712808 |
Reference URL |
https://collections.lib.utah.edu/ark:/87278/s6gx7mp7 |