Accurate localization of brain activity in presurgical fMRI by structure adaptive smoothing
Please always quote using this URN:urn:nbn:de:0296-matheon-3420
- An important problem of the analysis of fMRI experiments is to achieve some noise reduction of the data without blurring the shape of the activation areas. As a novel solution to this problem, the Propagation-Separation approach (PS), a structure adaptive smoothing method, has been proposed recently. PS adapts to different shapes of activation areas by generating a spatial structure corresponding to similarities and differences between time series in adjacent locations. In this paper we demonstrate how this method results in more accurate localization of brain activity. First, it is shown in numerical simulations that PS is superior over Gaussian smoothing with respect to the accurate description of the shape of activation clusters and and results in less false detections. Second, in a study of 37 presurgical planning cases we found that PS and Gaussian smoothing often yield different results, and we present examples showing aspects of the superiority of PS as applied to presurgical planning.
Author: | Karsten Tabelow, Jörg Polzehl, Aziz M. Uluğ, Jonathan P. Dyke, Richard Watts, Linda A. Heier, Henning U. Voss |
---|---|
URN: | urn:nbn:de:0296-matheon-3420 |
Referee: | Christof Schütte |
Document Type: | Preprint, Research Center Matheon |
Language: | English |
Date of first Publication: | 2006/09/11 |
Release Date: | 2006/06/06 |
Tag: | |
Institute: | Weierstraß-Institut für Angewandte Analysis und Stochastik (WIAS) |
MSC-Classification: | 62-XX STATISTICS / 62Gxx Nonparametric inference / 62G05 Estimation |
62-XX STATISTICS / 62Gxx Nonparametric inference / 62G10 Hypothesis testing | |
62-XX STATISTICS / 62Pxx Applications [See also 90-XX, 91-XX, 92-XX] / 62P10 Applications to biology and medical sciences | |
92-XX BIOLOGY AND OTHER NATURAL SCIENCES / 92Cxx Physiological, cellular and medical topics / 92C55 Biomedical imaging and signal processing [See also 44A12, 65R10] | |
Preprint Number: | 357 |