Performance quantification of clustering algorithms for false positive removal in fMRI by ROC curves
AUTOR(ES)
Peres, André Salles Cunha, Lemos, Tenysson Will de, Barros, Allan Kardec Duailibe, Baffa Filho, Oswaldo, Araújo, Dráulio Barraos de
FONTE
Res. Biomed. Eng.
DATA DE PUBLICAÇÃO
2017-03
RESUMO
Abstract Introduction Functional magnetic resonance imaging (fMRI) is a non-invasive technique that allows the detection of specific cerebral functions in humans based on hemodynamic changes. The contrast changes are about 5%, making visual inspection impossible. Thus, statistic strategies are applied to infer which brain region is engaged in a task. However, the traditional methods like general linear model and cross-correlation utilize voxel-wise calculation, introducing a lot of false-positive data. So, in this work we tested post-processing cluster algorithms to diminish the false-positives. Methods In this study, three clustering algorithms (the hierarchical cluster, k-means and self-organizing maps) were tested and compared for false-positive removal in the post-processing of cross-correlation analyses. Results Our results showed that the hierarchical cluster presented the best performance to remove the false positives in fMRI, being 2.3 times more accurate than k-means, and 1.9 times more accurate than self-organizing maps. Conclusion The hierarchical cluster presented the best performance in false-positive removal because it uses the inconsistency coefficient threshold, while k-means and self-organizing maps utilize a priori cluster number (centroids and neurons number); thus, the hierarchical cluster avoids clustering scattered voxels, as the inconsistency coefficient threshold allows only the voxels to be clustered that are at a minimum distance to some cluster.
Documentos Relacionados
- InferÃncia baseada em voxel para fMRI
- Brain Switch for Reflex Micturition Control Detected by fMRI in Rats
- Galvanic vestibular stimulator for fMRI studies
- Dinâmica da alteração perfusional induzida por estado de apnéia utilizando fMRI
- Em busca da região epileptiforme em pacientes com epilepsia do lobo temporal: métodos alternativos baseados em fMRI e EEG-fMRI