Al-Baddai, Saad and Al-Subari, Karema and Tome, Ana Maria and Ludwig, Bernd and Salas-Gonzales, Diego and Lang, Elmar Wolfgang (2016) Analysis of fMRI images with bi-dimensional empirical mode decomposition based-on Green's functions. BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 30. pp. 53-63. ISSN 1746-8094, 1746-8108
Full text not available from this repository. (Request a copy)Abstract
We present a new method for decomposing two-dimensional data arrays with empirical mode decomposition (EMD). It performs envelope surface interpolation based on Green's functions in tension (GiT) to extract bi-dimensional intrinsic mode functions (BIMFs). The new method is called GiT-BEMD and outperforms existing bi-dimensional ensemble EMD (BEEMD) variants in terms of computational costs and quality of extracted intrinsic modes. More specifically, it is easy to implement, much faster than BEEMD, very robust and free from processing artifacts. GiT-BEMD is applied to fMRI data recorded during a contour integration task. Features extracted from resulting volume intrinsic mode functions (VIMFs) achieve higher classification accuracy compared to the canonical BEEMD. The new method thus provides a valuable alternative to existing mode decomposition methods for analyzing images. (C) 2016 Elsevier Ltd. All rights reserved.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | BIDIMENSIONAL EMD; Empirical mode decomposition; Green's function; FMRI; SVM; VIMFs |
| Subjects: | 000 Computer science, information & general works > 020 Library & information sciences 500 Science > 570 Life sciences |
| Divisions: | Languages and Literatures > Institut für Information und Medien, Sprache und Kultur (I:IMSK) > Lehrstuhl für Informationswissenschaft Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 04 Apr 2019 13:35 |
| Last Modified: | 04 Apr 2019 13:35 |
| URI: | https://pred.uni-regensburg.de/id/eprint/3439 |
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