Al-Baddai, S. and Neubauer, A. and Tome, A. M. and Vigneron, V. and Salas-Gonzalez, D. and Gorriz, J. M. and Puntonet, C. G. and Lang, E. W. (2016) Functional Biomedical Images of Alzheimer's Disease. A Green's Function-based Empirical Mode Decomposition Study. CURRENT ALZHEIMER RESEARCH, 13 (6). pp. 695-707. ISSN 1567-2050, 1875-5828
Full text not available from this repository. (Request a copy)Abstract
Positron emission tomography (PET) provides a functional imaging modality to detect signs of dementias in human brains. Two-dimensional empirical mode decomposition (2D-EMD) provides means to analyze such images. It decomposes the latter into characteristic modes which represent textures on different spatial scales. These textures provide informative features for subsequent classification purposes. The study proposes a new EMD variant which relies on a Green's function based estimation method including a tension parameter to fast and reliably estimate the envelope hypersurfaces interpolating extremal points of the two-dimensional intensity distrubution of the images. The new method represents a fast and stable bi-dimensional EMD which speeds up computations roughly 100-fold. In combination with proper classifiers these exploratory feature extraction techniques can form a computer aided diagnosis (CAD) system to assist clinicians in identifying various diseases from functional images alone. PET images of subjects suffering from Alzheimer's disease are taken to illustrate this ability.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | BIDIMENSIONAL EMD; INTERPOLATION; Alzheimer's disease; empirical mode decomosition; Green's function; SVM; RF |
| Subjects: | 500 Science > 570 Life sciences |
| Divisions: | Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 15 Mar 2019 09:13 |
| Last Modified: | 15 Mar 2019 09:13 |
| URI: | https://pred.uni-regensburg.de/id/eprint/2719 |
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