Title :
Analysis of fMRI Data by Mathematical Morphology
Author :
Kang Yun ; Ye De-Rong
Author_Institution :
Sch. of Biomed. Eng., Capital Med. Univ., Beijing, China
Abstract :
Based on investigation of the characteristic of fMRI signals in block design, we present a mathematical morphology method for fMRI analysis. With both simulated data and real fMRI data, the results of our experiments show that the proposed method can approximately detect the activations without requiring any statistical model assumption. The proposed method is fairly easy to be implemented. It also can be used for improving the accuracy of clustering methods, and reducing the computational cost.
Keywords :
biomedical MRI; data analysis; mathematical morphology; medical image processing; pattern clustering; statistical analysis; clustering methods; fMRI data analysis; fMRI signal; functional magnetic resonance imaging; mathematical morphology method; statistical model assumption; Biomedical engineering; Clustering methods; Computational efficiency; Data analysis; Frequency; Hemodynamics; Low-frequency noise; Morphology; Signal analysis; Signal design;
Conference_Titel :
Biomedical Engineering and Computer Science (ICBECS), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5315-3
DOI :
10.1109/ICBECS.2010.5462351