Wavelet-MDL based detrending method for near infrared spectroscopy (NIRS)

Kwang Eun Jang; Sungho Tak; Jaeduck Jang; Jinwook Jung; Jong Chul Ye

doi:10.1117/12.764141

7 March 2008 Wavelet-MDL based detrending method for near infrared spectroscopy (NIRS)

Kwang Eun Jang, Sungho Tak, Jaeduck Jang, Jinwook Jung, Jong Chul Ye

Proceedings Volume 6850, Multimodal Biomedical Imaging III; 68500Y (2008) https://doi.org/10.1117/12.764141
Event: SPIE BiOS, 2008, San Jose, California, United States

Abstract

Near infrared spectroscopy (NIRS) is a relatively new non-invasive brain imaging method to measure brain activities associated with regional changes of the oxy- and deoxy- hemoglobin concentration. Typically, functional MRI or PET data are analyzed using the general linear model (GLM), in which measurements are modeled as a linear combination of explanatory variables plus an error term. However, the GLM often fails in NIRS if there exists an unknown global trend due to breathing, cardiac, vaso- motion and other experimental errors. In order to overcome these problems, we propose a wavelet-MDL based detrending algorithm. Specifically, the wavelet transform is applied to NIRS measurements to decompose them into global trends, signals and uncorrelated noise components in distinct scales. In order to prevent the over-fitting the minimum length description (MDL) principle is applied. Experimental results demonstrate that the new detrending algorithm outperforms the conventional approaches.

Citation Download Citation

Kwang Eun Jang, Sungho Tak, Jaeduck Jang, Jinwook Jung, and Jong Chul Ye "Wavelet-MDL based detrending method for near infrared spectroscopy (NIRS)", Proc. SPIE 6850, Multimodal Biomedical Imaging III, 68500Y (7 March 2008); https://doi.org/10.1117/12.764141

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