Advanced pre-processing algorithms for optical imaging systems in biological applications = 생물학적 응용을 위한 광학 시스템 신호의 고급 전처리 알고리즘

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In practice, every measured signal is a distorted version of unknown true signal. The pre-processing step for correcting various distortions is the starting point for further signal analysis. The first part of this article concerns an advanced method for removing the inherent bias in the functional near infrared spectroscopy (NIRS). The NIRS is capable of investigating brain activities associated with the regional changes of the oxy- and deoxy- hemoglobin concentration by measuring the absorption of the near infrared light through the intact skull. Recently, the general linear model (GLM), which is a standard method for functional MRI (fMRI) analysis, has been employed for quantitative analysis of NIRS data. However, the GLM often fails in NIRS when there exists an unknown global trend due to breathing, cardiac, vaso- motion and other experimental errors. To remedy this problem, we propose a wavelet minimum description length (Wavelet-MDL) detrending algorithm to overcome this problem. Specifically, the wavelet transform is applied to decompose NIRS measurements into global trends, hemodynamic signals and uncorrelated noise components at distinct scales. Then, the minimum length description (MDL) principle plays an important role in preventing the over- or under-fitting and facilitates the optimal model order selection for the global trend estimate. The remain part of this paper is devoted to single channel blind deconvolution algorithms for a brightfield microscopy that has radially symmetric point-spread function (PSF). The multichannel blind image deconvolution theory tells us that exact recovery of unknown blur kernels is possible from multiple measurements of an identical scene through distinct blur channels. However, there often exist obstacles in obtaining multiple distinct blur measurements in many biological applications, since the image content may vary for various reasons, including specimen drift between snapshots, specimen damage due to prolonged e...
Ye, Jong-Chulresearcher예종철researcher
한국과학기술원 : 바이오및뇌공학과,
Issue Date
308639/325007  / 020073477

학위논문(석사) - 한국과학기술원 : 바이오및뇌공학과, 2009.2, [ viii, 58 p. ]


NIRS; Blind deconvolution; Single channel; MDL; Universal prior; 근적외선분광기; 블라인드 복원법; 단일 채널; 디트렌딩; 웨이블렛; NIRS; Blind deconvolution; Single channel; MDL; Universal prior; 근적외선분광기; 블라인드 복원법; 단일 채널; 디트렌딩; 웨이블렛

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