Serrai Hacene, Senhadji Lotfi, Wang Guoyu, Akoka Serge, Stroman Patrick
Institute for Biodiagnostics, National Research Council of Canada, Winnipeg, Canada.
Magn Reson Med. 2003 Sep;50(3):623-6. doi: 10.1002/mrm.10544.
A new postprocessing filter based on the continuous wavelet transform (CWT) method modeled as a biexponential decay function to isolate the lactate doublet from overlapping lipid resonance(s) and estimate its magnetic resonance spectroscopy (MRS) parameters (signal amplitude, resonance frequencies, and apparent relaxation time (T(*) (2))) is proposed. The new filter employs the same iterative process used in the previously single exponential decay filter. A comparison of the results obtained from application of both filters to simulated data and real (1)H MRS data collected from human blood plasma and brain tumors demonstrates that the new filter provides a better estimate of MRS parameters of lactate, with less computation time. Furthermore, the results show that the new filter is less sensitive to noise and provides a direct estimate of J-coupling value of the lactate doublet.
提出了一种基于连续小波变换(CWT)方法的新型后处理滤波器,该方法被建模为双指数衰减函数,用于从重叠的脂质共振中分离乳酸双峰,并估计其磁共振波谱(MRS)参数(信号幅度、共振频率和表观弛豫时间(T(*)(2)))。新滤波器采用了与先前单指数衰减滤波器相同的迭代过程。将这两种滤波器应用于模拟数据以及从人血浆和脑肿瘤收集的真实(1)H MRS数据所获得的结果比较表明,新滤波器能够以更少的计算时间更好地估计乳酸的MRS参数。此外,结果表明新滤波器对噪声不太敏感,并能直接估计乳酸双峰的J耦合值。