Part of #Estimating the Statistical Distribution of Parameters for Activated Brain in functional PET Images# :
Publishing year : 2006
Conference : 13th Iranian Conference on Medical Engineering
Number of pages : 7
Abstract: In many biomedical applications, randomization (or resampling) methods allow us to estimate the probability density function (pdf) of parameters under null hypothesis (H) using a limited number of measurements. Null hypothesis stands for conditions where there is no effect of interest in measurements (pure noise and disturbances), and H0 is alternative hypothesis (reverse status). In this paper, a new procedure is developed for evaluating the pdf under H1, when boostrap is only applicable under H01. The total pdf of the parameter under study is first estimated from real world measurements. Then the pdf under H is estimated using a surrogate data which is generated by bootstrap. Making use of these pdfs and total probability law, we derive an estimate of pdf under H10. As the proposed method is applicable to many signal processing and biomedical applications, we demonstrated its validity using simulated data. The collection of PET functional images, which are processed for the localization of brain activity areas. The pdf of the & quot; activation height & quot; under H is estimated using the proposed method. The resulting pdf estimation is consistent with the map of activation regions.