Meeting Banner
Abstract #1315

Fractal Analysis of Real-Time BOLD Data from Healthy Kidneys

Marla Shaver1, Michael Noseworthy2

1School of Biomedical Engineering, McMaster University, Hamilton, Ontario, Canada; 2School of Biomedical Engineering, Electrical and Computer Engineering, McMaster University, Hamilton, Ontario, Canada

In this study, real-time BOLD data from healthy kidneys was analyzed to determine whether signal variations are fractal, and if so whether they can be characterized as fractional Gaussian noise (fGn) or fractional Brownian motion (fBm). Images were acquired using a T2* weighted GRE EPI sequence. Subjects were instructed to breath quietly during image acquisition. Rapidly acquired BOLD data from both kidney cortex and medulla behave fractally, where the majority of the data is characterized as fGn.

Abstract PDF

Keywords

acquisition allow analyzed approved array artifacts assessment axis behave beneficial biomedical board bold breath breathe breathing calculation carcinoma challenge channel characterized coefficient coefficients coil collection comp computer coronal cortex determine developed deviation differ differentiating dimension disease diseased done elderly electrical engineering ethics excluded explore exported feasible fewer fiesta fractal fractional greatly healthy holding house instructed kidney kidneys longitudinal majority maps matching materials matrix medulla minutes motion multiphase noise normally novel oblique organization prescribed previously processed processes quiet rapidly real rectal reduce related renal represent respectively scanning school select selected shaver skip slices subject subjects table template temporal thick torso useful variations whether