Deblurring and noise suppression in spatial EPR imaging

Abstract

Electron paramagnetic resonance (EPR) imaging has been used to map in vivo spatial distributions of endogenous and introduced free radicals. Because of the appreciable spectral linewidths of the radicals and the finite magnitude of the magnetic field gradients that encode spatial information, it is necessary to perform deblurring and noise suppression to achieve images with high spatial resolution. Recently, a regularized inverse-filtering technique for suppressing noise and blurring was described and evaluated for use with 3D single photon emission computed tomography. This filtering technique uses an a priori random image field (RIF) to specify the expected signal region and degree of smoothness in the image.