Adaptive Fourier threshold filtering: a method to reduce noise and incoherent artifacts in high resolution cardiac images.
We introduce an image processing method which reduces white noise and random artifacts in sets of high resolution, time resolved images. At each pixel, the processing consists of: 1) the isolation of a time intensity curve (TIC), 2) Fourier transformation of each TIC, 3) application of a threshold to remove low intensity coefficients, 4) inverse transformation to generate noise reduced TICs which are recombined to form images with improved signal-to-noise ratio (SNR). Noise filtering by Fourier thresholding is demonstrated on a set of cardiac images, resulting in a reduction of the noise energy by approximately 90%.
Doyle
M
M
Department of Medicine, University of Alabama at Birmingham 35294.
Chapman
B L
BL
Blackwell
G
G
Walsh
E G
EG
Pohost
G M
GM
D016477:Artifacts; D001783:Blood Flow Velocity / Q000502:physiology; D005583:Fourier Analysis; D006321:Heart / Q000033:anatomy & histology*; D006331:Heart Diseases / Q000175:diagnosis*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008944:Mitral Valve Insufficiency / Q000175:diagnosis / Q000503:physiopathology; D008962:Models, Theoretical; D012039:Regional Blood Flow / Q000502:physiology