Improving the performance of the prony method using a wavelet domain filter for MRI denoising.
The Prony methods are used for exponential fitting. We use a variant of the Prony method for abnormal brain tissue detection in sequences of T 2 weighted magnetic resonance images. Here, MR images are considered to be affected only by Rician noise, and a new wavelet domain bilateral filtering process is implemented to reduce the noise in the images. This filter is a modification of Kazubek's algorithm and we use synthetic images to show the ability of the new procedure to suppress noise and compare its performance with respect to the original filter, using quantitative and qualitative criteria. The tissue classification process is illustrated using a real sequence of T 2 MR images, and the filter is applied to each image before using the variant of the Prony method.
Escuela de Matemáticas, Facultad de Ciencias, Universidad Nacional de Colombia, Medellín, Colombia.
Rodney
0000-0002-7284-6481
R
Jaramillo
Escuela de Matemáticas, Facultad de Ciencias, Universidad Nacional de Colombia, Medellín, Colombia.
Marianela
M
Lentini
Escuela de Matemáticas, Facultad de Ciencias, Universidad Nacional de Colombia, Medellín, Colombia.
Marco
M
Paluszny
D000465:Algorithms; D001921:Brain / Q000473:pathology*; D003198:Computer Simulation; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008962:Models, Theoretical; D011336:Probability; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio; D012984:Software