Title :
An adaptive nonparametric approach to restoration and interpolation for medical imaging
Author :
Takeda, Hiroyuki ; Mil, Peyman
Author_Institution :
Univ. of California, Santa Cruz, CA, USA
fDate :
June 28 2009-July 1 2009
Abstract :
We present the application of a novel nonparametric approach to restoration and interpolation of medical images. The proposed approach is based on the notion of spatially adaptive filtering where locally computed filters adjust to the underlying estimated geometry of the signal of interest. In particular, the approach allows for high performance denoising, restoration and interpolation of images from a variety of modalities using the same mathematical and computational framework.
Keywords :
adaptive filters; image denoising; image restoration; interpolation; medical image processing; regression analysis; adaptive nonparametric approach; computational framework; image denoising; image restoration; locally computed filters; mathematical framework; medical imaging interpolation; nonparametric approach; spatially adaptive filtering; Adaptive filters; Biomedical imaging; Image reconstruction; Image restoration; Interpolation; Kernel; Noise reduction; Parameter estimation; Signal processing; Signal restoration; Kernel regression; denoising; interpolation; tomography;
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-3931-7
Electronic_ISBN :
1945-7928
DOI :
10.1109/ISBI.2009.5193135
