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

fYear

2009

fDate

June 28 2009-July 1 2009

Firstpage

666

Lastpage

669

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on

Conference_Location

Boston, MA

ISSN

1945-7928

Print_ISBN

978-1-4244-3931-7

Electronic_ISBN

1945-7928

Type

conf

DOI

10.1109/ISBI.2009.5193135

Filename

5193135