Paper Info
Title
An adaptive nonparametric approach to restoration and interpolation for medical imaging
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.
Year
DOI
Venue
2009
10.1109/ISBI.2009.5193135
Boston, MA
Keywords
Field
DocType
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,Kernel regression,denoising,interpolation,tomography
Kernel (linear algebra),Computer vision,Pattern recognition,Medical imaging,Computer science,Interpolation,Nonparametric statistics,Pixel,Adaptive filter,Artificial intelligence,Image restoration,Bilinear interpolation
Conference
ISSN
ISBN
Citations 
1945-7928 E-ISBN : 978-1-4244-3932-4
978-1-4244-3932-4
0
PageRank 
References 
Authors
0.34
6
2
Name
Order
Citations
PageRank
Hiroyuki Takeda12268.63
Peyman Milanfar23284155.61