Referenced Items are not available for this document.
A magnetic resonance image (MRI) may contain truncation artifacts if there are not enough high-frequency data when the conventional Fourier transform method is used for reconstruction. A method for reducing the artifacts using a multilayer neural network is presented. The network consists of one linear output layer and at least one nonlinear hidden layer. The missing high-frequency components are predicted based on known low-frequency components and are used to reduce the truncation artifacts of the image. Results from a series of simulation experiments are discussed
Published in:
Medical Imaging, IEEE Transactions on
(Volume:12
,
Issue:
1
)
Date of Publication: Mar 1993
- Page(s):
- 73 - 77
- ISSN :
- 0278-0062
- INSPEC Accession Number:
- 4479513
- Digital Object Identifier :
- 10.1109/42.222669
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 06 August 2002
- Issue Date :
- Mar 1993
- Sponsored by :
- IEEE Engineering in Medicine and Biology Society
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