DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kwon, Kinam | ko |
dc.contributor.author | Kim, Dongchan | ko |
dc.contributor.author | Park, Hyun Wook | ko |
dc.date.accessioned | 2016-07-04T03:13:11Z | - |
dc.date.available | 2016-07-04T03:13:11Z | - |
dc.date.created | 2016-05-10 | - |
dc.date.created | 2016-05-10 | - |
dc.date.issued | 2016-03 | - |
dc.identifier.citation | INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, v.26, no.1, pp.65 - 75 | - |
dc.identifier.issn | 0899-9457 | - |
dc.identifier.uri | http://hdl.handle.net/10203/209041 | - |
dc.description.abstract | For clinical diagnosis in MRI, multiple examinations are commonly performed to acquire various contrast images. This article presents a learning-based denoising method for parallel imaging to enhance the quality of multi-contrast images so that the imaging time can be accelerated highly. Multi-contrast images share structural information and coil geometry. The proposed method adopts the multilayer perceptron (MLP) model to save the sharable and redundant information among the multi-contrast images. The images are divided into patches, which are used as the input and output of MLP. A geometry factor map is additionally used to provide noise amplification information of the accelerated MR images. Computer simulation demonstrates that the use of multi-contrast images and geometry factor contributes to the quality of the reconstructed images. The proposed method reconstructs high-quality images without impairing details from the subsampled intermediate images, and it shows better results than previous denoising methods | - |
dc.language | English | - |
dc.publisher | WILEY-BLACKWELL | - |
dc.subject | NEURAL-NETWORKS | - |
dc.subject | RECONSTRUCTION | - |
dc.subject | GRAPPA | - |
dc.title | Multi-contrast MR image denoising for parallel imaging using multilayer perceptron | - |
dc.type | Article | - |
dc.identifier.wosid | 000374013300008 | - |
dc.identifier.scopusid | 2-s2.0-84962791729 | - |
dc.type.rims | ART | - |
dc.citation.volume | 26 | - |
dc.citation.issue | 1 | - |
dc.citation.beginningpage | 65 | - |
dc.citation.endingpage | 75 | - |
dc.citation.publicationname | INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY | - |
dc.identifier.doi | 10.1002/ima.22158 | - |
dc.contributor.localauthor | Park, Hyun Wook | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | denoising | - |
dc.subject.keywordAuthor | geometry factor | - |
dc.subject.keywordAuthor | multi-contrast | - |
dc.subject.keywordAuthor | multilayer perceptron | - |
dc.subject.keywordAuthor | parallel imaging | - |
dc.subject.keywordPlus | NEURAL-NETWORKS | - |
dc.subject.keywordPlus | RECONSTRUCTION | - |
dc.subject.keywordPlus | GRAPPA | - |
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