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Adaptive multiresolution non-local means filter for 3D magnetic resonance image denoising

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Adaptive multiresolution non-local means filter for 3D magnetic resonance image denoising

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Nombre: PIERRICK COUPÉ;M ...
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dc.contributor.author Coupé ., Pierrick es_ES
dc.contributor.author Manjón Herrera, José Vicente es_ES
dc.contributor.author Robles Viejo, Monserrat es_ES
dc.contributor.author Collins ., Louis es_ES
dc.date.accessioned 2014-02-27T11:11:34Z
dc.date.issued 2012-07
dc.identifier.issn 1751-9659
dc.identifier.uri http://hdl.handle.net/10251/36006
dc.description.abstract In this study, an adaptive multiresolution version of the blockwise non-local (NL)-means filter is presented for three-dimensional (3D) magnetic resonance (MR) images. On the basis of an adaptive soft wavelet coefficient mixing, the proposed filter implicitly adapts the amount of denoising according to the spatial and frequency information contained in the image. Two versions of the filter are described for Gaussian and Rician noise. Quantitative validation was carried out on BrainWeb datasets by using several quality metrics. The results show that the proposed multiresolution filter obtained competitive performance compared with recently proposed Rician NL-means filters. Finally, qualitative experiments on anatomical and diffusion-weighted MR images show that the proposed filter efficiently removes noise while preserving fine structures in classical and very noisy cases. The impact of the proposed denoising method on fibre tracking is also presented on a HARDI dataset. es_ES
dc.description.sponsorship The authors thank Ilana Leppert and Professor Bruce Pike for providing DW-MRI data and help in result analysis. They also thank Nicolas Guizard and Dr Vladimir Fonov for their help during tractography experiment. They thank Dr Luis Concha for his fruitful discussions about DTI processing. This work has been partially supported by the Canadian grant industry Cda (CECR)-Gevas-OE016 and by the Spanish Health Institute Carlos III through the RETICS Combiomed, RD07/0067/2001. en_EN
dc.format.extent 11 es_ES
dc.language Inglés es_ES
dc.publisher Institution of Engineering and Technology (IET) es_ES
dc.relation.ispartof IET Image Processing es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Gaussian noise es_ES
dc.subject Adaptative filters es_ES
dc.subject Image denoising es_ES
dc.subject Image resolution es_ES
dc.subject Magnetic resonance imaging es_ES
dc.subject Medical image processing es_ES
dc.subject Wavelet transforms es_ES
dc.subject.classification FISICA APLICADA es_ES
dc.title Adaptive multiresolution non-local means filter for 3D magnetic resonance image denoising es_ES
dc.type Artículo es_ES
dc.embargo.lift 10000-01-01
dc.embargo.terms forever es_ES
dc.identifier.doi 10.1049/iet-ipr.2011.0161
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//RD07%2F0067%2F2001/ES/RED TEMÁTICA DE INVESTIGACIÓN COOPERATIVA EN BIOMEDICINA COMPUTACIONAL/ / es_ES
dc.relation.projectID info:eu-repo/grantAgreement/CIHR//Gevas-OE016/CA es_ES
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Física Aplicada - Departament de Física Aplicada es_ES
dc.description.bibliographicCitation Coupé ., P.; Manjón Herrera, JV.; Robles Viejo, M.; Collins ., L. (2012). Adaptive multiresolution non-local means filter for 3D magnetic resonance image denoising. IET Image Processing. 6(5):558-568. doi:10.1049/iet-ipr.2011.0161 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1049/iet-ipr.2011.0161 es_ES
dc.description.upvformatpinicio 558 es_ES
dc.description.upvformatpfin 568 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 6 es_ES
dc.description.issue 5 es_ES
dc.relation.senia 237107
dc.identifier.eissn 1751-9667
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES
dc.contributor.funder Canadian Institutes of Health Research
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