Journal article Open Access

Implementation of Iterative bilateral filtering for removal of Rician noise in MR images using FPGA

Durga Pathrikar; V. N. Jirafe


DCAT Export

<?xml version='1.0' encoding='utf-8'?>
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:adms="http://www.w3.org/ns/adms#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dct="http://purl.org/dc/terms/" xmlns:dctype="http://purl.org/dc/dcmitype/" xmlns:dcat="http://www.w3.org/ns/dcat#" xmlns:duv="http://www.w3.org/ns/duv#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:frapo="http://purl.org/cerif/frapo/" xmlns:geo="http://www.w3.org/2003/01/geo/wgs84_pos#" xmlns:gsp="http://www.opengis.net/ont/geosparql#" xmlns:locn="http://www.w3.org/ns/locn#" xmlns:org="http://www.w3.org/ns/org#" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:prov="http://www.w3.org/ns/prov#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns:schema="http://schema.org/" xmlns:skos="http://www.w3.org/2004/02/skos/core#" xmlns:vcard="http://www.w3.org/2006/vcard/ns#" xmlns:wdrs="http://www.w3.org/2007/05/powder-s#">
  <rdf:Description rdf:about="https://zenodo.org/record/5843028">
    <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#anyURI">https://zenodo.org/record/5843028</dct:identifier>
    <foaf:page rdf:resource="https://zenodo.org/record/5843028"/>
    <dct:creator>
      <rdf:Description>
        <rdf:type rdf:resource="http://xmlns.com/foaf/0.1/Agent"/>
        <foaf:name>Durga Pathrikar</foaf:name>
        <org:memberOf>
          <foaf:Organization>
            <foaf:name>Department of Electronics and Telecommunication, PES's Modern College of Engineering, Pune, India.</foaf:name>
          </foaf:Organization>
        </org:memberOf>
      </rdf:Description>
    </dct:creator>
    <dct:creator>
      <rdf:Description>
        <rdf:type rdf:resource="http://xmlns.com/foaf/0.1/Agent"/>
        <foaf:name>V. N. Jirafe</foaf:name>
        <org:memberOf>
          <foaf:Organization>
            <foaf:name>Professor, Department of Electronics and Telecommunication, PES's Modern College of Engineering, Pune, India.</foaf:name>
          </foaf:Organization>
        </org:memberOf>
      </rdf:Description>
    </dct:creator>
    <dct:title>Implementation of Iterative bilateral filtering for removal of Rician noise in MR images using FPGA</dct:title>
    <dct:publisher>
      <foaf:Agent>
        <foaf:name>Zenodo</foaf:name>
      </foaf:Agent>
    </dct:publisher>
    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#gYear">2020</dct:issued>
    <dcat:keyword>Iterative Bilateral Filtering, MRI, Rician Noise, FPGA</dcat:keyword>
    <dct:subject>
      <skos:Concept>
        <skos:prefLabel>2277-3878</skos:prefLabel>
        <skos:inScheme>
          <skos:ConceptScheme>
            <dct:title>issn</dct:title>
          </skos:ConceptScheme>
        </skos:inScheme>
      </skos:Concept>
    </dct:subject>
    <dct:subject>
      <skos:Concept>
        <skos:prefLabel>10.35940/ijrte.C4351.099320</skos:prefLabel>
        <skos:inScheme>
          <skos:ConceptScheme>
            <dct:title>doi</dct:title>
          </skos:ConceptScheme>
        </skos:inScheme>
      </skos:Concept>
    </dct:subject>
    <schema:sponsor>
      <rdf:Description>
        <rdf:type rdf:resource="http://xmlns.com/foaf/0.1/Agent"/>
        <foaf:name>Blue Eyes Intelligence Engineering and Sciences Publication(BEIESP)</foaf:name>
        <org:memberOf>
          <foaf:Organization>
            <foaf:name>Publisher</foaf:name>
          </foaf:Organization>
        </org:memberOf>
      </rdf:Description>
    </schema:sponsor>
    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#date">2020-09-30</dct:issued>
    <dct:language rdf:resource="http://publications.europa.eu/resource/authority/language/ENG"/>
    <owl:sameAs rdf:resource="https://zenodo.org/record/5843028"/>
    <adms:identifier>
      <adms:Identifier>
        <skos:notation rdf:datatype="http://www.w3.org/2001/XMLSchema#anyURI">https://zenodo.org/record/5843028</skos:notation>
        <adms:schemeAgency>url</adms:schemeAgency>
      </adms:Identifier>
    </adms:identifier>
    <dct:relation rdf:resource="http://issn.org/resource/ISSN/2277-3878"/>
    <owl:sameAs rdf:resource="https://doi.org/10.35940/ijrte.C4351.099320"/>
    <dct:description>&lt;p&gt;Magnetic resonance image noise reduction is important to process further and visual analysis. Bilateral filter is denoises image and also preserves edge. It proposes Iterative bilateral filter which reduces Rician noise in the magnitude magnetic resonance images and retains the fine structures, edges and it also reduces the bias caused by Rician noise. The visual and diagnostic quality of the image is retained. The quantitative analysis is based on analysis of standard quality metrics parameters like peak signal-to-noise ratio and mean structural similarity index matrix reveals that these methods yields better results than the other proposed denoising methods for MRI. Problem associated with the method is that it is computationally complex hence time consuming. It is not recommended for real time applications. To use in real time application a parallel implantation of the same using FPGA is proposed.&lt;/p&gt;</dct:description>
    <dct:accessRights rdf:resource="http://publications.europa.eu/resource/authority/access-right/PUBLIC"/>
    <dct:accessRights>
      <dct:RightsStatement rdf:about="info:eu-repo/semantics/openAccess">
        <rdfs:label>Open Access</rdfs:label>
      </dct:RightsStatement>
    </dct:accessRights>
    <dct:license rdf:resource="https://creativecommons.org/licenses/by/4.0/legalcode"/>
    <dcat:distribution>
      <dcat:Distribution>
        <dcat:accessURL rdf:resource="https://doi.org/10.35940/ijrte.C4351.099320"/>
        <dcat:byteSize>727063</dcat:byteSize>
        <dcat:downloadURL rdf:resource="https://zenodo.org/record/5843028/files/C4351099320.pdf"/>
        <dcat:mediaType>application/pdf</dcat:mediaType>
      </dcat:Distribution>
    </dcat:distribution>
  </rdf:Description>
</rdf:RDF>
40
15
views
downloads
Views 40
Downloads 15
Data volume 10.9 MB
Unique views 31
Unique downloads 15

Share

Cite as