Highly accelerated intracranial 4D flow MRI: evaluation of healthy volunteers and patients with intracranial aneurysms View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-04

AUTHORS

Jing Liu, Louise Koskas, Farshid Faraji, Evan Kao, Yan Wang, Henrik Haraldsson, Sarah Kefayati, Chengcheng Zhu, Sinyeob Ahn, Gerhard Laub, David Saloner

ABSTRACT

OBJECTIVES: To evaluate an accelerated 4D flow MRI method that provides high temporal resolution in a clinically feasible acquisition time for intracranial velocity imaging. MATERIALS AND METHODS: Accelerated 4D flow MRI was developed by using a pseudo-random variable-density Cartesian undersampling strategy (CIRCUS) with the combination of k-t, parallel imaging and compressed sensing image reconstruction techniques (k-t SPARSE-SENSE). Four-dimensional flow data were acquired on five healthy volunteers and eight patients with intracranial aneurysms using CIRCUS (acceleration factor of R = 4, termed CIRCUS4) and GRAPPA (R = 2, termed GRAPPA2) as the reference method. Images with three times higher temporal resolution (R = 12, CIRCUS12) were also reconstructed from the same acquisition as CIRCUS4. Qualitative and quantitative image assessment was performed on the images acquired with different methods, and complex flow patterns in the aneurysms were identified and compared. RESULTS: Four-dimensional flow MRI with CIRCUS was achieved in 5 min and allowed further improved temporal resolution of <30 ms. Volunteer studies showed similar qualitative and quantitative evaluation obtained with the proposed approach compared to the reference (overall image scores: GRAPPA2 3.2 ± 0.6; CIRCUS4 3.1 ± 0.7; CIRCUS12 3.3 ± 0.4; difference of the peak velocities: -3.83 ± 7.72 cm/s between CIRCUS4 and GRAPPA2, -1.72 ± 8.41 cm/s between CIRCUS12 and GRAPPA2). In patients with intracranial aneurysms, the higher temporal resolution improved capturing of the flow features in intracranial aneurysms (pathline visualization scores: GRAPPA2 2.2 ± 0.2; CIRCUS4 2.5 ± 0.5; CIRCUS12 2.7 ± 0.6). CONCLUSION: The proposed rapid 4D flow MRI with a high temporal resolution is a promising tool for evaluating intracranial aneurysms in a clinically feasible acquisition time. More... »

PAGES

295-307

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10334-017-0646-8

DOI

http://dx.doi.org/10.1007/s10334-017-0646-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1091080342

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/28785850


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Adult", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Blood Flow Velocity", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Female", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Healthy Volunteers", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Image Enhancement", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Image Processing, Computer-Assisted", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Imaging, Three-Dimensional", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Intracranial Aneurysm", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Magnetic Resonance Angiography", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Magnetic Resonance Imaging", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Male", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Reproducibility of Results", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "University of California, San Francisco", 
          "id": "https://www.grid.ac/institutes/grid.266102.1", 
          "name": [
            "Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry St, Suite 350, 94107, San Francisco, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Liu", 
        "givenName": "Jing", 
        "id": "sg:person.01234554053.02", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01234554053.02"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of California, San Francisco", 
          "id": "https://www.grid.ac/institutes/grid.266102.1", 
          "name": [
            "Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry St, Suite 350, 94107, San Francisco, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Koskas", 
        "givenName": "Louise", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of California, San Francisco", 
          "id": "https://www.grid.ac/institutes/grid.266102.1", 
          "name": [
            "Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry St, Suite 350, 94107, San Francisco, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Faraji", 
        "givenName": "Farshid", 
        "id": "sg:person.0757124227.36", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0757124227.36"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of California, San Francisco", 
          "id": "https://www.grid.ac/institutes/grid.266102.1", 
          "name": [
            "Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry St, Suite 350, 94107, San Francisco, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kao", 
        "givenName": "Evan", 
        "id": "sg:person.012270714461.46", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012270714461.46"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of California, San Francisco", 
          "id": "https://www.grid.ac/institutes/grid.266102.1", 
          "name": [
            "Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry St, Suite 350, 94107, San Francisco, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wang", 
        "givenName": "Yan", 
        "id": "sg:person.01017622760.06", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01017622760.06"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of California, San Francisco", 
          "id": "https://www.grid.ac/institutes/grid.266102.1", 
          "name": [
            "Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry St, Suite 350, 94107, San Francisco, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Haraldsson", 
        "givenName": "Henrik", 
        "id": "sg:person.01215037004.85", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01215037004.85"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of California, San Francisco", 
          "id": "https://www.grid.ac/institutes/grid.266102.1", 
          "name": [
            "Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry St, Suite 350, 94107, San Francisco, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kefayati", 
        "givenName": "Sarah", 
        "id": "sg:person.01222326531.10", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01222326531.10"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of California, San Francisco", 
          "id": "https://www.grid.ac/institutes/grid.266102.1", 
          "name": [
            "Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry St, Suite 350, 94107, San Francisco, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhu", 
        "givenName": "Chengcheng", 
        "id": "sg:person.0636457767.19", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0636457767.19"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Siemens Healthcare (United States)", 
          "id": "https://www.grid.ac/institutes/grid.415886.6", 
          "name": [
            "Siemens Healthcare, California, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ahn", 
        "givenName": "Sinyeob", 
        "id": "sg:person.0717014647.17", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0717014647.17"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Siemens Healthcare (United States)", 
          "id": "https://www.grid.ac/institutes/grid.415886.6", 
          "name": [
            "Siemens Healthcare, California, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Laub", 
        "givenName": "Gerhard", 
        "id": "sg:person.0603101342.45", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0603101342.45"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "San Francisco VA Medical Center", 
          "id": "https://www.grid.ac/institutes/grid.410372.3", 
          "name": [
            "Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry St, Suite 350, 94107, San Francisco, CA, USA", 
            "Radiology Service, VA Medical Center, San Francisco, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Saloner", 
        "givenName": "David", 
        "id": "sg:person.01036206317.54", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01036206317.54"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1148/radiol.10091218", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000162385"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1148/radiol.14140973", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001401424"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.mri.2013.05.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003063093"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.25317", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003461669"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1148/radiol.12120055", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004343416"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.22463", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004356511"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.22463", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004356511"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.23297", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004424496"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3174/ajnr.a1138", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007292486"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.21861", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007653740"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/(sici)1522-2594(200004)43:4<503::aid-mrm3>3.0.co;2-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010710698"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00234-009-0635-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011130292", 
          "https://doi.org/10.1007/s00234-009-0635-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00234-009-0635-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011130292", 
          "https://doi.org/10.1007/s00234-009-0635-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00234-009-0635-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011130292", 
          "https://doi.org/10.1007/s00234-009-0635-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.10171", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012449961"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.21763", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013588487"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jmri.20494", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014955319"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jmri.20494", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014955319"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.22199", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016013763"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.22199", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016013763"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ejrad.2009.06.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017132316"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/7529.8927", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017643740"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.24925", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018512831"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.20730", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021030211"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.20730", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021030211"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.mri.2009.05.042", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021141340"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3174/ajnr.a3537", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022374636"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00330-014-3587-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023454576", 
          "https://doi.org/10.1007/s00330-014-3587-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00330-014-3587-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023454576", 
          "https://doi.org/10.1007/s00330-014-3587-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2463/mrms.2013-0008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025365323"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.24440", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026807801"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s12968-015-0174-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027175700", 
          "https://doi.org/10.1186/s12968-015-0174-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s12968-015-0174-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027175700", 
          "https://doi.org/10.1186/s12968-015-0174-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.22875", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027836464"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/strokeaha.108.521617", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028198220"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/strokeaha.108.521617", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028198220"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1532-429x-13-55", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028621413", 
          "https://doi.org/10.1186/1532-429x-13-55"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.24390", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029763149"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jmr.2010.01.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030625609"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jmri.23501", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031749574"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.24514", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035041541"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.21391", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037838340"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jmri.23778", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039209150"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10334-012-0336-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041467457", 
          "https://doi.org/10.1007/s10334-012-0336-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.23088", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045482364"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/1141911.1141915", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047393046"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/nbm.3443", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048089709"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3174/ajnr.a4259", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051298067"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.24431", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052847746"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.10369", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053519578"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tmi.2012.2196707", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061695910"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tmi.2014.2359238", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061696391"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10334-017-0607-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1074217197", 
          "https://doi.org/10.1007/s10334-017-0607-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10334-017-0607-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1074217197", 
          "https://doi.org/10.1007/s10334-017-0607-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1077034597", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1077383832", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/embc.2013.6609697", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1078796395"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/isbi.2011.5872579", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1078844720"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3978/j.issn.2223-4292.2014.02.01", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1078883502"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3174/ajnr.a5051", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1079387538"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3174/ajnr.a5051", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1079387538"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jmri.25595", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083523237"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-04", 
    "datePublishedReg": "2018-04-01", 
    "description": "OBJECTIVES: To evaluate an accelerated 4D flow MRI method that provides high temporal resolution in a clinically feasible acquisition time for intracranial velocity imaging.\nMATERIALS AND METHODS: Accelerated 4D flow MRI was developed by using a pseudo-random variable-density Cartesian undersampling strategy (CIRCUS) with the combination of k-t, parallel imaging and compressed sensing image reconstruction techniques (k-t SPARSE-SENSE). Four-dimensional flow data were acquired on five healthy volunteers and eight patients with intracranial aneurysms using CIRCUS (acceleration factor of R\u00a0=\u00a04, termed CIRCUS4) and GRAPPA (R\u00a0=\u00a02, termed GRAPPA2) as the reference method. Images with three times higher temporal resolution (R\u00a0=\u00a012, CIRCUS12) were also reconstructed from the same acquisition as CIRCUS4. Qualitative and quantitative image assessment was performed on the images acquired with different methods, and complex flow patterns in the aneurysms were identified and compared.\nRESULTS: Four-dimensional flow MRI with CIRCUS was achieved in 5\u00a0min and allowed further improved temporal resolution of <30\u00a0ms. Volunteer studies showed similar qualitative and quantitative evaluation obtained with the proposed approach compared to the reference (overall image scores: GRAPPA2 3.2\u00a0\u00b1\u00a00.6; CIRCUS4 3.1\u00a0\u00b1\u00a00.7; CIRCUS12 3.3\u00a0\u00b1\u00a00.4; difference of the peak velocities: -3.83\u00a0\u00b1\u00a07.72\u00a0cm/s between CIRCUS4 and GRAPPA2, -1.72\u00a0\u00b1\u00a08.41\u00a0cm/s between CIRCUS12 and GRAPPA2). In patients with intracranial aneurysms, the higher temporal resolution improved capturing of the flow features in intracranial aneurysms (pathline visualization scores: GRAPPA2 2.2\u00a0\u00b1\u00a00.2; CIRCUS4 2.5\u00a0\u00b1\u00a00.5; CIRCUS12 2.7\u00a0\u00b1\u00a00.6).\nCONCLUSION: The proposed rapid 4D flow MRI with a high temporal resolution is a promising tool for evaluating intracranial aneurysms in a clinically feasible acquisition time.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s10334-017-0646-8", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.3535673", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.6376750", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.2421543", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1104145", 
        "issn": [
          "0968-5243", 
          "1352-8661"
        ], 
        "name": "Magnetic Resonance Materials in Physics, Biology and Medicine", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "2", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "31"
      }
    ], 
    "name": "Highly accelerated intracranial 4D flow MRI: evaluation of healthy volunteers and patients with intracranial aneurysms", 
    "pagination": "295-307", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "30d88bc38cd756e4a96d29b4dca9f6ff75768372ad30c5aa9959114cda238a78"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "28785850"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "9310752"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10334-017-0646-8"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1091080342"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10334-017-0646-8", 
      "https://app.dimensions.ai/details/publication/pub.1091080342"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T09:42", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000346_0000000346/records_99843_00000004.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs10334-017-0646-8"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s10334-017-0646-8'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10334-017-0646-8'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10334-017-0646-8'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10334-017-0646-8'


 

This table displays all metadata directly associated to this object as RDF triples.

360 TRIPLES      21 PREDICATES      93 URIs      34 LITERALS      22 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10334-017-0646-8 schema:about N09e2bb35acca4f99a06a996817e581b3
2 N385754c2a92d406499c3942501d7327a
3 N568fc2a34448420cabc844a93b7f2c50
4 N8ae238fdba8e45b9a809671842237313
5 N96b4207c8cef4beca6970bccfcdd49f1
6 N96b9a29f64ff421dbf4b24d9157285ff
7 Nb1c973f7dd764f71896a9130ad859e23
8 Nba563c68f1824bb990eb8e987104c5a3
9 Nc647d9a88763464d964169f1413aeae6
10 Nccb64c6e67424d0c95529020913ac475
11 Ndd0a54c931e54059bcdbf7a1a497c81d
12 Nef5169b8cfd446ae91544b8ed92d6f87
13 Nfa0e45b4750c47ea91eb57b65c5bc6cf
14 anzsrc-for:08
15 anzsrc-for:0801
16 schema:author N771c530b20c94d75a550bed218bfd03c
17 schema:citation sg:pub.10.1007/s00234-009-0635-3
18 sg:pub.10.1007/s00330-014-3587-x
19 sg:pub.10.1007/s10334-012-0336-5
20 sg:pub.10.1007/s10334-017-0607-2
21 sg:pub.10.1186/1532-429x-13-55
22 sg:pub.10.1186/s12968-015-0174-5
23 https://app.dimensions.ai/details/publication/pub.1077034597
24 https://app.dimensions.ai/details/publication/pub.1077383832
25 https://doi.org/10.1002/(sici)1522-2594(200004)43:4<503::aid-mrm3>3.0.co;2-0
26 https://doi.org/10.1002/jmri.20494
27 https://doi.org/10.1002/jmri.23501
28 https://doi.org/10.1002/jmri.23778
29 https://doi.org/10.1002/jmri.25595
30 https://doi.org/10.1002/mrm.10171
31 https://doi.org/10.1002/mrm.10369
32 https://doi.org/10.1002/mrm.20730
33 https://doi.org/10.1002/mrm.21391
34 https://doi.org/10.1002/mrm.21763
35 https://doi.org/10.1002/mrm.21861
36 https://doi.org/10.1002/mrm.22199
37 https://doi.org/10.1002/mrm.22463
38 https://doi.org/10.1002/mrm.22875
39 https://doi.org/10.1002/mrm.23088
40 https://doi.org/10.1002/mrm.23297
41 https://doi.org/10.1002/mrm.24390
42 https://doi.org/10.1002/mrm.24431
43 https://doi.org/10.1002/mrm.24440
44 https://doi.org/10.1002/mrm.24514
45 https://doi.org/10.1002/mrm.24925
46 https://doi.org/10.1002/mrm.25317
47 https://doi.org/10.1002/nbm.3443
48 https://doi.org/10.1016/j.ejrad.2009.06.009
49 https://doi.org/10.1016/j.jmr.2010.01.001
50 https://doi.org/10.1016/j.mri.2009.05.042
51 https://doi.org/10.1016/j.mri.2013.05.009
52 https://doi.org/10.1109/embc.2013.6609697
53 https://doi.org/10.1109/isbi.2011.5872579
54 https://doi.org/10.1109/tmi.2012.2196707
55 https://doi.org/10.1109/tmi.2014.2359238
56 https://doi.org/10.1145/1141911.1141915
57 https://doi.org/10.1145/7529.8927
58 https://doi.org/10.1148/radiol.10091218
59 https://doi.org/10.1148/radiol.12120055
60 https://doi.org/10.1148/radiol.14140973
61 https://doi.org/10.1161/strokeaha.108.521617
62 https://doi.org/10.2463/mrms.2013-0008
63 https://doi.org/10.3174/ajnr.a1138
64 https://doi.org/10.3174/ajnr.a3537
65 https://doi.org/10.3174/ajnr.a4259
66 https://doi.org/10.3174/ajnr.a5051
67 https://doi.org/10.3978/j.issn.2223-4292.2014.02.01
68 schema:datePublished 2018-04
69 schema:datePublishedReg 2018-04-01
70 schema:description OBJECTIVES: To evaluate an accelerated 4D flow MRI method that provides high temporal resolution in a clinically feasible acquisition time for intracranial velocity imaging. MATERIALS AND METHODS: Accelerated 4D flow MRI was developed by using a pseudo-random variable-density Cartesian undersampling strategy (CIRCUS) with the combination of k-t, parallel imaging and compressed sensing image reconstruction techniques (k-t SPARSE-SENSE). Four-dimensional flow data were acquired on five healthy volunteers and eight patients with intracranial aneurysms using CIRCUS (acceleration factor of R = 4, termed CIRCUS4) and GRAPPA (R = 2, termed GRAPPA2) as the reference method. Images with three times higher temporal resolution (R = 12, CIRCUS12) were also reconstructed from the same acquisition as CIRCUS4. Qualitative and quantitative image assessment was performed on the images acquired with different methods, and complex flow patterns in the aneurysms were identified and compared. RESULTS: Four-dimensional flow MRI with CIRCUS was achieved in 5 min and allowed further improved temporal resolution of <30 ms. Volunteer studies showed similar qualitative and quantitative evaluation obtained with the proposed approach compared to the reference (overall image scores: GRAPPA2 3.2 ± 0.6; CIRCUS4 3.1 ± 0.7; CIRCUS12 3.3 ± 0.4; difference of the peak velocities: -3.83 ± 7.72 cm/s between CIRCUS4 and GRAPPA2, -1.72 ± 8.41 cm/s between CIRCUS12 and GRAPPA2). In patients with intracranial aneurysms, the higher temporal resolution improved capturing of the flow features in intracranial aneurysms (pathline visualization scores: GRAPPA2 2.2 ± 0.2; CIRCUS4 2.5 ± 0.5; CIRCUS12 2.7 ± 0.6). CONCLUSION: The proposed rapid 4D flow MRI with a high temporal resolution is a promising tool for evaluating intracranial aneurysms in a clinically feasible acquisition time.
71 schema:genre research_article
72 schema:inLanguage en
73 schema:isAccessibleForFree true
74 schema:isPartOf N16efdf2c3b804f6980c155433796254c
75 Nf5a1e03d342b40b3b09d21f19f6e77f5
76 sg:journal.1104145
77 schema:name Highly accelerated intracranial 4D flow MRI: evaluation of healthy volunteers and patients with intracranial aneurysms
78 schema:pagination 295-307
79 schema:productId N3eb13e0e1870426cb2cba5c0c7234dc7
80 N4658f033deb54995b36e366e960034db
81 N611ebbb621a24aaeafe5fe2f8ec7bc82
82 N98aaabf050fb42ac94ca51a79866b86e
83 Nb0210c23ef984478aa6e2787c26821ae
84 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091080342
85 https://doi.org/10.1007/s10334-017-0646-8
86 schema:sdDatePublished 2019-04-11T09:42
87 schema:sdLicense https://scigraph.springernature.com/explorer/license/
88 schema:sdPublisher N284c1a680d49492cbbfe73c683d44239
89 schema:url https://link.springer.com/10.1007%2Fs10334-017-0646-8
90 sgo:license sg:explorer/license/
91 sgo:sdDataset articles
92 rdf:type schema:ScholarlyArticle
93 N09e2bb35acca4f99a06a996817e581b3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
94 schema:name Humans
95 rdf:type schema:DefinedTerm
96 N16efdf2c3b804f6980c155433796254c schema:issueNumber 2
97 rdf:type schema:PublicationIssue
98 N284c1a680d49492cbbfe73c683d44239 schema:name Springer Nature - SN SciGraph project
99 rdf:type schema:Organization
100 N3175799fde9a428cb5fd05a5df90051f rdf:first sg:person.01036206317.54
101 rdf:rest rdf:nil
102 N353ef04a829b4f71b91d2d2d6872eb42 rdf:first sg:person.0757124227.36
103 rdf:rest N4ca54c80846e4c2d9cf7e0a3336eb608
104 N385754c2a92d406499c3942501d7327a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
105 schema:name Male
106 rdf:type schema:DefinedTerm
107 N3eb13e0e1870426cb2cba5c0c7234dc7 schema:name doi
108 schema:value 10.1007/s10334-017-0646-8
109 rdf:type schema:PropertyValue
110 N4658f033deb54995b36e366e960034db schema:name readcube_id
111 schema:value 30d88bc38cd756e4a96d29b4dca9f6ff75768372ad30c5aa9959114cda238a78
112 rdf:type schema:PropertyValue
113 N4ca54c80846e4c2d9cf7e0a3336eb608 rdf:first sg:person.012270714461.46
114 rdf:rest N8947d1306b714bd4b068fccb1dcfd7b7
115 N4da8509919ab4b9b8926792ef76568ae rdf:first sg:person.0603101342.45
116 rdf:rest N3175799fde9a428cb5fd05a5df90051f
117 N5147cd6c7f684c36884c20cce0fde137 rdf:first sg:person.01222326531.10
118 rdf:rest N60519c2f171e44acbb6ece5512c2beca
119 N568fc2a34448420cabc844a93b7f2c50 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
120 schema:name Image Enhancement
121 rdf:type schema:DefinedTerm
122 N60519c2f171e44acbb6ece5512c2beca rdf:first sg:person.0636457767.19
123 rdf:rest Nd602a3c75b6b4d7aaaa66296cc7caada
124 N611ebbb621a24aaeafe5fe2f8ec7bc82 schema:name nlm_unique_id
125 schema:value 9310752
126 rdf:type schema:PropertyValue
127 N6477649bdaa2427bb1ddb97231f243b2 schema:affiliation https://www.grid.ac/institutes/grid.266102.1
128 schema:familyName Koskas
129 schema:givenName Louise
130 rdf:type schema:Person
131 N771c530b20c94d75a550bed218bfd03c rdf:first sg:person.01234554053.02
132 rdf:rest Nbeb34daa2fde43abbdc627141785e550
133 N8947d1306b714bd4b068fccb1dcfd7b7 rdf:first sg:person.01017622760.06
134 rdf:rest Na7dde66d4a0e406489ee1a5f54017736
135 N8ae238fdba8e45b9a809671842237313 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
136 schema:name Adult
137 rdf:type schema:DefinedTerm
138 N96b4207c8cef4beca6970bccfcdd49f1 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
139 schema:name Healthy Volunteers
140 rdf:type schema:DefinedTerm
141 N96b9a29f64ff421dbf4b24d9157285ff schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
142 schema:name Female
143 rdf:type schema:DefinedTerm
144 N98aaabf050fb42ac94ca51a79866b86e schema:name pubmed_id
145 schema:value 28785850
146 rdf:type schema:PropertyValue
147 Na7dde66d4a0e406489ee1a5f54017736 rdf:first sg:person.01215037004.85
148 rdf:rest N5147cd6c7f684c36884c20cce0fde137
149 Nb0210c23ef984478aa6e2787c26821ae schema:name dimensions_id
150 schema:value pub.1091080342
151 rdf:type schema:PropertyValue
152 Nb1c973f7dd764f71896a9130ad859e23 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
153 schema:name Magnetic Resonance Imaging
154 rdf:type schema:DefinedTerm
155 Nba563c68f1824bb990eb8e987104c5a3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
156 schema:name Magnetic Resonance Angiography
157 rdf:type schema:DefinedTerm
158 Nbeb34daa2fde43abbdc627141785e550 rdf:first N6477649bdaa2427bb1ddb97231f243b2
159 rdf:rest N353ef04a829b4f71b91d2d2d6872eb42
160 Nc647d9a88763464d964169f1413aeae6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
161 schema:name Reproducibility of Results
162 rdf:type schema:DefinedTerm
163 Nccb64c6e67424d0c95529020913ac475 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
164 schema:name Imaging, Three-Dimensional
165 rdf:type schema:DefinedTerm
166 Nd602a3c75b6b4d7aaaa66296cc7caada rdf:first sg:person.0717014647.17
167 rdf:rest N4da8509919ab4b9b8926792ef76568ae
168 Ndd0a54c931e54059bcdbf7a1a497c81d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
169 schema:name Blood Flow Velocity
170 rdf:type schema:DefinedTerm
171 Nef5169b8cfd446ae91544b8ed92d6f87 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
172 schema:name Intracranial Aneurysm
173 rdf:type schema:DefinedTerm
174 Nf5a1e03d342b40b3b09d21f19f6e77f5 schema:volumeNumber 31
175 rdf:type schema:PublicationVolume
176 Nfa0e45b4750c47ea91eb57b65c5bc6cf schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
177 schema:name Image Processing, Computer-Assisted
178 rdf:type schema:DefinedTerm
179 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
180 schema:name Information and Computing Sciences
181 rdf:type schema:DefinedTerm
182 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
183 schema:name Artificial Intelligence and Image Processing
184 rdf:type schema:DefinedTerm
185 sg:grant.2421543 http://pending.schema.org/fundedItem sg:pub.10.1007/s10334-017-0646-8
186 rdf:type schema:MonetaryGrant
187 sg:grant.3535673 http://pending.schema.org/fundedItem sg:pub.10.1007/s10334-017-0646-8
188 rdf:type schema:MonetaryGrant
189 sg:grant.6376750 http://pending.schema.org/fundedItem sg:pub.10.1007/s10334-017-0646-8
190 rdf:type schema:MonetaryGrant
191 sg:journal.1104145 schema:issn 0968-5243
192 1352-8661
193 schema:name Magnetic Resonance Materials in Physics, Biology and Medicine
194 rdf:type schema:Periodical
195 sg:person.01017622760.06 schema:affiliation https://www.grid.ac/institutes/grid.266102.1
196 schema:familyName Wang
197 schema:givenName Yan
198 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01017622760.06
199 rdf:type schema:Person
200 sg:person.01036206317.54 schema:affiliation https://www.grid.ac/institutes/grid.410372.3
201 schema:familyName Saloner
202 schema:givenName David
203 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01036206317.54
204 rdf:type schema:Person
205 sg:person.01215037004.85 schema:affiliation https://www.grid.ac/institutes/grid.266102.1
206 schema:familyName Haraldsson
207 schema:givenName Henrik
208 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01215037004.85
209 rdf:type schema:Person
210 sg:person.01222326531.10 schema:affiliation https://www.grid.ac/institutes/grid.266102.1
211 schema:familyName Kefayati
212 schema:givenName Sarah
213 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01222326531.10
214 rdf:type schema:Person
215 sg:person.012270714461.46 schema:affiliation https://www.grid.ac/institutes/grid.266102.1
216 schema:familyName Kao
217 schema:givenName Evan
218 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012270714461.46
219 rdf:type schema:Person
220 sg:person.01234554053.02 schema:affiliation https://www.grid.ac/institutes/grid.266102.1
221 schema:familyName Liu
222 schema:givenName Jing
223 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01234554053.02
224 rdf:type schema:Person
225 sg:person.0603101342.45 schema:affiliation https://www.grid.ac/institutes/grid.415886.6
226 schema:familyName Laub
227 schema:givenName Gerhard
228 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0603101342.45
229 rdf:type schema:Person
230 sg:person.0636457767.19 schema:affiliation https://www.grid.ac/institutes/grid.266102.1
231 schema:familyName Zhu
232 schema:givenName Chengcheng
233 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0636457767.19
234 rdf:type schema:Person
235 sg:person.0717014647.17 schema:affiliation https://www.grid.ac/institutes/grid.415886.6
236 schema:familyName Ahn
237 schema:givenName Sinyeob
238 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0717014647.17
239 rdf:type schema:Person
240 sg:person.0757124227.36 schema:affiliation https://www.grid.ac/institutes/grid.266102.1
241 schema:familyName Faraji
242 schema:givenName Farshid
243 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0757124227.36
244 rdf:type schema:Person
245 sg:pub.10.1007/s00234-009-0635-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011130292
246 https://doi.org/10.1007/s00234-009-0635-3
247 rdf:type schema:CreativeWork
248 sg:pub.10.1007/s00330-014-3587-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1023454576
249 https://doi.org/10.1007/s00330-014-3587-x
250 rdf:type schema:CreativeWork
251 sg:pub.10.1007/s10334-012-0336-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041467457
252 https://doi.org/10.1007/s10334-012-0336-5
253 rdf:type schema:CreativeWork
254 sg:pub.10.1007/s10334-017-0607-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1074217197
255 https://doi.org/10.1007/s10334-017-0607-2
256 rdf:type schema:CreativeWork
257 sg:pub.10.1186/1532-429x-13-55 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028621413
258 https://doi.org/10.1186/1532-429x-13-55
259 rdf:type schema:CreativeWork
260 sg:pub.10.1186/s12968-015-0174-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027175700
261 https://doi.org/10.1186/s12968-015-0174-5
262 rdf:type schema:CreativeWork
263 https://app.dimensions.ai/details/publication/pub.1077034597 schema:CreativeWork
264 https://app.dimensions.ai/details/publication/pub.1077383832 schema:CreativeWork
265 https://doi.org/10.1002/(sici)1522-2594(200004)43:4<503::aid-mrm3>3.0.co;2-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010710698
266 rdf:type schema:CreativeWork
267 https://doi.org/10.1002/jmri.20494 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014955319
268 rdf:type schema:CreativeWork
269 https://doi.org/10.1002/jmri.23501 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031749574
270 rdf:type schema:CreativeWork
271 https://doi.org/10.1002/jmri.23778 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039209150
272 rdf:type schema:CreativeWork
273 https://doi.org/10.1002/jmri.25595 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083523237
274 rdf:type schema:CreativeWork
275 https://doi.org/10.1002/mrm.10171 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012449961
276 rdf:type schema:CreativeWork
277 https://doi.org/10.1002/mrm.10369 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053519578
278 rdf:type schema:CreativeWork
279 https://doi.org/10.1002/mrm.20730 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021030211
280 rdf:type schema:CreativeWork
281 https://doi.org/10.1002/mrm.21391 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037838340
282 rdf:type schema:CreativeWork
283 https://doi.org/10.1002/mrm.21763 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013588487
284 rdf:type schema:CreativeWork
285 https://doi.org/10.1002/mrm.21861 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007653740
286 rdf:type schema:CreativeWork
287 https://doi.org/10.1002/mrm.22199 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016013763
288 rdf:type schema:CreativeWork
289 https://doi.org/10.1002/mrm.22463 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004356511
290 rdf:type schema:CreativeWork
291 https://doi.org/10.1002/mrm.22875 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027836464
292 rdf:type schema:CreativeWork
293 https://doi.org/10.1002/mrm.23088 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045482364
294 rdf:type schema:CreativeWork
295 https://doi.org/10.1002/mrm.23297 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004424496
296 rdf:type schema:CreativeWork
297 https://doi.org/10.1002/mrm.24390 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029763149
298 rdf:type schema:CreativeWork
299 https://doi.org/10.1002/mrm.24431 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052847746
300 rdf:type schema:CreativeWork
301 https://doi.org/10.1002/mrm.24440 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026807801
302 rdf:type schema:CreativeWork
303 https://doi.org/10.1002/mrm.24514 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035041541
304 rdf:type schema:CreativeWork
305 https://doi.org/10.1002/mrm.24925 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018512831
306 rdf:type schema:CreativeWork
307 https://doi.org/10.1002/mrm.25317 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003461669
308 rdf:type schema:CreativeWork
309 https://doi.org/10.1002/nbm.3443 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048089709
310 rdf:type schema:CreativeWork
311 https://doi.org/10.1016/j.ejrad.2009.06.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017132316
312 rdf:type schema:CreativeWork
313 https://doi.org/10.1016/j.jmr.2010.01.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030625609
314 rdf:type schema:CreativeWork
315 https://doi.org/10.1016/j.mri.2009.05.042 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021141340
316 rdf:type schema:CreativeWork
317 https://doi.org/10.1016/j.mri.2013.05.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003063093
318 rdf:type schema:CreativeWork
319 https://doi.org/10.1109/embc.2013.6609697 schema:sameAs https://app.dimensions.ai/details/publication/pub.1078796395
320 rdf:type schema:CreativeWork
321 https://doi.org/10.1109/isbi.2011.5872579 schema:sameAs https://app.dimensions.ai/details/publication/pub.1078844720
322 rdf:type schema:CreativeWork
323 https://doi.org/10.1109/tmi.2012.2196707 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061695910
324 rdf:type schema:CreativeWork
325 https://doi.org/10.1109/tmi.2014.2359238 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061696391
326 rdf:type schema:CreativeWork
327 https://doi.org/10.1145/1141911.1141915 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047393046
328 rdf:type schema:CreativeWork
329 https://doi.org/10.1145/7529.8927 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017643740
330 rdf:type schema:CreativeWork
331 https://doi.org/10.1148/radiol.10091218 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000162385
332 rdf:type schema:CreativeWork
333 https://doi.org/10.1148/radiol.12120055 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004343416
334 rdf:type schema:CreativeWork
335 https://doi.org/10.1148/radiol.14140973 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001401424
336 rdf:type schema:CreativeWork
337 https://doi.org/10.1161/strokeaha.108.521617 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028198220
338 rdf:type schema:CreativeWork
339 https://doi.org/10.2463/mrms.2013-0008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025365323
340 rdf:type schema:CreativeWork
341 https://doi.org/10.3174/ajnr.a1138 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007292486
342 rdf:type schema:CreativeWork
343 https://doi.org/10.3174/ajnr.a3537 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022374636
344 rdf:type schema:CreativeWork
345 https://doi.org/10.3174/ajnr.a4259 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051298067
346 rdf:type schema:CreativeWork
347 https://doi.org/10.3174/ajnr.a5051 schema:sameAs https://app.dimensions.ai/details/publication/pub.1079387538
348 rdf:type schema:CreativeWork
349 https://doi.org/10.3978/j.issn.2223-4292.2014.02.01 schema:sameAs https://app.dimensions.ai/details/publication/pub.1078883502
350 rdf:type schema:CreativeWork
351 https://www.grid.ac/institutes/grid.266102.1 schema:alternateName University of California, San Francisco
352 schema:name Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry St, Suite 350, 94107, San Francisco, CA, USA
353 rdf:type schema:Organization
354 https://www.grid.ac/institutes/grid.410372.3 schema:alternateName San Francisco VA Medical Center
355 schema:name Radiology Service, VA Medical Center, San Francisco, CA, USA
356 Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry St, Suite 350, 94107, San Francisco, CA, USA
357 rdf:type schema:Organization
358 https://www.grid.ac/institutes/grid.415886.6 schema:alternateName Siemens Healthcare (United States)
359 schema:name Siemens Healthcare, California, USA
360 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...