Automatic Artery-Vein Separation from Thoracic CT Images Using Integer Programming View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2015

AUTHORS

Christian Payer , Michael Pienn , Zoltán Bálint , Andrea Olschewski , Horst Olschewski , Martin Urschler

ABSTRACT

Automated computer-aided analysis of lung vessels has shown to yield promising results for non-invasive diagnosis of lung diseases. In order to detect vascular changes affecting arteries and veins differently, an algorithm capable of identifying these two compartments is needed. We propose a fully automatic algorithm that separates arteries and veins in thoracic computed tomography (CT) images based on two integer programs. The first extracts multiple subtrees inside a graph of vessel paths. The second labels each tree as either artery or vein by maximizing both, the contact surface in their Voronoi diagram, and a measure based on closeness to accompanying bronchi. We evaluate the performance of our automatic algorithm on 10 manual segmentations of arterial and venous trees from patients with and without pulmonary vascular disease, achieving an average voxel based overlap of 94.1% (range: 85.0% – 98.7%), outperforming a recent state-of-the-art interactive method. More... »

PAGES

36-43

References to SciGraph publications

  • 2014. Simultaneous Segmentation and Anatomical Labeling of the Cerebral Vasculature in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION – MICCAI 2014
  • Book

    TITLE

    Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015

    ISBN

    978-3-319-24570-6
    978-3-319-24571-3

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-319-24571-3_5

    DOI

    http://dx.doi.org/10.1007/978-3-319-24571-3_5

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1034371079


    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/2008/1102", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Cardiorespiratory Medicine and Haematology", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Medical and Health Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Ludwig Boltzmann Institute for Lung Vascular Research", 
              "id": "https://www.grid.ac/institutes/grid.489038.e", 
              "name": [
                "Institute for Computer Graphics and Vision, BioTechMed, Graz University of Technology", 
                "Ludwig Boltzmann Institute for Lung Vascular Research"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Payer", 
            "givenName": "Christian", 
            "id": "sg:person.015110704055.73", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015110704055.73"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Ludwig Boltzmann Institute for Lung Vascular Research", 
              "id": "https://www.grid.ac/institutes/grid.489038.e", 
              "name": [
                "Ludwig Boltzmann Institute for Lung Vascular Research"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Pienn", 
            "givenName": "Michael", 
            "id": "sg:person.0740236300.74", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0740236300.74"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Ludwig Boltzmann Institute for Lung Vascular Research", 
              "id": "https://www.grid.ac/institutes/grid.489038.e", 
              "name": [
                "Ludwig Boltzmann Institute for Lung Vascular Research"
              ], 
              "type": "Organization"
            }, 
            "familyName": "B\u00e1lint", 
            "givenName": "Zolt\u00e1n", 
            "id": "sg:person.01117244633.07", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01117244633.07"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Ludwig Boltzmann Institute for Lung Vascular Research", 
              "id": "https://www.grid.ac/institutes/grid.489038.e", 
              "name": [
                "Ludwig Boltzmann Institute for Lung Vascular Research"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Olschewski", 
            "givenName": "Andrea", 
            "id": "sg:person.01305567666.52", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01305567666.52"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Department of Pulmonology, Medical University of Graz"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Olschewski", 
            "givenName": "Horst", 
            "id": "sg:person.0720160270.18", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0720160270.18"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Ludwig Boltzmann Institute for Clinical Forensic Imaging", 
                "Institute for Computer Graphics and Vision, BioTechMed, Graz University of Technology"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Urschler", 
            "givenName": "Martin", 
            "id": "sg:person.01263233742.39", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01263233742.39"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1164/rccm.201301-0162oc", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001084858"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1117/12.595286", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006041793"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1118/1.4811203", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016344043"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1118/1.3355892", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025978779"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.media.2009.07.001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035795628"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0087515", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039588268"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-319-10404-1_39", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050990439", 
              "https://doi.org/10.1007/978-3-319-10404-1_39"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1088/0031-9155/58/17/r187", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059029916"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tbme.2012.2212894", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061528934"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tmi.2002.806586", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061694357"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tmi.2009.2038224", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061695508"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/cvpr.2013.238", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093313472"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/cvpr.2013.238", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093313472"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2015", 
        "datePublishedReg": "2015-01-01", 
        "description": "Automated computer-aided analysis of lung vessels has shown to yield promising results for non-invasive diagnosis of lung diseases. In order to detect vascular changes affecting arteries and veins differently, an algorithm capable of identifying these two compartments is needed. We propose a fully automatic algorithm that separates arteries and veins in thoracic computed tomography (CT) images based on two integer programs. The first extracts multiple subtrees inside a graph of vessel paths. The second labels each tree as either artery or vein by maximizing both, the contact surface in their Voronoi diagram, and a measure based on closeness to accompanying bronchi. We evaluate the performance of our automatic algorithm on 10 manual segmentations of arterial and venous trees from patients with and without pulmonary vascular disease, achieving an average voxel based overlap of 94.1% (range: 85.0% \u2013 98.7%), outperforming a recent state-of-the-art interactive method.", 
        "editor": [
          {
            "familyName": "Navab", 
            "givenName": "Nassir", 
            "type": "Person"
          }, 
          {
            "familyName": "Hornegger", 
            "givenName": "Joachim", 
            "type": "Person"
          }, 
          {
            "familyName": "Wells", 
            "givenName": "William M.", 
            "type": "Person"
          }, 
          {
            "familyName": "Frangi", 
            "givenName": "Alejandro", 
            "type": "Person"
          }
        ], 
        "genre": "chapter", 
        "id": "sg:pub.10.1007/978-3-319-24571-3_5", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": {
          "isbn": [
            "978-3-319-24570-6", 
            "978-3-319-24571-3"
          ], 
          "name": "Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015", 
          "type": "Book"
        }, 
        "name": "Automatic Artery-Vein Separation from Thoracic CT Images Using Integer Programming", 
        "pagination": "36-43", 
        "productId": [
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/978-3-319-24571-3_5"
            ]
          }, 
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "a3bad49dafbb12163b577256d5d4cda28a5ac76aa42315ce5d01421e9b8bccd1"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1034371079"
            ]
          }
        ], 
        "publisher": {
          "location": "Cham", 
          "name": "Springer International Publishing", 
          "type": "Organisation"
        }, 
        "sameAs": [
          "https://doi.org/10.1007/978-3-319-24571-3_5", 
          "https://app.dimensions.ai/details/publication/pub.1034371079"
        ], 
        "sdDataset": "chapters", 
        "sdDatePublished": "2019-04-15T12:33", 
        "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/v90/0000000001_0000000264/records_8663_00000264.jsonl", 
        "type": "Chapter", 
        "url": "http://link.springer.com/10.1007/978-3-319-24571-3_5"
      }
    ]
     

    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.10.1007/978-3-319-24571-3_5'

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

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-24571-3_5'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-24571-3_5'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-24571-3_5'


     

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

    158 TRIPLES      23 PREDICATES      39 URIs      20 LITERALS      8 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/978-3-319-24571-3_5 schema:about anzsrc-for:11
    2 anzsrc-for:1102
    3 schema:author N6ae8f7ab973f4498a5d218dd24d0702c
    4 schema:citation sg:pub.10.1007/978-3-319-10404-1_39
    5 https://doi.org/10.1016/j.media.2009.07.001
    6 https://doi.org/10.1088/0031-9155/58/17/r187
    7 https://doi.org/10.1109/cvpr.2013.238
    8 https://doi.org/10.1109/tbme.2012.2212894
    9 https://doi.org/10.1109/tmi.2002.806586
    10 https://doi.org/10.1109/tmi.2009.2038224
    11 https://doi.org/10.1117/12.595286
    12 https://doi.org/10.1118/1.3355892
    13 https://doi.org/10.1118/1.4811203
    14 https://doi.org/10.1164/rccm.201301-0162oc
    15 https://doi.org/10.1371/journal.pone.0087515
    16 schema:datePublished 2015
    17 schema:datePublishedReg 2015-01-01
    18 schema:description Automated computer-aided analysis of lung vessels has shown to yield promising results for non-invasive diagnosis of lung diseases. In order to detect vascular changes affecting arteries and veins differently, an algorithm capable of identifying these two compartments is needed. We propose a fully automatic algorithm that separates arteries and veins in thoracic computed tomography (CT) images based on two integer programs. The first extracts multiple subtrees inside a graph of vessel paths. The second labels each tree as either artery or vein by maximizing both, the contact surface in their Voronoi diagram, and a measure based on closeness to accompanying bronchi. We evaluate the performance of our automatic algorithm on 10 manual segmentations of arterial and venous trees from patients with and without pulmonary vascular disease, achieving an average voxel based overlap of 94.1% (range: 85.0% – 98.7%), outperforming a recent state-of-the-art interactive method.
    19 schema:editor Nb6963f4eb714461faa8041a883172c84
    20 schema:genre chapter
    21 schema:inLanguage en
    22 schema:isAccessibleForFree false
    23 schema:isPartOf Na8cd405fb2054affb8eb741da0268e60
    24 schema:name Automatic Artery-Vein Separation from Thoracic CT Images Using Integer Programming
    25 schema:pagination 36-43
    26 schema:productId Nb99a690eda5f44a1832f2f809e452c92
    27 Nc9c7aa6839bc4e19b84cd55cda10f028
    28 Ncbc4e547d61d483e8a216144f96b1d72
    29 schema:publisher N011f4045b7a4479c93c603b0ea642377
    30 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034371079
    31 https://doi.org/10.1007/978-3-319-24571-3_5
    32 schema:sdDatePublished 2019-04-15T12:33
    33 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    34 schema:sdPublisher Na844e7b7cfec4a52b4f507643f973c31
    35 schema:url http://link.springer.com/10.1007/978-3-319-24571-3_5
    36 sgo:license sg:explorer/license/
    37 sgo:sdDataset chapters
    38 rdf:type schema:Chapter
    39 N011f4045b7a4479c93c603b0ea642377 schema:location Cham
    40 schema:name Springer International Publishing
    41 rdf:type schema:Organisation
    42 N01c834b4de764ac0888115c372e4159d rdf:first sg:person.0740236300.74
    43 rdf:rest Nb53fe86c4de94d5aa7ae025dbb90590e
    44 N183da0bf141840bf829537c1608f8231 schema:name Institute for Computer Graphics and Vision, BioTechMed, Graz University of Technology
    45 Ludwig Boltzmann Institute for Clinical Forensic Imaging
    46 rdf:type schema:Organization
    47 N3223b993ecb74dae8f634b971c7226f6 rdf:first sg:person.01263233742.39
    48 rdf:rest rdf:nil
    49 N497e9d4bb3fc463c8f0ed1c7eaf6605a schema:name Department of Pulmonology, Medical University of Graz
    50 rdf:type schema:Organization
    51 N56d6f3fe80ef420eb4a948823d5ad927 rdf:first Nab97b189b5464a748380683c7ea05bca
    52 rdf:rest Nc7feaf93ad2247bd909baed28728e736
    53 N5f5fa62219ca46849433a3f4198c623a schema:familyName Navab
    54 schema:givenName Nassir
    55 rdf:type schema:Person
    56 N6ae8f7ab973f4498a5d218dd24d0702c rdf:first sg:person.015110704055.73
    57 rdf:rest N01c834b4de764ac0888115c372e4159d
    58 N7117ec92ebed4d6884dab52b4a8858fc schema:familyName Wells
    59 schema:givenName William M.
    60 rdf:type schema:Person
    61 Na844e7b7cfec4a52b4f507643f973c31 schema:name Springer Nature - SN SciGraph project
    62 rdf:type schema:Organization
    63 Na8cd405fb2054affb8eb741da0268e60 schema:isbn 978-3-319-24570-6
    64 978-3-319-24571-3
    65 schema:name Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015
    66 rdf:type schema:Book
    67 Nab97b189b5464a748380683c7ea05bca schema:familyName Hornegger
    68 schema:givenName Joachim
    69 rdf:type schema:Person
    70 Naf2cdbf7d8aa4db389ccbd0d2bce55ce rdf:first sg:person.0720160270.18
    71 rdf:rest N3223b993ecb74dae8f634b971c7226f6
    72 Nb53fe86c4de94d5aa7ae025dbb90590e rdf:first sg:person.01117244633.07
    73 rdf:rest Ne6a89735e818452088792723e76c754b
    74 Nb6963f4eb714461faa8041a883172c84 rdf:first N5f5fa62219ca46849433a3f4198c623a
    75 rdf:rest N56d6f3fe80ef420eb4a948823d5ad927
    76 Nb99a690eda5f44a1832f2f809e452c92 schema:name dimensions_id
    77 schema:value pub.1034371079
    78 rdf:type schema:PropertyValue
    79 Nc7feaf93ad2247bd909baed28728e736 rdf:first N7117ec92ebed4d6884dab52b4a8858fc
    80 rdf:rest Ncb784ee68e254d92a2a9d5b1c0c2003d
    81 Nc9c7aa6839bc4e19b84cd55cda10f028 schema:name doi
    82 schema:value 10.1007/978-3-319-24571-3_5
    83 rdf:type schema:PropertyValue
    84 Ncb784ee68e254d92a2a9d5b1c0c2003d rdf:first Nd74e8119fbce452a9a258492a79c27c3
    85 rdf:rest rdf:nil
    86 Ncbc4e547d61d483e8a216144f96b1d72 schema:name readcube_id
    87 schema:value a3bad49dafbb12163b577256d5d4cda28a5ac76aa42315ce5d01421e9b8bccd1
    88 rdf:type schema:PropertyValue
    89 Nd74e8119fbce452a9a258492a79c27c3 schema:familyName Frangi
    90 schema:givenName Alejandro
    91 rdf:type schema:Person
    92 Ne6a89735e818452088792723e76c754b rdf:first sg:person.01305567666.52
    93 rdf:rest Naf2cdbf7d8aa4db389ccbd0d2bce55ce
    94 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
    95 schema:name Medical and Health Sciences
    96 rdf:type schema:DefinedTerm
    97 anzsrc-for:1102 schema:inDefinedTermSet anzsrc-for:
    98 schema:name Cardiorespiratory Medicine and Haematology
    99 rdf:type schema:DefinedTerm
    100 sg:person.01117244633.07 schema:affiliation https://www.grid.ac/institutes/grid.489038.e
    101 schema:familyName Bálint
    102 schema:givenName Zoltán
    103 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01117244633.07
    104 rdf:type schema:Person
    105 sg:person.01263233742.39 schema:affiliation N183da0bf141840bf829537c1608f8231
    106 schema:familyName Urschler
    107 schema:givenName Martin
    108 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01263233742.39
    109 rdf:type schema:Person
    110 sg:person.01305567666.52 schema:affiliation https://www.grid.ac/institutes/grid.489038.e
    111 schema:familyName Olschewski
    112 schema:givenName Andrea
    113 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01305567666.52
    114 rdf:type schema:Person
    115 sg:person.015110704055.73 schema:affiliation https://www.grid.ac/institutes/grid.489038.e
    116 schema:familyName Payer
    117 schema:givenName Christian
    118 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015110704055.73
    119 rdf:type schema:Person
    120 sg:person.0720160270.18 schema:affiliation N497e9d4bb3fc463c8f0ed1c7eaf6605a
    121 schema:familyName Olschewski
    122 schema:givenName Horst
    123 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0720160270.18
    124 rdf:type schema:Person
    125 sg:person.0740236300.74 schema:affiliation https://www.grid.ac/institutes/grid.489038.e
    126 schema:familyName Pienn
    127 schema:givenName Michael
    128 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0740236300.74
    129 rdf:type schema:Person
    130 sg:pub.10.1007/978-3-319-10404-1_39 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050990439
    131 https://doi.org/10.1007/978-3-319-10404-1_39
    132 rdf:type schema:CreativeWork
    133 https://doi.org/10.1016/j.media.2009.07.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035795628
    134 rdf:type schema:CreativeWork
    135 https://doi.org/10.1088/0031-9155/58/17/r187 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059029916
    136 rdf:type schema:CreativeWork
    137 https://doi.org/10.1109/cvpr.2013.238 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093313472
    138 rdf:type schema:CreativeWork
    139 https://doi.org/10.1109/tbme.2012.2212894 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061528934
    140 rdf:type schema:CreativeWork
    141 https://doi.org/10.1109/tmi.2002.806586 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061694357
    142 rdf:type schema:CreativeWork
    143 https://doi.org/10.1109/tmi.2009.2038224 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061695508
    144 rdf:type schema:CreativeWork
    145 https://doi.org/10.1117/12.595286 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006041793
    146 rdf:type schema:CreativeWork
    147 https://doi.org/10.1118/1.3355892 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025978779
    148 rdf:type schema:CreativeWork
    149 https://doi.org/10.1118/1.4811203 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016344043
    150 rdf:type schema:CreativeWork
    151 https://doi.org/10.1164/rccm.201301-0162oc schema:sameAs https://app.dimensions.ai/details/publication/pub.1001084858
    152 rdf:type schema:CreativeWork
    153 https://doi.org/10.1371/journal.pone.0087515 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039588268
    154 rdf:type schema:CreativeWork
    155 https://www.grid.ac/institutes/grid.489038.e schema:alternateName Ludwig Boltzmann Institute for Lung Vascular Research
    156 schema:name Institute for Computer Graphics and Vision, BioTechMed, Graz University of Technology
    157 Ludwig Boltzmann Institute for Lung Vascular Research
    158 rdf:type schema:Organization
     




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


    ...