Non Rigid Registration of 3D Images to Laparoscopic Video for Image Guided Surgery View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2016

AUTHORS

Max Allan , Ankur Kapoor , Philip Mewes , Peter Mountney

ABSTRACT

Image guidance and the visualization of sub surface structures during laparoscopic procedures have the potential to change the current capabilities of surgery. Increased target localization accuracy and the identification of critical structures can reduce resection mar-gins, procedure time and tissue trauma while simplifying procedures and enabling new functional capabilities. Image guidance requires the registration of 3D images to the laparoscopic video. Tissue deformation and lack of cross modality landmarks make this challenging. Registration can be performed by aligning the 3D image to a surface reconstructed from stereo laparoscopic images. Current research is focused on creating more generic stereo reconstruction techniques and rigid registration methods. This paper proposes a novel stereo reconstruction approach which exploits prior knowledge of patient specific organ models and outlier robust non rigid registration. The approach is validated on phantom data and the practical application of the reconstruction is demonstrated on in vivo data. More... »

PAGES

109-116

References to SciGraph publications

  • 2008. Efficient 3D Tracking for Motion Compensation in Beating Heart Surgery in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION – MICCAI 2008
  • 2010. Dynamic Guidance for Robotic Surgery Using Image-Constrained Biomechanical Models in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION – MICCAI 2010
  • 2004. Stereo-Based Endoscopic Tracking of Cardiac Surface Deformation in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION – MICCAI 2004
  • 2010. Accounting for Anisotropic Noise in Fine Registration of Time-of-Flight Range Data with High-Resolution Surface Data in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION – MICCAI 2010
  • 2010. Real-Time Stereo Reconstruction in Robotically Assisted Minimally Invasive Surgery in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION – MICCAI 2010
  • 2012. Template-Based Conformal Shape-from-Motion-and-Shading for Laparoscopy in INFORMATION PROCESSING IN COMPUTER-ASSISTED INTERVENTIONS
  • Book

    TITLE

    Computer-Assisted and Robotic Endoscopy

    ISBN

    978-3-319-29964-8
    978-3-319-29965-5

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-319-29965-5_11

    DOI

    http://dx.doi.org/10.1007/978-3-319-29965-5_11

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1040767189


    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"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "name": [
                "Siemens Corporate Research"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Allan", 
            "givenName": "Max", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Siemens Corporate Research"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Kapoor", 
            "givenName": "Ankur", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Siemens Healthcare"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Mewes", 
            "givenName": "Philip", 
            "id": "sg:person.013200653273.40", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013200653273.40"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Siemens Corporate Research"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Mountney", 
            "givenName": "Peter", 
            "id": "sg:person.0702376130.54", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0702376130.54"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/978-3-642-15705-9_31", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000754864", 
              "https://doi.org/10.1007/978-3-642-15705-9_31"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-15705-9_31", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000754864", 
              "https://doi.org/10.1007/978-3-642-15705-9_31"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-85990-1_82", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003815683", 
              "https://doi.org/10.1007/978-3-540-85990-1_82"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-85990-1_82", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003815683", 
              "https://doi.org/10.1007/978-3-540-85990-1_82"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1146/annurev-bioeng-071910-124757", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010713116"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-15705-9_34", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011146145", 
              "https://doi.org/10.1007/978-3-642-15705-9_34"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-15705-9_34", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011146145", 
              "https://doi.org/10.1007/978-3-642-15705-9_34"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-30618-1_1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014777228", 
              "https://doi.org/10.1007/978-3-642-30618-1_1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.urology.2008.11.040", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016366600"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1117/12.911994", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019909984"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-15705-9_10", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021700413", 
              "https://doi.org/10.1007/978-3-642-15705-9_10"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-15705-9_10", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021700413", 
              "https://doi.org/10.1007/978-3-642-15705-9_10"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-30136-3_61", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023274353", 
              "https://doi.org/10.1007/978-3-540-30136-3_61"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-30136-3_61", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023274353", 
              "https://doi.org/10.1007/978-3-540-30136-3_61"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.pbiomolbio.2010.09.014", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035104385"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tpami.2010.46", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061743964"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/miar.2001.930258", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094816564"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1017/cbo9780511996504", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1098776139"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2016", 
        "datePublishedReg": "2016-01-01", 
        "description": "Image guidance and the visualization of sub surface structures during laparoscopic procedures have the potential to change the current capabilities of surgery. Increased target localization accuracy and the identification of critical structures can reduce resection mar-gins, procedure time and tissue trauma while simplifying procedures and enabling new functional capabilities. Image guidance requires the registration of 3D images to the laparoscopic video. Tissue deformation and lack of cross modality landmarks make this challenging. Registration can be performed by aligning the 3D image to a surface reconstructed from stereo laparoscopic images. Current research is focused on creating more generic stereo reconstruction techniques and rigid registration methods. This paper proposes a novel stereo reconstruction approach which exploits prior knowledge of patient specific organ models and outlier robust non rigid registration. The approach is validated on phantom data and the practical application of the reconstruction is demonstrated on in vivo data.", 
        "editor": [
          {
            "familyName": "Luo", 
            "givenName": "Xiongbiao", 
            "type": "Person"
          }, 
          {
            "familyName": "Reichl", 
            "givenName": "Tobias", 
            "type": "Person"
          }, 
          {
            "familyName": "Reiter", 
            "givenName": "Austin", 
            "type": "Person"
          }, 
          {
            "familyName": "Mariottini", 
            "givenName": "Gian-Luca", 
            "type": "Person"
          }
        ], 
        "genre": "chapter", 
        "id": "sg:pub.10.1007/978-3-319-29965-5_11", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": {
          "isbn": [
            "978-3-319-29964-8", 
            "978-3-319-29965-5"
          ], 
          "name": "Computer-Assisted and Robotic Endoscopy", 
          "type": "Book"
        }, 
        "name": "Non Rigid Registration of 3D Images to Laparoscopic Video for Image Guided Surgery", 
        "pagination": "109-116", 
        "productId": [
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/978-3-319-29965-5_11"
            ]
          }, 
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "c232c658784be08834915c2b8a2136c2358bae9378f40c5cf216dbd48225951c"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1040767189"
            ]
          }
        ], 
        "publisher": {
          "location": "Cham", 
          "name": "Springer International Publishing", 
          "type": "Organisation"
        }, 
        "sameAs": [
          "https://doi.org/10.1007/978-3-319-29965-5_11", 
          "https://app.dimensions.ai/details/publication/pub.1040767189"
        ], 
        "sdDataset": "chapters", 
        "sdDatePublished": "2019-04-15T19:14", 
        "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_8684_00000291.jsonl", 
        "type": "Chapter", 
        "url": "http://link.springer.com/10.1007/978-3-319-29965-5_11"
      }
    ]
     

    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.10.1007/978-3-319-29965-5_11'

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

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-29965-5_11'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-29965-5_11'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-29965-5_11'


     

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

    149 TRIPLES      23 PREDICATES      40 URIs      20 LITERALS      8 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/978-3-319-29965-5_11 schema:about anzsrc-for:08
    2 anzsrc-for:0801
    3 schema:author Nca603fda9b0c4dcba59ee08b13d6d8c1
    4 schema:citation sg:pub.10.1007/978-3-540-30136-3_61
    5 sg:pub.10.1007/978-3-540-85990-1_82
    6 sg:pub.10.1007/978-3-642-15705-9_10
    7 sg:pub.10.1007/978-3-642-15705-9_31
    8 sg:pub.10.1007/978-3-642-15705-9_34
    9 sg:pub.10.1007/978-3-642-30618-1_1
    10 https://doi.org/10.1016/j.pbiomolbio.2010.09.014
    11 https://doi.org/10.1016/j.urology.2008.11.040
    12 https://doi.org/10.1017/cbo9780511996504
    13 https://doi.org/10.1109/miar.2001.930258
    14 https://doi.org/10.1109/tpami.2010.46
    15 https://doi.org/10.1117/12.911994
    16 https://doi.org/10.1146/annurev-bioeng-071910-124757
    17 schema:datePublished 2016
    18 schema:datePublishedReg 2016-01-01
    19 schema:description Image guidance and the visualization of sub surface structures during laparoscopic procedures have the potential to change the current capabilities of surgery. Increased target localization accuracy and the identification of critical structures can reduce resection mar-gins, procedure time and tissue trauma while simplifying procedures and enabling new functional capabilities. Image guidance requires the registration of 3D images to the laparoscopic video. Tissue deformation and lack of cross modality landmarks make this challenging. Registration can be performed by aligning the 3D image to a surface reconstructed from stereo laparoscopic images. Current research is focused on creating more generic stereo reconstruction techniques and rigid registration methods. This paper proposes a novel stereo reconstruction approach which exploits prior knowledge of patient specific organ models and outlier robust non rigid registration. The approach is validated on phantom data and the practical application of the reconstruction is demonstrated on in vivo data.
    20 schema:editor N6b6be22ff65a40f8933132da0d35505a
    21 schema:genre chapter
    22 schema:inLanguage en
    23 schema:isAccessibleForFree false
    24 schema:isPartOf N96f362568eb04cb0b7c28f90a6a13af8
    25 schema:name Non Rigid Registration of 3D Images to Laparoscopic Video for Image Guided Surgery
    26 schema:pagination 109-116
    27 schema:productId Nc5baa781a49245e0968f550c69040c6c
    28 Nd9ea602615fd490d989e4051672a6623
    29 Nfb479754ace94c7db707bccad3b49ba2
    30 schema:publisher N705470d293634fa6b200950707e09b10
    31 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040767189
    32 https://doi.org/10.1007/978-3-319-29965-5_11
    33 schema:sdDatePublished 2019-04-15T19:14
    34 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    35 schema:sdPublisher N48bbf31fe4ab4cd583d24f7535e785e2
    36 schema:url http://link.springer.com/10.1007/978-3-319-29965-5_11
    37 sgo:license sg:explorer/license/
    38 sgo:sdDataset chapters
    39 rdf:type schema:Chapter
    40 N0e9cfb22967647459e92246b92b9552d schema:name Siemens Corporate Research
    41 rdf:type schema:Organization
    42 N1beca829ee0748be8e0a57b1cc653616 schema:name Siemens Corporate Research
    43 rdf:type schema:Organization
    44 N408114ecf68f42eeaca7907ae72147a9 schema:familyName Mariottini
    45 schema:givenName Gian-Luca
    46 rdf:type schema:Person
    47 N40e82b09b57e422a8b219f51ea63440a rdf:first N9b1ee924a9764afc824d6f8aa82d8ebf
    48 rdf:rest Na233f22f9f654d13843e9b273f7f3be0
    49 N480695d383da427898ee1adfe6357f1b rdf:first N408114ecf68f42eeaca7907ae72147a9
    50 rdf:rest rdf:nil
    51 N48bbf31fe4ab4cd583d24f7535e785e2 schema:name Springer Nature - SN SciGraph project
    52 rdf:type schema:Organization
    53 N5d8c33018f3142bfbdb648ffc8c6ddbe schema:name Siemens Corporate Research
    54 rdf:type schema:Organization
    55 N6b6be22ff65a40f8933132da0d35505a rdf:first Nb2dec28d8c78443089248dd72471cd27
    56 rdf:rest N40e82b09b57e422a8b219f51ea63440a
    57 N705470d293634fa6b200950707e09b10 schema:location Cham
    58 schema:name Springer International Publishing
    59 rdf:type schema:Organisation
    60 N7d1c2a399a81405d924d2fb7d1be7c24 rdf:first sg:person.0702376130.54
    61 rdf:rest rdf:nil
    62 N87d1d370ad3f43bbb5ebf34741fbb03a schema:affiliation N1beca829ee0748be8e0a57b1cc653616
    63 schema:familyName Kapoor
    64 schema:givenName Ankur
    65 rdf:type schema:Person
    66 N96f362568eb04cb0b7c28f90a6a13af8 schema:isbn 978-3-319-29964-8
    67 978-3-319-29965-5
    68 schema:name Computer-Assisted and Robotic Endoscopy
    69 rdf:type schema:Book
    70 N9b1ee924a9764afc824d6f8aa82d8ebf schema:familyName Reichl
    71 schema:givenName Tobias
    72 rdf:type schema:Person
    73 Na233f22f9f654d13843e9b273f7f3be0 rdf:first Neaffa62e238e45a396fd489fb61ce4a9
    74 rdf:rest N480695d383da427898ee1adfe6357f1b
    75 Nb2dec28d8c78443089248dd72471cd27 schema:familyName Luo
    76 schema:givenName Xiongbiao
    77 rdf:type schema:Person
    78 Nb3a198d41de14802a6326ede6e56dbf7 schema:affiliation N0e9cfb22967647459e92246b92b9552d
    79 schema:familyName Allan
    80 schema:givenName Max
    81 rdf:type schema:Person
    82 Nc5baa781a49245e0968f550c69040c6c schema:name doi
    83 schema:value 10.1007/978-3-319-29965-5_11
    84 rdf:type schema:PropertyValue
    85 Nca603fda9b0c4dcba59ee08b13d6d8c1 rdf:first Nb3a198d41de14802a6326ede6e56dbf7
    86 rdf:rest Nedb2e0e0f9034dd3a3e75ca152e9e90d
    87 Nd9ea602615fd490d989e4051672a6623 schema:name dimensions_id
    88 schema:value pub.1040767189
    89 rdf:type schema:PropertyValue
    90 Neaffa62e238e45a396fd489fb61ce4a9 schema:familyName Reiter
    91 schema:givenName Austin
    92 rdf:type schema:Person
    93 Nedb2e0e0f9034dd3a3e75ca152e9e90d rdf:first N87d1d370ad3f43bbb5ebf34741fbb03a
    94 rdf:rest Nf93ca2d626ba4c5c995efe4895d1381d
    95 Nefeb1d74d04b40ffa5bb7e29d866a32e schema:name Siemens Healthcare
    96 rdf:type schema:Organization
    97 Nf93ca2d626ba4c5c995efe4895d1381d rdf:first sg:person.013200653273.40
    98 rdf:rest N7d1c2a399a81405d924d2fb7d1be7c24
    99 Nfb479754ace94c7db707bccad3b49ba2 schema:name readcube_id
    100 schema:value c232c658784be08834915c2b8a2136c2358bae9378f40c5cf216dbd48225951c
    101 rdf:type schema:PropertyValue
    102 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
    103 schema:name Information and Computing Sciences
    104 rdf:type schema:DefinedTerm
    105 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
    106 schema:name Artificial Intelligence and Image Processing
    107 rdf:type schema:DefinedTerm
    108 sg:person.013200653273.40 schema:affiliation Nefeb1d74d04b40ffa5bb7e29d866a32e
    109 schema:familyName Mewes
    110 schema:givenName Philip
    111 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013200653273.40
    112 rdf:type schema:Person
    113 sg:person.0702376130.54 schema:affiliation N5d8c33018f3142bfbdb648ffc8c6ddbe
    114 schema:familyName Mountney
    115 schema:givenName Peter
    116 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0702376130.54
    117 rdf:type schema:Person
    118 sg:pub.10.1007/978-3-540-30136-3_61 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023274353
    119 https://doi.org/10.1007/978-3-540-30136-3_61
    120 rdf:type schema:CreativeWork
    121 sg:pub.10.1007/978-3-540-85990-1_82 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003815683
    122 https://doi.org/10.1007/978-3-540-85990-1_82
    123 rdf:type schema:CreativeWork
    124 sg:pub.10.1007/978-3-642-15705-9_10 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021700413
    125 https://doi.org/10.1007/978-3-642-15705-9_10
    126 rdf:type schema:CreativeWork
    127 sg:pub.10.1007/978-3-642-15705-9_31 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000754864
    128 https://doi.org/10.1007/978-3-642-15705-9_31
    129 rdf:type schema:CreativeWork
    130 sg:pub.10.1007/978-3-642-15705-9_34 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011146145
    131 https://doi.org/10.1007/978-3-642-15705-9_34
    132 rdf:type schema:CreativeWork
    133 sg:pub.10.1007/978-3-642-30618-1_1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014777228
    134 https://doi.org/10.1007/978-3-642-30618-1_1
    135 rdf:type schema:CreativeWork
    136 https://doi.org/10.1016/j.pbiomolbio.2010.09.014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035104385
    137 rdf:type schema:CreativeWork
    138 https://doi.org/10.1016/j.urology.2008.11.040 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016366600
    139 rdf:type schema:CreativeWork
    140 https://doi.org/10.1017/cbo9780511996504 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098776139
    141 rdf:type schema:CreativeWork
    142 https://doi.org/10.1109/miar.2001.930258 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094816564
    143 rdf:type schema:CreativeWork
    144 https://doi.org/10.1109/tpami.2010.46 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061743964
    145 rdf:type schema:CreativeWork
    146 https://doi.org/10.1117/12.911994 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019909984
    147 rdf:type schema:CreativeWork
    148 https://doi.org/10.1146/annurev-bioeng-071910-124757 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010713116
    149 rdf:type schema:CreativeWork
     




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


    ...