Surgical Task and Skill Classification from Eye Tracking and Tool Motion in Minimally Invasive Surgery View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2010

AUTHORS

Narges Ahmidi , Gregory D. Hager , Lisa Ishii , Gabor Fichtinger , Gary L. Gallia , Masaru Ishii

ABSTRACT

In the context of minimally invasive surgery, clinical risks are highly associated with surgeons' skill in manipulating surgical tools and their knowledge of the closed anatomy. A quantitative surgical skill assessment can reduce faulty procedures and prevent some surgical risks. In this paper focusing on sinus surgery, we present two methods to identify both skill level and task type by recording motion data of surgical tools as well as the surgeon's eye gaze location on the screen. We generate a total of 14 discrete Hidden Markov Models for seven surgical tasks at both expert and novice levels using a repeated k-fold evaluation method. The dataset contains 95 expert and 139 novice trials of surgery over a cadaver. The results reveal two insights: eye-gaze data contains skill related structures; and adding this info to the surgical tool motion data improves skill assessment by 13.2% and 5.3% for expert and novice levels, respectively. The proposed system quantifies surgeon's skill level with an accuracy of 82.5% and surgical task type of 77.8%. More... »

PAGES

295-302

References to SciGraph publications

  • 2009. Data-Derived Models for Segmentation with Application to Surgical Assessment and Training in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION – MICCAI 2009
  • 2004. A Study of Saccade Transition for Attention Segregation and Task Strategy in Laparoscopic Surgery in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION – MICCAI 2004
  • 2009. Task versus Subtask Surgical Skill Evaluation of Robotic Minimally Invasive Surgery in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION – MICCAI 2009
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-642-15711-0_37

    DOI

    http://dx.doi.org/10.1007/978-3-642-15711-0_37

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1026966987

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/20879412


    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/2008/1103", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Clinical Sciences", 
            "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"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Clinical Competence", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Eye Movements", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Humans", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Image Interpretation, Computer-Assisted", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Minimally Invasive Surgical Procedures", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Surgical Instruments", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Task Performance and Analysis", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Queen's University", 
              "id": "https://www.grid.ac/institutes/grid.410356.5", 
              "name": [
                "Queen\u2019s University, K7L3N6, Kingston, ON, Canada"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Ahmidi", 
            "givenName": "Narges", 
            "id": "sg:person.01265544074.16", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01265544074.16"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University", 
              "id": "https://www.grid.ac/institutes/grid.21107.35", 
              "name": [
                "Johns Hopkins University, 21211, Baltimore, MD"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Hager", 
            "givenName": "Gregory D.", 
            "id": "sg:person.0727264574.79", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0727264574.79"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University", 
              "id": "https://www.grid.ac/institutes/grid.21107.35", 
              "name": [
                "Johns Hopkins Medical Institutions, 21287, Baltimore, MD"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Ishii", 
            "givenName": "Lisa", 
            "id": "sg:person.01152710166.83", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01152710166.83"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Queen's University", 
              "id": "https://www.grid.ac/institutes/grid.410356.5", 
              "name": [
                "Queen\u2019s University, K7L3N6, Kingston, ON, Canada"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Fichtinger", 
            "givenName": "Gabor", 
            "id": "sg:person.01001154535.47", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01001154535.47"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University", 
              "id": "https://www.grid.ac/institutes/grid.21107.35", 
              "name": [
                "Department of Neurosurgery, Johns Hopkins University School of Medicine, 21287, Baltimore, MD"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Gallia", 
            "givenName": "Gary L.", 
            "id": "sg:person.01354145322.15", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01354145322.15"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University", 
              "id": "https://www.grid.ac/institutes/grid.21107.35", 
              "name": [
                "Johns Hopkins Medical Institutions, 21287, Baltimore, MD"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Ishii", 
            "givenName": "Masaru", 
            "id": "sg:person.0722233166.49", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0722233166.49"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1016/j.amjsurg.2007.01.022", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001183975"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-30136-3_13", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010437126", 
              "https://doi.org/10.1007/978-3-540-30136-3_13"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-30136-3_13", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010437126", 
              "https://doi.org/10.1007/978-3-540-30136-3_13"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-04268-3_54", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033230823", 
              "https://doi.org/10.1007/978-3-642-04268-3_54"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-04268-3_53", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037658876", 
              "https://doi.org/10.1007/978-3-642-04268-3_53"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1162/jocn.2009.21106", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039352427"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/10929080600989189", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1058378000"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/10929080701730979", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1058378048"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tbme.2005.869771", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061526582"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/iccvw.2009.5457648", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093909166"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2010", 
        "datePublishedReg": "2010-01-01", 
        "description": "In the context of minimally invasive surgery, clinical risks are highly associated with surgeons' skill in manipulating surgical tools and their knowledge of the closed anatomy. A quantitative surgical skill assessment can reduce faulty procedures and prevent some surgical risks. In this paper focusing on sinus surgery, we present two methods to identify both skill level and task type by recording motion data of surgical tools as well as the surgeon's eye gaze location on the screen. We generate a total of 14 discrete Hidden Markov Models for seven surgical tasks at both expert and novice levels using a repeated k-fold evaluation method. The dataset contains 95 expert and 139 novice trials of surgery over a cadaver. The results reveal two insights: eye-gaze data contains skill related structures; and adding this info to the surgical tool motion data improves skill assessment by 13.2% and 5.3% for expert and novice levels, respectively. The proposed system quantifies surgeon's skill level with an accuracy of 82.5% and surgical task type of 77.8%.", 
        "editor": [
          {
            "familyName": "Jiang", 
            "givenName": "Tianzi", 
            "type": "Person"
          }, 
          {
            "familyName": "Navab", 
            "givenName": "Nassir", 
            "type": "Person"
          }, 
          {
            "familyName": "Pluim", 
            "givenName": "Josien P. W.", 
            "type": "Person"
          }, 
          {
            "familyName": "Viergever", 
            "givenName": "Max A.", 
            "type": "Person"
          }
        ], 
        "genre": "chapter", 
        "id": "sg:pub.10.1007/978-3-642-15711-0_37", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.2478477", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": {
          "isbn": [
            "978-3-642-15710-3", 
            "978-3-642-15711-0"
          ], 
          "name": "Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2010", 
          "type": "Book"
        }, 
        "name": "Surgical Task and Skill Classification from Eye Tracking and Tool Motion in Minimally Invasive Surgery", 
        "pagination": "295-302", 
        "productId": [
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "20879412"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1026966987"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/978-3-642-15711-0_37"
            ]
          }, 
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "8076e08cb8649146d24ca3e53d4b276f49011ef705d4112e88abd9e58b7c1781"
            ]
          }
        ], 
        "publisher": {
          "location": "Berlin, Heidelberg", 
          "name": "Springer Berlin Heidelberg", 
          "type": "Organisation"
        }, 
        "sameAs": [
          "https://doi.org/10.1007/978-3-642-15711-0_37", 
          "https://app.dimensions.ai/details/publication/pub.1026966987"
        ], 
        "sdDataset": "chapters", 
        "sdDatePublished": "2019-04-16T08:27", 
        "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/v90/0000000363_0000000363/records_70061_00000001.jsonl", 
        "type": "Chapter", 
        "url": "https://link.springer.com/10.1007%2F978-3-642-15711-0_37"
      }
    ]
     

    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.10.1007/978-3-642-15711-0_37'

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

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-15711-0_37'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-15711-0_37'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-15711-0_37'


     

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

    184 TRIPLES      23 PREDICATES      44 URIs      28 LITERALS      16 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/978-3-642-15711-0_37 schema:about N012339d250a446f490a9025de5df8e31
    2 N6f2c601c694543ed9a1d5a040f262d35
    3 N9e63f47ab51e4e00bc88c36c260256f1
    4 N9f6ee2a43eb24491a76dbf8d9e559a4e
    5 Na5034a11e6584bfd9009a003f040024f
    6 Nce3eb1b000024ecf878b5c3687a5115c
    7 Neaab6df1dfb34be88e582951223995f4
    8 anzsrc-for:11
    9 anzsrc-for:1103
    10 schema:author N49883043994b4d558170693e1a04f6bf
    11 schema:citation sg:pub.10.1007/978-3-540-30136-3_13
    12 sg:pub.10.1007/978-3-642-04268-3_53
    13 sg:pub.10.1007/978-3-642-04268-3_54
    14 https://doi.org/10.1016/j.amjsurg.2007.01.022
    15 https://doi.org/10.1080/10929080600989189
    16 https://doi.org/10.1080/10929080701730979
    17 https://doi.org/10.1109/iccvw.2009.5457648
    18 https://doi.org/10.1109/tbme.2005.869771
    19 https://doi.org/10.1162/jocn.2009.21106
    20 schema:datePublished 2010
    21 schema:datePublishedReg 2010-01-01
    22 schema:description In the context of minimally invasive surgery, clinical risks are highly associated with surgeons' skill in manipulating surgical tools and their knowledge of the closed anatomy. A quantitative surgical skill assessment can reduce faulty procedures and prevent some surgical risks. In this paper focusing on sinus surgery, we present two methods to identify both skill level and task type by recording motion data of surgical tools as well as the surgeon's eye gaze location on the screen. We generate a total of 14 discrete Hidden Markov Models for seven surgical tasks at both expert and novice levels using a repeated k-fold evaluation method. The dataset contains 95 expert and 139 novice trials of surgery over a cadaver. The results reveal two insights: eye-gaze data contains skill related structures; and adding this info to the surgical tool motion data improves skill assessment by 13.2% and 5.3% for expert and novice levels, respectively. The proposed system quantifies surgeon's skill level with an accuracy of 82.5% and surgical task type of 77.8%.
    23 schema:editor N4d3b1f25f1ed463fa8fea017b76b63c3
    24 schema:genre chapter
    25 schema:inLanguage en
    26 schema:isAccessibleForFree true
    27 schema:isPartOf N35d89f6878614402947fe913dcce1419
    28 schema:name Surgical Task and Skill Classification from Eye Tracking and Tool Motion in Minimally Invasive Surgery
    29 schema:pagination 295-302
    30 schema:productId N1ab138c0ec924f2c98b8303c833065f6
    31 N6ddc28922bfc439684bda527da5e7de4
    32 Na24fe0c72138464fa4795a5abdefa335
    33 Nf52bda515e56469b9713d4c72219ee26
    34 schema:publisher Nd7fdc81d10744c79b00d25c60b812601
    35 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026966987
    36 https://doi.org/10.1007/978-3-642-15711-0_37
    37 schema:sdDatePublished 2019-04-16T08:27
    38 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    39 schema:sdPublisher N06d2d69b5a7f454498ba925bd2dcc349
    40 schema:url https://link.springer.com/10.1007%2F978-3-642-15711-0_37
    41 sgo:license sg:explorer/license/
    42 sgo:sdDataset chapters
    43 rdf:type schema:Chapter
    44 N012339d250a446f490a9025de5df8e31 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    45 schema:name Eye Movements
    46 rdf:type schema:DefinedTerm
    47 N06d2d69b5a7f454498ba925bd2dcc349 schema:name Springer Nature - SN SciGraph project
    48 rdf:type schema:Organization
    49 N0852cfda99854ca08dbec4483cf02f29 rdf:first sg:person.01354145322.15
    50 rdf:rest N2b9816294f4b4eaaa9414b7160020b45
    51 N1396a250abf44b6db1dac6747b1a833f rdf:first sg:person.0727264574.79
    52 rdf:rest Na61f27b724f64d81a57bb3e74e987b48
    53 N1a8bda2c1b0941d3bff2185b86661b28 rdf:first N6f62c391bee8492ab8dd13e9cc69446a
    54 rdf:rest N2b11f22cc8f1444aaae41c030a43178a
    55 N1ab138c0ec924f2c98b8303c833065f6 schema:name pubmed_id
    56 schema:value 20879412
    57 rdf:type schema:PropertyValue
    58 N2b11f22cc8f1444aaae41c030a43178a rdf:first Nd739c585b3ca4e15896a9ded0c0219f6
    59 rdf:rest rdf:nil
    60 N2b9816294f4b4eaaa9414b7160020b45 rdf:first sg:person.0722233166.49
    61 rdf:rest rdf:nil
    62 N3288f09236c0402991f76fa2303f3732 rdf:first Nde4e6f35bf2d4c0bab032a7f56d4d6cc
    63 rdf:rest N1a8bda2c1b0941d3bff2185b86661b28
    64 N35d89f6878614402947fe913dcce1419 schema:isbn 978-3-642-15710-3
    65 978-3-642-15711-0
    66 schema:name Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010
    67 rdf:type schema:Book
    68 N49883043994b4d558170693e1a04f6bf rdf:first sg:person.01265544074.16
    69 rdf:rest N1396a250abf44b6db1dac6747b1a833f
    70 N4d3b1f25f1ed463fa8fea017b76b63c3 rdf:first Ne16c25e83b434bfe81edd34575c10be5
    71 rdf:rest N3288f09236c0402991f76fa2303f3732
    72 N6ddc28922bfc439684bda527da5e7de4 schema:name dimensions_id
    73 schema:value pub.1026966987
    74 rdf:type schema:PropertyValue
    75 N6f2c601c694543ed9a1d5a040f262d35 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    76 schema:name Minimally Invasive Surgical Procedures
    77 rdf:type schema:DefinedTerm
    78 N6f62c391bee8492ab8dd13e9cc69446a schema:familyName Pluim
    79 schema:givenName Josien P. W.
    80 rdf:type schema:Person
    81 N9e63f47ab51e4e00bc88c36c260256f1 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    82 schema:name Surgical Instruments
    83 rdf:type schema:DefinedTerm
    84 N9f6ee2a43eb24491a76dbf8d9e559a4e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    85 schema:name Humans
    86 rdf:type schema:DefinedTerm
    87 Na24fe0c72138464fa4795a5abdefa335 schema:name doi
    88 schema:value 10.1007/978-3-642-15711-0_37
    89 rdf:type schema:PropertyValue
    90 Na5034a11e6584bfd9009a003f040024f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    91 schema:name Image Interpretation, Computer-Assisted
    92 rdf:type schema:DefinedTerm
    93 Na61f27b724f64d81a57bb3e74e987b48 rdf:first sg:person.01152710166.83
    94 rdf:rest Nc6f37001eac040b38b2b0fc74003553b
    95 Nc6f37001eac040b38b2b0fc74003553b rdf:first sg:person.01001154535.47
    96 rdf:rest N0852cfda99854ca08dbec4483cf02f29
    97 Nce3eb1b000024ecf878b5c3687a5115c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    98 schema:name Task Performance and Analysis
    99 rdf:type schema:DefinedTerm
    100 Nd739c585b3ca4e15896a9ded0c0219f6 schema:familyName Viergever
    101 schema:givenName Max A.
    102 rdf:type schema:Person
    103 Nd7fdc81d10744c79b00d25c60b812601 schema:location Berlin, Heidelberg
    104 schema:name Springer Berlin Heidelberg
    105 rdf:type schema:Organisation
    106 Nde4e6f35bf2d4c0bab032a7f56d4d6cc schema:familyName Navab
    107 schema:givenName Nassir
    108 rdf:type schema:Person
    109 Ne16c25e83b434bfe81edd34575c10be5 schema:familyName Jiang
    110 schema:givenName Tianzi
    111 rdf:type schema:Person
    112 Neaab6df1dfb34be88e582951223995f4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    113 schema:name Clinical Competence
    114 rdf:type schema:DefinedTerm
    115 Nf52bda515e56469b9713d4c72219ee26 schema:name readcube_id
    116 schema:value 8076e08cb8649146d24ca3e53d4b276f49011ef705d4112e88abd9e58b7c1781
    117 rdf:type schema:PropertyValue
    118 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
    119 schema:name Medical and Health Sciences
    120 rdf:type schema:DefinedTerm
    121 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
    122 schema:name Clinical Sciences
    123 rdf:type schema:DefinedTerm
    124 sg:grant.2478477 http://pending.schema.org/fundedItem sg:pub.10.1007/978-3-642-15711-0_37
    125 rdf:type schema:MonetaryGrant
    126 sg:person.01001154535.47 schema:affiliation https://www.grid.ac/institutes/grid.410356.5
    127 schema:familyName Fichtinger
    128 schema:givenName Gabor
    129 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01001154535.47
    130 rdf:type schema:Person
    131 sg:person.01152710166.83 schema:affiliation https://www.grid.ac/institutes/grid.21107.35
    132 schema:familyName Ishii
    133 schema:givenName Lisa
    134 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01152710166.83
    135 rdf:type schema:Person
    136 sg:person.01265544074.16 schema:affiliation https://www.grid.ac/institutes/grid.410356.5
    137 schema:familyName Ahmidi
    138 schema:givenName Narges
    139 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01265544074.16
    140 rdf:type schema:Person
    141 sg:person.01354145322.15 schema:affiliation https://www.grid.ac/institutes/grid.21107.35
    142 schema:familyName Gallia
    143 schema:givenName Gary L.
    144 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01354145322.15
    145 rdf:type schema:Person
    146 sg:person.0722233166.49 schema:affiliation https://www.grid.ac/institutes/grid.21107.35
    147 schema:familyName Ishii
    148 schema:givenName Masaru
    149 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0722233166.49
    150 rdf:type schema:Person
    151 sg:person.0727264574.79 schema:affiliation https://www.grid.ac/institutes/grid.21107.35
    152 schema:familyName Hager
    153 schema:givenName Gregory D.
    154 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0727264574.79
    155 rdf:type schema:Person
    156 sg:pub.10.1007/978-3-540-30136-3_13 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010437126
    157 https://doi.org/10.1007/978-3-540-30136-3_13
    158 rdf:type schema:CreativeWork
    159 sg:pub.10.1007/978-3-642-04268-3_53 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037658876
    160 https://doi.org/10.1007/978-3-642-04268-3_53
    161 rdf:type schema:CreativeWork
    162 sg:pub.10.1007/978-3-642-04268-3_54 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033230823
    163 https://doi.org/10.1007/978-3-642-04268-3_54
    164 rdf:type schema:CreativeWork
    165 https://doi.org/10.1016/j.amjsurg.2007.01.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001183975
    166 rdf:type schema:CreativeWork
    167 https://doi.org/10.1080/10929080600989189 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058378000
    168 rdf:type schema:CreativeWork
    169 https://doi.org/10.1080/10929080701730979 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058378048
    170 rdf:type schema:CreativeWork
    171 https://doi.org/10.1109/iccvw.2009.5457648 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093909166
    172 rdf:type schema:CreativeWork
    173 https://doi.org/10.1109/tbme.2005.869771 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061526582
    174 rdf:type schema:CreativeWork
    175 https://doi.org/10.1162/jocn.2009.21106 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039352427
    176 rdf:type schema:CreativeWork
    177 https://www.grid.ac/institutes/grid.21107.35 schema:alternateName Johns Hopkins University
    178 schema:name Department of Neurosurgery, Johns Hopkins University School of Medicine, 21287, Baltimore, MD
    179 Johns Hopkins Medical Institutions, 21287, Baltimore, MD
    180 Johns Hopkins University, 21211, Baltimore, MD
    181 rdf:type schema:Organization
    182 https://www.grid.ac/institutes/grid.410356.5 schema:alternateName Queen's University
    183 schema:name Queen’s University, K7L3N6, Kingston, ON, Canada
    184 rdf:type schema:Organization
     




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


    ...