Voxel-based statistical analysis of cerebral glucose metabolism in the rat cortical deafness model by 3D reconstruction of brain from autoradiographic ... View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2005-03-04

AUTHORS

Jae Sung Lee, Soon-Hyun Ahn, Dong Soo Lee, Seung Ha Oh, Chong Sun Kim, Jae Min Jeong, Kwang Suk Park, June-Key Chung, Myung Chul Lee

ABSTRACT

PurposeAnimal models of cortical deafness are essential for investigation of the cerebral glucose metabolism in congenital or prelingual deafness. Autoradiographic imaging is mainly used to assess the cerebral glucose metabolism in rodents. In this study, procedures for the 3D voxel-based statistical analysis of autoradiographic data were established to enable investigations of the within-modal and cross-modal plasticity through entire areas of the brain of sensory-deprived animals without lumping together heterogeneous subregions within each brain structure into a large region of interest.MethodsThirteen 2-[1-14C]-deoxy-D-glucose autoradiographic images were acquired from six deaf and seven age-matched normal rats (age 6–10 weeks). The deafness was induced by surgical ablation. For the 3D voxel-based statistical analysis, brain slices were extracted semiautomatically from the autoradiographic images, which contained the coronal sections of the brain, and were stacked into 3D volume data. Using principal axes matching and mutual information maximization algorithms, the adjacent coronal sections were co-registered using a rigid body transformation, and all sections were realigned to the first section. A study-specific template was composed and the realigned images were spatially normalized onto the template. Following count normalization, voxel-wise t tests were performed to reveal the areas with significant differences in cerebral glucose metabolism between the deaf and the control rats.ResultsContinuous and clear edges were detected in each image after registration between the coronal sections, and the internal and external landmarks extracted from the spatially normalized images were well matched, demonstrating the reliability of the spatial processing procedures. Voxel-wise t tests showed that the glucose metabolism in the bilateral auditory cortices of the deaf rats was significantly (P<0.001) lower than that in the controls. There was no significantly reduced metabolism in any other area, and no area showed a significant increase in metabolism in the deaf rats with the same threshold, demonstrating the high localization accuracy and specificity of the method developed in this study.ConclusionThis study established new procedures for the 3D reconstruction and voxel-based analysis of autoradiographic data which will be useful for examining the cerebral glucose metabolism in a rat cortical deafness model. More... »

PAGES

696-701

References to SciGraph publications

  • 2001-01. Cross-modal plasticity and cochlear implants in NATURE
  • 2002-06. Cross-modal plasticity: where and how? in NATURE REVIEWS NEUROSCIENCE
  • 2002-01. Molecular imaging of small animals with dedicated PET tomographs in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s00259-004-1739-y

    DOI

    http://dx.doi.org/10.1007/s00259-004-1739-y

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1006535553

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/15747156


    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/2008/11", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Medical and Health Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1109", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Neurosciences", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Algorithms", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Autoradiography", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Brain", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Deafness", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Fluorodeoxyglucose F18", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Glucose", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Image Interpretation, 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": "Models, Neurological", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Models, Statistical", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Radionuclide Imaging", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Radiopharmaceuticals", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Korea", 
              "id": "http://www.grid.ac/institutes/grid.31501.36", 
              "name": [
                "Department of Nuclear Medicine, Seoul National University College of Medicine, 28 Yungun-Dong, 110-799, Seoul, Chongno-Ku, Korea", 
                "Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Korea"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Lee", 
            "givenName": "Jae Sung", 
            "id": "sg:person.0677005044.62", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0677005044.62"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Otolaryngology, Head and Neck Surgery, Seoul National University College of Medicine, Seoul, Korea", 
              "id": "http://www.grid.ac/institutes/grid.31501.36", 
              "name": [
                "Department of Otolaryngology, Head and Neck Surgery, Seoul National University College of Medicine, Seoul, Korea"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Ahn", 
            "givenName": "Soon-Hyun", 
            "id": "sg:person.0724162325.77", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0724162325.77"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Nuclear Medicine, Seoul National University College of Medicine, 28 Yungun-Dong, 110-799, Seoul, Chongno-Ku, Korea", 
              "id": "http://www.grid.ac/institutes/grid.31501.36", 
              "name": [
                "Department of Nuclear Medicine, Seoul National University College of Medicine, 28 Yungun-Dong, 110-799, Seoul, Chongno-Ku, Korea"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Lee", 
            "givenName": "Dong Soo", 
            "id": "sg:person.015617314175.88", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015617314175.88"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Otolaryngology, Head and Neck Surgery, Seoul National University College of Medicine, Seoul, Korea", 
              "id": "http://www.grid.ac/institutes/grid.31501.36", 
              "name": [
                "Department of Otolaryngology, Head and Neck Surgery, Seoul National University College of Medicine, Seoul, Korea"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Oh", 
            "givenName": "Seung Ha", 
            "id": "sg:person.01061105660.11", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01061105660.11"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Otolaryngology, Head and Neck Surgery, Seoul National University College of Medicine, Seoul, Korea", 
              "id": "http://www.grid.ac/institutes/grid.31501.36", 
              "name": [
                "Department of Otolaryngology, Head and Neck Surgery, Seoul National University College of Medicine, Seoul, Korea"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Kim", 
            "givenName": "Chong Sun", 
            "id": "sg:person.0652066253.59", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0652066253.59"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Nuclear Medicine, Seoul National University College of Medicine, 28 Yungun-Dong, 110-799, Seoul, Chongno-Ku, Korea", 
              "id": "http://www.grid.ac/institutes/grid.31501.36", 
              "name": [
                "Department of Nuclear Medicine, Seoul National University College of Medicine, 28 Yungun-Dong, 110-799, Seoul, Chongno-Ku, Korea"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Jeong", 
            "givenName": "Jae Min", 
            "id": "sg:person.01301360400.94", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01301360400.94"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Korea", 
              "id": "http://www.grid.ac/institutes/grid.31501.36", 
              "name": [
                "Department of Nuclear Medicine, Seoul National University College of Medicine, 28 Yungun-Dong, 110-799, Seoul, Chongno-Ku, Korea", 
                "Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Korea"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Park", 
            "givenName": "Kwang Suk", 
            "id": "sg:person.07403351434.54", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07403351434.54"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Otolaryngology, Head and Neck Surgery, Seoul National University College of Medicine, Seoul, Korea", 
              "id": "http://www.grid.ac/institutes/grid.31501.36", 
              "name": [
                "Department of Otolaryngology, Head and Neck Surgery, Seoul National University College of Medicine, Seoul, Korea"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Chung", 
            "givenName": "June-Key", 
            "id": "sg:person.0751347234.39", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0751347234.39"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Otolaryngology, Head and Neck Surgery, Seoul National University College of Medicine, Seoul, Korea", 
              "id": "http://www.grid.ac/institutes/grid.31501.36", 
              "name": [
                "Department of Otolaryngology, Head and Neck Surgery, Seoul National University College of Medicine, Seoul, Korea"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Lee", 
            "givenName": "Myung Chul", 
            "id": "sg:person.01337220140.25", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01337220140.25"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/s00259-001-0683-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018614151", 
              "https://doi.org/10.1007/s00259-001-0683-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrn848", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046569768", 
              "https://doi.org/10.1038/nrn848"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/35051653", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050868757", 
              "https://doi.org/10.1038/35051653"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2005-03-04", 
        "datePublishedReg": "2005-03-04", 
        "description": "PurposeAnimal models of cortical deafness are essential for investigation of the cerebral glucose metabolism in congenital or prelingual deafness. Autoradiographic imaging is mainly used to assess the cerebral glucose metabolism in rodents. In this study, procedures for the 3D voxel-based statistical analysis of autoradiographic data were established to enable investigations of the within-modal and cross-modal plasticity through entire areas of the brain of sensory-deprived animals without lumping together heterogeneous subregions within each brain structure into a large region of interest.MethodsThirteen 2-[1-14C]-deoxy-D-glucose autoradiographic images were acquired from six deaf and seven age-matched normal rats (age 6\u201310\u00a0weeks). The deafness was induced by surgical ablation. For the 3D voxel-based statistical analysis, brain slices were extracted semiautomatically from the autoradiographic images, which contained the coronal sections of the brain, and were stacked into 3D volume data. Using principal axes matching and mutual information maximization algorithms, the adjacent coronal sections were co-registered using a rigid body transformation, and all sections were realigned to the first section. A study-specific template was composed and the realigned images were spatially normalized onto the template. Following count normalization, voxel-wise t tests were performed to reveal the areas with significant differences in cerebral glucose metabolism between the deaf and the control rats.ResultsContinuous and clear edges were detected in each image after registration between the coronal sections, and the internal and external landmarks extracted from the spatially normalized images were well matched, demonstrating the reliability of the spatial processing procedures. Voxel-wise t tests showed that the glucose metabolism in the bilateral auditory cortices of the deaf rats was significantly (P<0.001) lower than that in the controls. There was no significantly reduced metabolism in any other area, and no area showed a significant increase in metabolism in the deaf rats with the same threshold, demonstrating the high localization accuracy and specificity of the method developed in this study.ConclusionThis study established new procedures for the 3D reconstruction and voxel-based analysis of autoradiographic data which will be useful for examining the cerebral glucose metabolism in a rat cortical deafness model.", 
        "genre": "article", 
        "id": "sg:pub.10.1007/s00259-004-1739-y", 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1297401", 
            "issn": [
              "1619-7070", 
              "1619-7089"
            ], 
            "name": "European Journal of Nuclear Medicine and Molecular Imaging", 
            "publisher": "Springer Nature", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "6", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "32"
          }
        ], 
        "keywords": [
          "cerebral glucose metabolism", 
          "voxel-based statistical analysis", 
          "glucose metabolism", 
          "voxel-wise t-tests", 
          "coronal sections", 
          "deaf rats", 
          "deafness model", 
          "age-matched normal rats", 
          "adjacent coronal sections", 
          "cross-modal plasticity", 
          "autoradiographic images", 
          "t-test", 
          "autoradiographic data", 
          "bilateral auditory cortices", 
          "voxel-based analysis", 
          "PurposeAnimal models", 
          "cortical deafness", 
          "surgical ablation", 
          "normal rats", 
          "brain slices", 
          "auditory cortex", 
          "ConclusionThis study", 
          "study-specific template", 
          "autoradiographic imaging", 
          "statistical analysis", 
          "brain structures", 
          "count normalization", 
          "rats", 
          "prelingual deafness", 
          "brain", 
          "deafness", 
          "significant differences", 
          "significant increase", 
          "metabolism", 
          "external landmarks", 
          "heterogeneous subregions", 
          "cortex", 
          "mutual information maximization algorithm", 
          "study", 
          "rodents", 
          "procedure", 
          "control", 
          "same threshold", 
          "ablation", 
          "animals", 
          "test", 
          "imaging", 
          "slices", 
          "specificity", 
          "data", 
          "reconstruction", 
          "normalization", 
          "analysis", 
          "plasticity", 
          "differences", 
          "area", 
          "sections", 
          "subregions", 
          "increase", 
          "investigation", 
          "landmarks", 
          "voxels", 
          "threshold", 
          "registration", 
          "Deaf", 
          "new procedure", 
          "model", 
          "volume data", 
          "images", 
          "region", 
          "method", 
          "reliability", 
          "interest", 
          "information maximization algorithm", 
          "clear edges", 
          "first section", 
          "template", 
          "accuracy", 
          "body transformation", 
          "entire area", 
          "large regions", 
          "axes", 
          "processing procedures", 
          "transformation", 
          "rigid body transformation", 
          "structure", 
          "localization accuracy", 
          "edge", 
          "maximization algorithm", 
          "algorithm", 
          "modal", 
          "high localization accuracy", 
          "principal axes"
        ], 
        "name": "Voxel-based statistical analysis of cerebral glucose metabolism in the rat cortical deafness model by 3D reconstruction of brain from autoradiographic images", 
        "pagination": "696-701", 
        "productId": [
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1006535553"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s00259-004-1739-y"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "15747156"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s00259-004-1739-y", 
          "https://app.dimensions.ai/details/publication/pub.1006535553"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2022-10-01T06:33", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-springernature-scigraph/baseset/20221001/entities/gbq_results/article/article_410.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://doi.org/10.1007/s00259-004-1739-y"
      }
    ]
     

    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/s00259-004-1739-y'

    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/s00259-004-1739-y'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00259-004-1739-y'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00259-004-1739-y'


     

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

    274 TRIPLES      21 PREDICATES      133 URIs      122 LITERALS      19 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s00259-004-1739-y schema:about N046dc3b2f5a64539b9af97644130ae3b
    2 N08eabfbf72cf485cad9d9f130e71e45a
    3 N1ffae1d839024b8c872453b51b57f303
    4 N235d7192c4ed4ba6a4b77def9d2cda68
    5 N537d9f4c94274620a5032e9e7f2dae06
    6 N5e896a9dc73e46abb822e18eac7e986a
    7 N773b39ef44fd47ae937fe27e89b2b1aa
    8 N957e0f83b31a415695c1876949326a22
    9 N98d074e695e84e7084c12863ce5fa95e
    10 Na3e50f95323e439db246a9ef74b3465e
    11 Nbb62d14ab6344bb282204aafd97c7e0f
    12 Nf5705a0a4d6d4cdaadc8921074ca5532
    13 anzsrc-for:11
    14 anzsrc-for:1109
    15 schema:author N99f0c2af17634657bf4f016509953109
    16 schema:citation sg:pub.10.1007/s00259-001-0683-3
    17 sg:pub.10.1038/35051653
    18 sg:pub.10.1038/nrn848
    19 schema:datePublished 2005-03-04
    20 schema:datePublishedReg 2005-03-04
    21 schema:description PurposeAnimal models of cortical deafness are essential for investigation of the cerebral glucose metabolism in congenital or prelingual deafness. Autoradiographic imaging is mainly used to assess the cerebral glucose metabolism in rodents. In this study, procedures for the 3D voxel-based statistical analysis of autoradiographic data were established to enable investigations of the within-modal and cross-modal plasticity through entire areas of the brain of sensory-deprived animals without lumping together heterogeneous subregions within each brain structure into a large region of interest.MethodsThirteen 2-[1-14C]-deoxy-D-glucose autoradiographic images were acquired from six deaf and seven age-matched normal rats (age 6–10 weeks). The deafness was induced by surgical ablation. For the 3D voxel-based statistical analysis, brain slices were extracted semiautomatically from the autoradiographic images, which contained the coronal sections of the brain, and were stacked into 3D volume data. Using principal axes matching and mutual information maximization algorithms, the adjacent coronal sections were co-registered using a rigid body transformation, and all sections were realigned to the first section. A study-specific template was composed and the realigned images were spatially normalized onto the template. Following count normalization, voxel-wise t tests were performed to reveal the areas with significant differences in cerebral glucose metabolism between the deaf and the control rats.ResultsContinuous and clear edges were detected in each image after registration between the coronal sections, and the internal and external landmarks extracted from the spatially normalized images were well matched, demonstrating the reliability of the spatial processing procedures. Voxel-wise t tests showed that the glucose metabolism in the bilateral auditory cortices of the deaf rats was significantly (P<0.001) lower than that in the controls. There was no significantly reduced metabolism in any other area, and no area showed a significant increase in metabolism in the deaf rats with the same threshold, demonstrating the high localization accuracy and specificity of the method developed in this study.ConclusionThis study established new procedures for the 3D reconstruction and voxel-based analysis of autoradiographic data which will be useful for examining the cerebral glucose metabolism in a rat cortical deafness model.
    22 schema:genre article
    23 schema:isAccessibleForFree false
    24 schema:isPartOf Na80f09dfca6f4b78943ea00dbcb9fa40
    25 Ne04b8b8f0b434fde8fc9fe71fcd845b0
    26 sg:journal.1297401
    27 schema:keywords ConclusionThis study
    28 Deaf
    29 PurposeAnimal models
    30 ablation
    31 accuracy
    32 adjacent coronal sections
    33 age-matched normal rats
    34 algorithm
    35 analysis
    36 animals
    37 area
    38 auditory cortex
    39 autoradiographic data
    40 autoradiographic images
    41 autoradiographic imaging
    42 axes
    43 bilateral auditory cortices
    44 body transformation
    45 brain
    46 brain slices
    47 brain structures
    48 cerebral glucose metabolism
    49 clear edges
    50 control
    51 coronal sections
    52 cortex
    53 cortical deafness
    54 count normalization
    55 cross-modal plasticity
    56 data
    57 deaf rats
    58 deafness
    59 deafness model
    60 differences
    61 edge
    62 entire area
    63 external landmarks
    64 first section
    65 glucose metabolism
    66 heterogeneous subregions
    67 high localization accuracy
    68 images
    69 imaging
    70 increase
    71 information maximization algorithm
    72 interest
    73 investigation
    74 landmarks
    75 large regions
    76 localization accuracy
    77 maximization algorithm
    78 metabolism
    79 method
    80 modal
    81 model
    82 mutual information maximization algorithm
    83 new procedure
    84 normal rats
    85 normalization
    86 plasticity
    87 prelingual deafness
    88 principal axes
    89 procedure
    90 processing procedures
    91 rats
    92 reconstruction
    93 region
    94 registration
    95 reliability
    96 rigid body transformation
    97 rodents
    98 same threshold
    99 sections
    100 significant differences
    101 significant increase
    102 slices
    103 specificity
    104 statistical analysis
    105 structure
    106 study
    107 study-specific template
    108 subregions
    109 surgical ablation
    110 t-test
    111 template
    112 test
    113 threshold
    114 transformation
    115 volume data
    116 voxel-based analysis
    117 voxel-based statistical analysis
    118 voxel-wise t-tests
    119 voxels
    120 schema:name Voxel-based statistical analysis of cerebral glucose metabolism in the rat cortical deafness model by 3D reconstruction of brain from autoradiographic images
    121 schema:pagination 696-701
    122 schema:productId N83511101000c4235ac77c7a699cb16e3
    123 Nab66e111cd874e59858ab6b412c2573c
    124 Nc4d87e148c6846d7a87b72d7ffd01936
    125 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006535553
    126 https://doi.org/10.1007/s00259-004-1739-y
    127 schema:sdDatePublished 2022-10-01T06:33
    128 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    129 schema:sdPublisher N0509fb15f94d449d97232327fd51133f
    130 schema:url https://doi.org/10.1007/s00259-004-1739-y
    131 sgo:license sg:explorer/license/
    132 sgo:sdDataset articles
    133 rdf:type schema:ScholarlyArticle
    134 N046dc3b2f5a64539b9af97644130ae3b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    135 schema:name Algorithms
    136 rdf:type schema:DefinedTerm
    137 N0509fb15f94d449d97232327fd51133f schema:name Springer Nature - SN SciGraph project
    138 rdf:type schema:Organization
    139 N08eabfbf72cf485cad9d9f130e71e45a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    140 schema:name Models, Statistical
    141 rdf:type schema:DefinedTerm
    142 N1ffae1d839024b8c872453b51b57f303 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    143 schema:name Autoradiography
    144 rdf:type schema:DefinedTerm
    145 N235d7192c4ed4ba6a4b77def9d2cda68 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    146 schema:name Models, Neurological
    147 rdf:type schema:DefinedTerm
    148 N537d9f4c94274620a5032e9e7f2dae06 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    149 schema:name Radionuclide Imaging
    150 rdf:type schema:DefinedTerm
    151 N5e896a9dc73e46abb822e18eac7e986a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    152 schema:name Brain
    153 rdf:type schema:DefinedTerm
    154 N62e00dcf652c48468ee09fca1c3fd5be rdf:first sg:person.01061105660.11
    155 rdf:rest N95466a29374b400aac51bb8b7d0a4372
    156 N773b39ef44fd47ae937fe27e89b2b1aa schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    157 schema:name Fluorodeoxyglucose F18
    158 rdf:type schema:DefinedTerm
    159 N811f79f34da948f69c02f0830e986474 rdf:first sg:person.0751347234.39
    160 rdf:rest N9fb7e28bf9b2474d884b5acb635ae9e8
    161 N83511101000c4235ac77c7a699cb16e3 schema:name dimensions_id
    162 schema:value pub.1006535553
    163 rdf:type schema:PropertyValue
    164 N8b63e01ffb2a4e48b6accc8ceaaa9eb4 rdf:first sg:person.015617314175.88
    165 rdf:rest N62e00dcf652c48468ee09fca1c3fd5be
    166 N8f3eabd6462d4cbc8d55df5d939f3874 rdf:first sg:person.07403351434.54
    167 rdf:rest N811f79f34da948f69c02f0830e986474
    168 N95466a29374b400aac51bb8b7d0a4372 rdf:first sg:person.0652066253.59
    169 rdf:rest Nf5db924b9eb74508ac579d339f22b3c3
    170 N957e0f83b31a415695c1876949326a22 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    171 schema:name Glucose
    172 rdf:type schema:DefinedTerm
    173 N98d074e695e84e7084c12863ce5fa95e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    174 schema:name Deafness
    175 rdf:type schema:DefinedTerm
    176 N99f0c2af17634657bf4f016509953109 rdf:first sg:person.0677005044.62
    177 rdf:rest Nc4708838a5cc487b9229774ac1acc372
    178 N9fb7e28bf9b2474d884b5acb635ae9e8 rdf:first sg:person.01337220140.25
    179 rdf:rest rdf:nil
    180 Na3e50f95323e439db246a9ef74b3465e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    181 schema:name Imaging, Three-Dimensional
    182 rdf:type schema:DefinedTerm
    183 Na80f09dfca6f4b78943ea00dbcb9fa40 schema:volumeNumber 32
    184 rdf:type schema:PublicationVolume
    185 Nab66e111cd874e59858ab6b412c2573c schema:name doi
    186 schema:value 10.1007/s00259-004-1739-y
    187 rdf:type schema:PropertyValue
    188 Nbb62d14ab6344bb282204aafd97c7e0f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    189 schema:name Radiopharmaceuticals
    190 rdf:type schema:DefinedTerm
    191 Nc4708838a5cc487b9229774ac1acc372 rdf:first sg:person.0724162325.77
    192 rdf:rest N8b63e01ffb2a4e48b6accc8ceaaa9eb4
    193 Nc4d87e148c6846d7a87b72d7ffd01936 schema:name pubmed_id
    194 schema:value 15747156
    195 rdf:type schema:PropertyValue
    196 Ne04b8b8f0b434fde8fc9fe71fcd845b0 schema:issueNumber 6
    197 rdf:type schema:PublicationIssue
    198 Nf5705a0a4d6d4cdaadc8921074ca5532 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    199 schema:name Image Interpretation, Computer-Assisted
    200 rdf:type schema:DefinedTerm
    201 Nf5db924b9eb74508ac579d339f22b3c3 rdf:first sg:person.01301360400.94
    202 rdf:rest N8f3eabd6462d4cbc8d55df5d939f3874
    203 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
    204 schema:name Medical and Health Sciences
    205 rdf:type schema:DefinedTerm
    206 anzsrc-for:1109 schema:inDefinedTermSet anzsrc-for:
    207 schema:name Neurosciences
    208 rdf:type schema:DefinedTerm
    209 sg:journal.1297401 schema:issn 1619-7070
    210 1619-7089
    211 schema:name European Journal of Nuclear Medicine and Molecular Imaging
    212 schema:publisher Springer Nature
    213 rdf:type schema:Periodical
    214 sg:person.01061105660.11 schema:affiliation grid-institutes:grid.31501.36
    215 schema:familyName Oh
    216 schema:givenName Seung Ha
    217 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01061105660.11
    218 rdf:type schema:Person
    219 sg:person.01301360400.94 schema:affiliation grid-institutes:grid.31501.36
    220 schema:familyName Jeong
    221 schema:givenName Jae Min
    222 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01301360400.94
    223 rdf:type schema:Person
    224 sg:person.01337220140.25 schema:affiliation grid-institutes:grid.31501.36
    225 schema:familyName Lee
    226 schema:givenName Myung Chul
    227 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01337220140.25
    228 rdf:type schema:Person
    229 sg:person.015617314175.88 schema:affiliation grid-institutes:grid.31501.36
    230 schema:familyName Lee
    231 schema:givenName Dong Soo
    232 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015617314175.88
    233 rdf:type schema:Person
    234 sg:person.0652066253.59 schema:affiliation grid-institutes:grid.31501.36
    235 schema:familyName Kim
    236 schema:givenName Chong Sun
    237 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0652066253.59
    238 rdf:type schema:Person
    239 sg:person.0677005044.62 schema:affiliation grid-institutes:grid.31501.36
    240 schema:familyName Lee
    241 schema:givenName Jae Sung
    242 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0677005044.62
    243 rdf:type schema:Person
    244 sg:person.0724162325.77 schema:affiliation grid-institutes:grid.31501.36
    245 schema:familyName Ahn
    246 schema:givenName Soon-Hyun
    247 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0724162325.77
    248 rdf:type schema:Person
    249 sg:person.07403351434.54 schema:affiliation grid-institutes:grid.31501.36
    250 schema:familyName Park
    251 schema:givenName Kwang Suk
    252 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07403351434.54
    253 rdf:type schema:Person
    254 sg:person.0751347234.39 schema:affiliation grid-institutes:grid.31501.36
    255 schema:familyName Chung
    256 schema:givenName June-Key
    257 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0751347234.39
    258 rdf:type schema:Person
    259 sg:pub.10.1007/s00259-001-0683-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018614151
    260 https://doi.org/10.1007/s00259-001-0683-3
    261 rdf:type schema:CreativeWork
    262 sg:pub.10.1038/35051653 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050868757
    263 https://doi.org/10.1038/35051653
    264 rdf:type schema:CreativeWork
    265 sg:pub.10.1038/nrn848 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046569768
    266 https://doi.org/10.1038/nrn848
    267 rdf:type schema:CreativeWork
    268 grid-institutes:grid.31501.36 schema:alternateName Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Korea
    269 Department of Nuclear Medicine, Seoul National University College of Medicine, 28 Yungun-Dong, 110-799, Seoul, Chongno-Ku, Korea
    270 Department of Otolaryngology, Head and Neck Surgery, Seoul National University College of Medicine, Seoul, Korea
    271 schema:name Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Korea
    272 Department of Nuclear Medicine, Seoul National University College of Medicine, 28 Yungun-Dong, 110-799, Seoul, Chongno-Ku, Korea
    273 Department of Otolaryngology, Head and Neck Surgery, Seoul National University College of Medicine, Seoul, Korea
    274 rdf:type schema:Organization
     




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


    ...