Eigenshape Analysis of Left Ventricular Outlines from Contrast Ventriculograms View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

1996

AUTHORS

Paul D. Sampson , Fred L. Bookstein , Florence H. Sheehan , Edward L. Bolson

ABSTRACT

The left ventricle of the heart functions by contraction. From digitized outlines we analyze its function by describing its shape, shape change, and size change (or “ejection fraction”) over the cardiac cycle, from end diastole (ED) to end systole (ES). For this purpose we introduce a new variant of eigenshape analysis for the morphometric analysis of outline data. The method begins with a mean outline defined by pointwise averages of a sample of outlines after they have been oriented in a Procrustes superposition by means of an “iterative closest point” algorithm. Individual outlines are then represented by vectors of deviations normal to the mean outline, and variation in shape is analyzed in terms of a singular value decomposition (SVD) of a sample matrix of such deviations. Principal modes of variation in shape are given by so-called “eigenshapes”—the left singular vectors of the SVD. In application to the analysis of left ventricular outlines we compute an SVD for the joint representation of the outline shapes at both ED and ES. The results are discussed in terms of shape change. We use the scores on a subset of the principal eigenshapes to demonstrate a discriminant analysis distinguishing samples of “normals” from groups of clinical cases having either cardiomyopathy or infarcts associated with one of three types of coronary artery disease. We then discuss proposals for the morphometric analysis of two-dimensional outlines and three-dimensional surfaces that also include landmarks. These proposals integrate an eigenshape analysis with thin-plate spline based analyses of configurations of landmarks. More... »

PAGES

211-233

References to SciGraph publications

Book

TITLE

Advances in Morphometrics

ISBN

978-1-4757-9085-6
978-1-4757-9083-2

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-4757-9083-2_18

DOI

http://dx.doi.org/10.1007/978-1-4757-9083-2_18

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1001898664


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": {
          "name": [
            "Department of Statistics, University of Washington, Box 354322, Seattle, Washington\u00a098195-4322, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sampson", 
        "givenName": "Paul D.", 
        "id": "sg:person.0705727144.58", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0705727144.58"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Michigan\u2013Ann Arbor", 
          "id": "https://www.grid.ac/institutes/grid.214458.e", 
          "name": [
            "Institute of Gerontology, University of Michigan, Ann Arbor, Michigan\u00a048109-2007, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bookstein", 
        "givenName": "Fred L.", 
        "id": "sg:person.0611561377.45", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0611561377.45"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Washington", 
          "id": "https://www.grid.ac/institutes/grid.34477.33", 
          "name": [
            "Division of Cardiology, School of Medicine University of Washington, Box 356422, Seattle, Washington\u00a098195-6422, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sheehan", 
        "givenName": "Florence H.", 
        "id": "sg:person.01371202547.69", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01371202547.69"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Washington", 
          "id": "https://www.grid.ac/institutes/grid.34477.33", 
          "name": [
            "Division of Cardiology, School of Medicine University of Washington, Box 356422, Seattle, Washington\u00a098195-6422, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bolson", 
        "givenName": "Edward L.", 
        "id": "sg:person.0646101707.28", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0646101707.28"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/978-3-642-93093-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002495929", 
          "https://doi.org/10.1007/978-3-642-93093-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-93093-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002495929", 
          "https://doi.org/10.1007/978-3-642-93093-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0146-664x(82)90034-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003975878"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0735-1097(89)90504-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017177900"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01151436", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018278647", 
          "https://doi.org/10.1007/bf01151436"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01151436", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018278647", 
          "https://doi.org/10.1007/bf01151436"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0002-9149(91)90831-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027254534"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00899747", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029192736", 
          "https://doi.org/10.1007/bf00899747"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bfb0033764", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030399089", 
          "https://doi.org/10.1007/bfb0033764"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bfb0033764", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030399089", 
          "https://doi.org/10.1007/bfb0033764"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.cir.81.4.1161", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032601562"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1117/12.146610", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033965965"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01248355", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034100362", 
          "https://doi.org/10.1007/bf01248355"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01145320", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046398371", 
          "https://doi.org/10.1007/bf01145320"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02291478", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049977738", 
          "https://doi.org/10.1007/bf02291478"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02291478", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049977738", 
          "https://doi.org/10.1007/bf02291478"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01033230", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052341646", 
          "https://doi.org/10.1007/bf01033230"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/34.121791", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061155634"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/34.24792", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061155904"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tc.1972.5008949", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061531397"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/ss/1177013696", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064410204"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/2413076", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069921405"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/2992207", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1070161844"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/cbo9780511573064", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1098664430"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "1996", 
    "datePublishedReg": "1996-01-01", 
    "description": "The left ventricle of the heart functions by contraction. From digitized outlines we analyze its function by describing its shape, shape change, and size change (or \u201cejection fraction\u201d) over the cardiac cycle, from end diastole (ED) to end systole (ES). For this purpose we introduce a new variant of eigenshape analysis for the morphometric analysis of outline data. The method begins with a mean outline defined by pointwise averages of a sample of outlines after they have been oriented in a Procrustes superposition by means of an \u201citerative closest point\u201d algorithm. Individual outlines are then represented by vectors of deviations normal to the mean outline, and variation in shape is analyzed in terms of a singular value decomposition (SVD) of a sample matrix of such deviations. Principal modes of variation in shape are given by so-called \u201ceigenshapes\u201d\u2014the left singular vectors of the SVD. In application to the analysis of left ventricular outlines we compute an SVD for the joint representation of the outline shapes at both ED and ES. The results are discussed in terms of shape change. We use the scores on a subset of the principal eigenshapes to demonstrate a discriminant analysis distinguishing samples of \u201cnormals\u201d from groups of clinical cases having either cardiomyopathy or infarcts associated with one of three types of coronary artery disease. We then discuss proposals for the morphometric analysis of two-dimensional outlines and three-dimensional surfaces that also include landmarks. These proposals integrate an eigenshape analysis with thin-plate spline based analyses of configurations of landmarks.", 
    "editor": [
      {
        "familyName": "Marcus", 
        "givenName": "Leslie F.", 
        "type": "Person"
      }, 
      {
        "familyName": "Corti", 
        "givenName": "Marco", 
        "type": "Person"
      }, 
      {
        "familyName": "Loy", 
        "givenName": "Anna", 
        "type": "Person"
      }, 
      {
        "familyName": "Naylor", 
        "givenName": "Gavin J. P.", 
        "type": "Person"
      }, 
      {
        "familyName": "Slice", 
        "givenName": "Dennis E.", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-1-4757-9083-2_18", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-1-4757-9085-6", 
        "978-1-4757-9083-2"
      ], 
      "name": "Advances in Morphometrics", 
      "type": "Book"
    }, 
    "name": "Eigenshape Analysis of Left Ventricular Outlines from Contrast Ventriculograms", 
    "pagination": "211-233", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-1-4757-9083-2_18"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "090b5da6d25f2b86e97d7527db9f0b0ed7fc105024c97d6338b76c4f13ef1aa3"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1001898664"
        ]
      }
    ], 
    "publisher": {
      "location": "Boston, MA", 
      "name": "Springer US", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-1-4757-9083-2_18", 
      "https://app.dimensions.ai/details/publication/pub.1001898664"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-15T11:31", 
    "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_8660_00000244.jsonl", 
    "type": "Chapter", 
    "url": "http://link.springer.com/10.1007/978-1-4757-9083-2_18"
  }
]
 

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.10.1007/978-1-4757-9083-2_18'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-1-4757-9083-2_18'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-1-4757-9083-2_18'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-1-4757-9083-2_18'


 

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

179 TRIPLES      23 PREDICATES      47 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-1-4757-9083-2_18 schema:about anzsrc-for:11
2 anzsrc-for:1102
3 schema:author N5ced16aba7304f42bd14dc8a8857c34c
4 schema:citation sg:pub.10.1007/978-3-642-93093-5
5 sg:pub.10.1007/bf00899747
6 sg:pub.10.1007/bf01033230
7 sg:pub.10.1007/bf01145320
8 sg:pub.10.1007/bf01151436
9 sg:pub.10.1007/bf01248355
10 sg:pub.10.1007/bf02291478
11 sg:pub.10.1007/bfb0033764
12 https://doi.org/10.1016/0002-9149(91)90831-5
13 https://doi.org/10.1016/0146-664x(82)90034-x
14 https://doi.org/10.1016/0735-1097(89)90504-4
15 https://doi.org/10.1017/cbo9780511573064
16 https://doi.org/10.1109/34.121791
17 https://doi.org/10.1109/34.24792
18 https://doi.org/10.1109/tc.1972.5008949
19 https://doi.org/10.1117/12.146610
20 https://doi.org/10.1161/01.cir.81.4.1161
21 https://doi.org/10.1214/ss/1177013696
22 https://doi.org/10.2307/2413076
23 https://doi.org/10.2307/2992207
24 schema:datePublished 1996
25 schema:datePublishedReg 1996-01-01
26 schema:description The left ventricle of the heart functions by contraction. From digitized outlines we analyze its function by describing its shape, shape change, and size change (or “ejection fraction”) over the cardiac cycle, from end diastole (ED) to end systole (ES). For this purpose we introduce a new variant of eigenshape analysis for the morphometric analysis of outline data. The method begins with a mean outline defined by pointwise averages of a sample of outlines after they have been oriented in a Procrustes superposition by means of an “iterative closest point” algorithm. Individual outlines are then represented by vectors of deviations normal to the mean outline, and variation in shape is analyzed in terms of a singular value decomposition (SVD) of a sample matrix of such deviations. Principal modes of variation in shape are given by so-called “eigenshapes”—the left singular vectors of the SVD. In application to the analysis of left ventricular outlines we compute an SVD for the joint representation of the outline shapes at both ED and ES. The results are discussed in terms of shape change. We use the scores on a subset of the principal eigenshapes to demonstrate a discriminant analysis distinguishing samples of “normals” from groups of clinical cases having either cardiomyopathy or infarcts associated with one of three types of coronary artery disease. We then discuss proposals for the morphometric analysis of two-dimensional outlines and three-dimensional surfaces that also include landmarks. These proposals integrate an eigenshape analysis with thin-plate spline based analyses of configurations of landmarks.
27 schema:editor N2c879ccfe42144a69de79553ca8ff707
28 schema:genre chapter
29 schema:inLanguage en
30 schema:isAccessibleForFree false
31 schema:isPartOf Ncd03560bc47d4530b973e20b0002f852
32 schema:name Eigenshape Analysis of Left Ventricular Outlines from Contrast Ventriculograms
33 schema:pagination 211-233
34 schema:productId N46415b99f301466dbb01e5cb1d6ebc7d
35 Ne17dc3c2be9c4faa85f7497433877187
36 Necb822aaeb8e4bf4b7a11a28a18307c6
37 schema:publisher Nd31daf0d0293469783be7dd4b56a73df
38 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001898664
39 https://doi.org/10.1007/978-1-4757-9083-2_18
40 schema:sdDatePublished 2019-04-15T11:31
41 schema:sdLicense https://scigraph.springernature.com/explorer/license/
42 schema:sdPublisher N29f8655fc482478e972f2adcb4231000
43 schema:url http://link.springer.com/10.1007/978-1-4757-9083-2_18
44 sgo:license sg:explorer/license/
45 sgo:sdDataset chapters
46 rdf:type schema:Chapter
47 N1a6e43e199d94fbebcb8c958d59954d0 rdf:first sg:person.01371202547.69
48 rdf:rest Nc18d4667901f465f83f66caef851708e
49 N1f68a0aa2aef45bdba4c60633ce43f87 schema:name Department of Statistics, University of Washington, Box 354322, Seattle, Washington 98195-4322, USA
50 rdf:type schema:Organization
51 N29f8655fc482478e972f2adcb4231000 schema:name Springer Nature - SN SciGraph project
52 rdf:type schema:Organization
53 N2c879ccfe42144a69de79553ca8ff707 rdf:first Ne2c8a63f77574130b4f0ee7ec45d44cb
54 rdf:rest N937ad42ec1f34134be4088fb64a513a9
55 N2d99998844d8423582dc596081c435cb rdf:first N9bdd8c7272cc49759802a3920bbc0b60
56 rdf:rest Nb26f13d6f47445b89bccacec08047801
57 N46415b99f301466dbb01e5cb1d6ebc7d schema:name dimensions_id
58 schema:value pub.1001898664
59 rdf:type schema:PropertyValue
60 N5ced16aba7304f42bd14dc8a8857c34c rdf:first sg:person.0705727144.58
61 rdf:rest Ndc4174bb53164aa596156fa6f860b2a8
62 N659c3933f1c74aa1955986cc915a0926 schema:familyName Slice
63 schema:givenName Dennis E.
64 rdf:type schema:Person
65 N937ad42ec1f34134be4088fb64a513a9 rdf:first Nce57833e21804f80aaee5a411eda91fe
66 rdf:rest Ne41990d5e0a4484492ffdb5421ad2a71
67 N9bdd8c7272cc49759802a3920bbc0b60 schema:familyName Naylor
68 schema:givenName Gavin J. P.
69 rdf:type schema:Person
70 Na0febf6387d54be4af052252adc439e7 schema:familyName Loy
71 schema:givenName Anna
72 rdf:type schema:Person
73 Nb26f13d6f47445b89bccacec08047801 rdf:first N659c3933f1c74aa1955986cc915a0926
74 rdf:rest rdf:nil
75 Nc18d4667901f465f83f66caef851708e rdf:first sg:person.0646101707.28
76 rdf:rest rdf:nil
77 Ncd03560bc47d4530b973e20b0002f852 schema:isbn 978-1-4757-9083-2
78 978-1-4757-9085-6
79 schema:name Advances in Morphometrics
80 rdf:type schema:Book
81 Nce57833e21804f80aaee5a411eda91fe schema:familyName Corti
82 schema:givenName Marco
83 rdf:type schema:Person
84 Nd31daf0d0293469783be7dd4b56a73df schema:location Boston, MA
85 schema:name Springer US
86 rdf:type schema:Organisation
87 Ndc4174bb53164aa596156fa6f860b2a8 rdf:first sg:person.0611561377.45
88 rdf:rest N1a6e43e199d94fbebcb8c958d59954d0
89 Ne17dc3c2be9c4faa85f7497433877187 schema:name doi
90 schema:value 10.1007/978-1-4757-9083-2_18
91 rdf:type schema:PropertyValue
92 Ne2c8a63f77574130b4f0ee7ec45d44cb schema:familyName Marcus
93 schema:givenName Leslie F.
94 rdf:type schema:Person
95 Ne41990d5e0a4484492ffdb5421ad2a71 rdf:first Na0febf6387d54be4af052252adc439e7
96 rdf:rest N2d99998844d8423582dc596081c435cb
97 Necb822aaeb8e4bf4b7a11a28a18307c6 schema:name readcube_id
98 schema:value 090b5da6d25f2b86e97d7527db9f0b0ed7fc105024c97d6338b76c4f13ef1aa3
99 rdf:type schema:PropertyValue
100 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
101 schema:name Medical and Health Sciences
102 rdf:type schema:DefinedTerm
103 anzsrc-for:1102 schema:inDefinedTermSet anzsrc-for:
104 schema:name Cardiorespiratory Medicine and Haematology
105 rdf:type schema:DefinedTerm
106 sg:person.01371202547.69 schema:affiliation https://www.grid.ac/institutes/grid.34477.33
107 schema:familyName Sheehan
108 schema:givenName Florence H.
109 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01371202547.69
110 rdf:type schema:Person
111 sg:person.0611561377.45 schema:affiliation https://www.grid.ac/institutes/grid.214458.e
112 schema:familyName Bookstein
113 schema:givenName Fred L.
114 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0611561377.45
115 rdf:type schema:Person
116 sg:person.0646101707.28 schema:affiliation https://www.grid.ac/institutes/grid.34477.33
117 schema:familyName Bolson
118 schema:givenName Edward L.
119 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0646101707.28
120 rdf:type schema:Person
121 sg:person.0705727144.58 schema:affiliation N1f68a0aa2aef45bdba4c60633ce43f87
122 schema:familyName Sampson
123 schema:givenName Paul D.
124 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0705727144.58
125 rdf:type schema:Person
126 sg:pub.10.1007/978-3-642-93093-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002495929
127 https://doi.org/10.1007/978-3-642-93093-5
128 rdf:type schema:CreativeWork
129 sg:pub.10.1007/bf00899747 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029192736
130 https://doi.org/10.1007/bf00899747
131 rdf:type schema:CreativeWork
132 sg:pub.10.1007/bf01033230 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052341646
133 https://doi.org/10.1007/bf01033230
134 rdf:type schema:CreativeWork
135 sg:pub.10.1007/bf01145320 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046398371
136 https://doi.org/10.1007/bf01145320
137 rdf:type schema:CreativeWork
138 sg:pub.10.1007/bf01151436 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018278647
139 https://doi.org/10.1007/bf01151436
140 rdf:type schema:CreativeWork
141 sg:pub.10.1007/bf01248355 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034100362
142 https://doi.org/10.1007/bf01248355
143 rdf:type schema:CreativeWork
144 sg:pub.10.1007/bf02291478 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049977738
145 https://doi.org/10.1007/bf02291478
146 rdf:type schema:CreativeWork
147 sg:pub.10.1007/bfb0033764 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030399089
148 https://doi.org/10.1007/bfb0033764
149 rdf:type schema:CreativeWork
150 https://doi.org/10.1016/0002-9149(91)90831-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027254534
151 rdf:type schema:CreativeWork
152 https://doi.org/10.1016/0146-664x(82)90034-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1003975878
153 rdf:type schema:CreativeWork
154 https://doi.org/10.1016/0735-1097(89)90504-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017177900
155 rdf:type schema:CreativeWork
156 https://doi.org/10.1017/cbo9780511573064 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098664430
157 rdf:type schema:CreativeWork
158 https://doi.org/10.1109/34.121791 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061155634
159 rdf:type schema:CreativeWork
160 https://doi.org/10.1109/34.24792 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061155904
161 rdf:type schema:CreativeWork
162 https://doi.org/10.1109/tc.1972.5008949 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061531397
163 rdf:type schema:CreativeWork
164 https://doi.org/10.1117/12.146610 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033965965
165 rdf:type schema:CreativeWork
166 https://doi.org/10.1161/01.cir.81.4.1161 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032601562
167 rdf:type schema:CreativeWork
168 https://doi.org/10.1214/ss/1177013696 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064410204
169 rdf:type schema:CreativeWork
170 https://doi.org/10.2307/2413076 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069921405
171 rdf:type schema:CreativeWork
172 https://doi.org/10.2307/2992207 schema:sameAs https://app.dimensions.ai/details/publication/pub.1070161844
173 rdf:type schema:CreativeWork
174 https://www.grid.ac/institutes/grid.214458.e schema:alternateName University of Michigan–Ann Arbor
175 schema:name Institute of Gerontology, University of Michigan, Ann Arbor, Michigan 48109-2007, USA
176 rdf:type schema:Organization
177 https://www.grid.ac/institutes/grid.34477.33 schema:alternateName University of Washington
178 schema:name Division of Cardiology, School of Medicine University of Washington, Box 356422, Seattle, Washington 98195-6422, USA
179 rdf:type schema:Organization
 




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


...