Automated Model-Based Left Ventricle Segmentation in Cardiac MR Images View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2016-01-09

AUTHORS

Sharath Gopal , Demetri Terzopoulos

ABSTRACT

We present a fully automated system for segmenting the Left Ventricle (LV) in cardiac MR images based on statistical and deformable models. A Project-Out Inverse Compositional Active Appearance Model of 3D LV shape produces segmentations that are refined using a unified statistical/deterministic deformable model. A new multi-scale detector, based on the Histogram of Oriented Gradients (HoG), produces initial estimates of LV position and scale in the MR volume. The performance of the HoG detector and the deformable-model-based segmentation components are evaluated on the 30 MICCAI Grand Challenge test images. The average F-measure for detector bounding box overlap is 0.89. The average F-measures for contour overlap are 0.80 (endo), 0.82 (epi), and 0.46 (myocardium). More... »

PAGES

3-12

Book

TITLE

Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges

ISBN

978-3-319-28711-9
978-3-319-28712-6

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-28712-6_1

DOI

http://dx.doi.org/10.1007/978-3-319-28712-6_1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1002636953


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/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Computer Science Department, University of California, Los Angeles, USA", 
          "id": "http://www.grid.ac/institutes/grid.19006.3e", 
          "name": [
            "Computer Science Department, University of California, Los Angeles, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gopal", 
        "givenName": "Sharath", 
        "id": "sg:person.013544572527.35", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013544572527.35"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Computer Science Department, University of California, Los Angeles, USA", 
          "id": "http://www.grid.ac/institutes/grid.19006.3e", 
          "name": [
            "Computer Science Department, University of California, Los Angeles, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Terzopoulos", 
        "givenName": "Demetri", 
        "id": "sg:person.016347323445.35", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016347323445.35"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2016-01-09", 
    "datePublishedReg": "2016-01-09", 
    "description": "We present a fully automated system for segmenting the Left Ventricle (LV) in cardiac MR images based on statistical and deformable models. A Project-Out Inverse Compositional Active Appearance Model of 3D LV shape produces segmentations that are refined using a unified statistical/deterministic deformable model. A new multi-scale detector, based on the Histogram of Oriented Gradients (HoG), produces initial estimates of LV position and scale in the MR volume. The performance of the HoG detector and the deformable-model-based segmentation components are evaluated on the 30 MICCAI Grand Challenge test images. The average F-measure for detector bounding box overlap is 0.89. The average F-measures for contour overlap are 0.80 (endo), 0.82 (epi), and 0.46 (myocardium).", 
    "editor": [
      {
        "familyName": "Camara", 
        "givenName": "Oscar", 
        "type": "Person"
      }, 
      {
        "familyName": "Mansi", 
        "givenName": "Tommaso", 
        "type": "Person"
      }, 
      {
        "familyName": "Pop", 
        "givenName": "Mihaela", 
        "type": "Person"
      }, 
      {
        "familyName": "Rhode", 
        "givenName": "Kawal", 
        "type": "Person"
      }, 
      {
        "familyName": "Sermesant", 
        "givenName": "Maxime", 
        "type": "Person"
      }, 
      {
        "familyName": "Young", 
        "givenName": "Alistair", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-319-28712-6_1", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-319-28711-9", 
        "978-3-319-28712-6"
      ], 
      "name": "Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges", 
      "type": "Book"
    }, 
    "keywords": [
      "cardiac MR images", 
      "deformable model", 
      "multi-scale detector", 
      "Active Appearance Models", 
      "Left Ventricle Segmentation", 
      "Oriented Gradients", 
      "segmentation component", 
      "HOG detector", 
      "appearance model", 
      "test images", 
      "ventricle segmentation", 
      "MR volumes", 
      "MR images", 
      "box overlap", 
      "contour overlap", 
      "segmentation", 
      "images", 
      "initial estimates", 
      "histogram", 
      "LV shape", 
      "LV position", 
      "model", 
      "detector", 
      "performance", 
      "project", 
      "system", 
      "measures", 
      "components", 
      "position", 
      "overlap", 
      "shape", 
      "estimates", 
      "volume", 
      "left ventricle", 
      "scale", 
      "gradient", 
      "ventricle", 
      "Inverse Compositional Active Appearance Model", 
      "Compositional Active Appearance Model", 
      "deterministic deformable model", 
      "new multi-scale detector", 
      "MICCAI Grand Challenge test images", 
      "Grand Challenge test images", 
      "Challenge test images"
    ], 
    "name": "Automated Model-Based Left Ventricle Segmentation in Cardiac MR Images", 
    "pagination": "3-12", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1002636953"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-319-28712-6_1"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-319-28712-6_1", 
      "https://app.dimensions.ai/details/publication/pub.1002636953"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2022-01-01T19:24", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220101/entities/gbq_results/chapter/chapter_422.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/978-3-319-28712-6_1"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-28712-6_1'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-28712-6_1'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-28712-6_1'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-28712-6_1'


 

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

136 TRIPLES      23 PREDICATES      69 URIs      62 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-319-28712-6_1 schema:about anzsrc-for:08
2 anzsrc-for:0801
3 schema:author N8476f67033384ec9a58060cf76deee55
4 schema:datePublished 2016-01-09
5 schema:datePublishedReg 2016-01-09
6 schema:description We present a fully automated system for segmenting the Left Ventricle (LV) in cardiac MR images based on statistical and deformable models. A Project-Out Inverse Compositional Active Appearance Model of 3D LV shape produces segmentations that are refined using a unified statistical/deterministic deformable model. A new multi-scale detector, based on the Histogram of Oriented Gradients (HoG), produces initial estimates of LV position and scale in the MR volume. The performance of the HoG detector and the deformable-model-based segmentation components are evaluated on the 30 MICCAI Grand Challenge test images. The average F-measure for detector bounding box overlap is 0.89. The average F-measures for contour overlap are 0.80 (endo), 0.82 (epi), and 0.46 (myocardium).
7 schema:editor N7e76a6a0a3c14d9fab3862d215f72117
8 schema:genre chapter
9 schema:inLanguage en
10 schema:isAccessibleForFree false
11 schema:isPartOf N4b66bffcc4364006a34001fda7885f0f
12 schema:keywords Active Appearance Models
13 Challenge test images
14 Compositional Active Appearance Model
15 Grand Challenge test images
16 HOG detector
17 Inverse Compositional Active Appearance Model
18 LV position
19 LV shape
20 Left Ventricle Segmentation
21 MICCAI Grand Challenge test images
22 MR images
23 MR volumes
24 Oriented Gradients
25 appearance model
26 box overlap
27 cardiac MR images
28 components
29 contour overlap
30 deformable model
31 detector
32 deterministic deformable model
33 estimates
34 gradient
35 histogram
36 images
37 initial estimates
38 left ventricle
39 measures
40 model
41 multi-scale detector
42 new multi-scale detector
43 overlap
44 performance
45 position
46 project
47 scale
48 segmentation
49 segmentation component
50 shape
51 system
52 test images
53 ventricle
54 ventricle segmentation
55 volume
56 schema:name Automated Model-Based Left Ventricle Segmentation in Cardiac MR Images
57 schema:pagination 3-12
58 schema:productId N7bd62c39b5e34530a485e7f9127904b0
59 Nb7d2650e25af424397d29bdbd54dffed
60 schema:publisher Nfca3729833744edf870554e3289061a9
61 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002636953
62 https://doi.org/10.1007/978-3-319-28712-6_1
63 schema:sdDatePublished 2022-01-01T19:24
64 schema:sdLicense https://scigraph.springernature.com/explorer/license/
65 schema:sdPublisher Nd855b8bc3ccc48bf90c20a998157cca0
66 schema:url https://doi.org/10.1007/978-3-319-28712-6_1
67 sgo:license sg:explorer/license/
68 sgo:sdDataset chapters
69 rdf:type schema:Chapter
70 N01dcd3dfe14d4f92bde8f41a779e0b2f schema:familyName Rhode
71 schema:givenName Kawal
72 rdf:type schema:Person
73 N15c63c6091b64b88b8895ca5c4c09cea rdf:first Nc9e7fe44f74a4a7db8756763995c49f2
74 rdf:rest N936afd7f42aa489e941a45e4b5be0e85
75 N3a97ba864f8141ada1fa6017c0604f34 rdf:first N01dcd3dfe14d4f92bde8f41a779e0b2f
76 rdf:rest N15c63c6091b64b88b8895ca5c4c09cea
77 N4b66bffcc4364006a34001fda7885f0f schema:isbn 978-3-319-28711-9
78 978-3-319-28712-6
79 schema:name Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges
80 rdf:type schema:Book
81 N66bc79c3479846a5894832945536fb63 rdf:first Nb38fc263327142a3a2612ca8698fb546
82 rdf:rest N3a97ba864f8141ada1fa6017c0604f34
83 N7bd62c39b5e34530a485e7f9127904b0 schema:name doi
84 schema:value 10.1007/978-3-319-28712-6_1
85 rdf:type schema:PropertyValue
86 N7e76a6a0a3c14d9fab3862d215f72117 rdf:first Nffebced79ebc484f8a172f30d45857fb
87 rdf:rest N8ca280c7f33c440aa31f42002c7dba90
88 N7fb1516654be45fa97285fe7131026e5 rdf:first sg:person.016347323445.35
89 rdf:rest rdf:nil
90 N8476f67033384ec9a58060cf76deee55 rdf:first sg:person.013544572527.35
91 rdf:rest N7fb1516654be45fa97285fe7131026e5
92 N8ca280c7f33c440aa31f42002c7dba90 rdf:first Naece942f70394e8bb3b6ceced1afd74f
93 rdf:rest N66bc79c3479846a5894832945536fb63
94 N936afd7f42aa489e941a45e4b5be0e85 rdf:first Nf736397f6b2a42a3899978f06e71a475
95 rdf:rest rdf:nil
96 Naece942f70394e8bb3b6ceced1afd74f schema:familyName Mansi
97 schema:givenName Tommaso
98 rdf:type schema:Person
99 Nb38fc263327142a3a2612ca8698fb546 schema:familyName Pop
100 schema:givenName Mihaela
101 rdf:type schema:Person
102 Nb7d2650e25af424397d29bdbd54dffed schema:name dimensions_id
103 schema:value pub.1002636953
104 rdf:type schema:PropertyValue
105 Nc9e7fe44f74a4a7db8756763995c49f2 schema:familyName Sermesant
106 schema:givenName Maxime
107 rdf:type schema:Person
108 Nd855b8bc3ccc48bf90c20a998157cca0 schema:name Springer Nature - SN SciGraph project
109 rdf:type schema:Organization
110 Nf736397f6b2a42a3899978f06e71a475 schema:familyName Young
111 schema:givenName Alistair
112 rdf:type schema:Person
113 Nfca3729833744edf870554e3289061a9 schema:name Springer Nature
114 rdf:type schema:Organisation
115 Nffebced79ebc484f8a172f30d45857fb schema:familyName Camara
116 schema:givenName Oscar
117 rdf:type schema:Person
118 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
119 schema:name Information and Computing Sciences
120 rdf:type schema:DefinedTerm
121 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
122 schema:name Artificial Intelligence and Image Processing
123 rdf:type schema:DefinedTerm
124 sg:person.013544572527.35 schema:affiliation grid-institutes:grid.19006.3e
125 schema:familyName Gopal
126 schema:givenName Sharath
127 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013544572527.35
128 rdf:type schema:Person
129 sg:person.016347323445.35 schema:affiliation grid-institutes:grid.19006.3e
130 schema:familyName Terzopoulos
131 schema:givenName Demetri
132 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016347323445.35
133 rdf:type schema:Person
134 grid-institutes:grid.19006.3e schema:alternateName Computer Science Department, University of California, Los Angeles, USA
135 schema:name Computer Science Department, University of California, Los Angeles, USA
136 rdf:type schema:Organization
 




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


...