ParkinsonCanadaV1, PascalFrancis, Curation, bibRecord, 000785

Comparison of Piece-Wise Linear, Linear, and Nonlinear Atlas-to-Patient Warping Techniques: Analysis of the Labeling of Subcortical Nuclei for Functional Neurosurgical Applications

Identifieur interne : 000785 ( PascalFrancis/Curation ); précédent : 000784; suivant : 000786

Comparison of Piece-Wise Linear, Linear, and Nonlinear Atlas-to-Patient Warping Techniques: Analysis of the Labeling of Subcortical Nuclei for Functional Neurosurgical Applications

Auteurs : M. Mallar Chakravarty [Canada] ; Abbas F. Sadikot [Canada] ; Jürgen Germany [Canada] ; Pierre Hellier [France] ; Gilles Bertrand [Canada] ; D. Louis Collins [Canada]

Source :

Human brain mapping [ 1065-9471 ] ; 2009.

RBID : Pascal:09-0447014

Descripteurs français

Pascal (Inist)
- Maladie de Parkinson, Pathologie du système nerveux, Etude comparative, Non linéarité, Atlas, Homme, Technique, Souscortex, Chirurgie, Planification, Thalamotomie, Radiodiagnostic, Stimulation cérébrale profonde.
Wicri :
- topic : Atlas, Homme, Chirurgie.

English descriptors

KwdEn :
- Atlas, Comparative study, Deep brain stimulation, Human, Nervous system diseases, Nonlinearity, Parkinson disease, Planning, Radiodiagnosis, Subcortex, Surgery, Technique, Thalamotomy.

Abstract

Digital atlases are commonly used in pre-operative planning in functional neurosurgical procedures performed to minimize the symptoms of Parkinson's disease. These atlases can be customized to fit an individual patient's anatomy through atlas-to-patient warping procedures. Once fitted to pre-operative magnetic resonance imaging (MRI) data, the customized atlas can be used to plan and navigate surgical procedures. Linear, piece-wise linear and nonlinear registration methods have been used to customize different digital atlases with varying accuracies. Our goal was to evaluate eight different registration methods for atlas-to-patient customization of a new digital atlas of the basal ganglia and thalamus to demonstrate the value of nonlinear registration for automated atlas-based subcortical target identification in functional neurosurgery. In this work, we evaluate the accuracy of two automated linear techniques, two piece-wise linear techniques (requiring the identification of manually placed anatomical landmarks), and four different automated nonlinear atlas-to-patient warping techniques (where two of the four nonlinear techniques are variants of the ANIMAL algorithm). Since a gold standard of the subcortical anatomy is not available, manual segmentations of the striatum, globus pallidus, and thalamus are used to derive a silver standard for evaluation. Four different metrics, including the kappa statistic, the mean distance between the surfaces, the maximum distance between surfaces, and the total structure volume are used to compare the warping techniques. The results show that nonlinear techniques perform statistically better than linear and piece-wise linear techniques. In addition, the results demonstrate statistically significant differences between the nonlinear techniques, with the ANIMAL algorithm yielding better results.

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A08	`01`	`1`	`ENG`	`@1 Comparison of Piece-Wise Linear, Linear, and Nonlinear Atlas-to-Patient Warping Techniques: Analysis of the Labeling of Subcortical Nuclei for Functional Neurosurgical Applications`
A11	`01`	`1`		`@1 MALLAR CHAKRAVARTY (M.)`
A11	`02`	`1`		`@1 SADIKOT (Abbas F.)`
A11	`03`	`1`		`@1 GERMANY (Jürgen)`
A11	`04`	`1`		`@1 HELLIER (Pierre)`
A11	`05`	`1`		`@1 BERTRAND (Gilles)`
A11	`06`	`1`		`@1 COLLINS (D. Louis)`
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C01	`01`		`ENG`	@0 Digital atlases are commonly used in pre-operative planning in functional neurosurgical procedures performed to minimize the symptoms of Parkinson's disease. These atlases can be customized to fit an individual patient's anatomy through atlas-to-patient warping procedures. Once fitted to pre-operative magnetic resonance imaging (MRI) data, the customized atlas can be used to plan and navigate surgical procedures. Linear, piece-wise linear and nonlinear registration methods have been used to customize different digital atlases with varying accuracies. Our goal was to evaluate eight different registration methods for atlas-to-patient customization of a new digital atlas of the basal ganglia and thalamus to demonstrate the value of nonlinear registration for automated atlas-based subcortical target identification in functional neurosurgery. In this work, we evaluate the accuracy of two automated linear techniques, two piece-wise linear techniques (requiring the identification of manually placed anatomical landmarks), and four different automated nonlinear atlas-to-patient warping techniques (where two of the four nonlinear techniques are variants of the ANIMAL algorithm). Since a gold standard of the subcortical anatomy is not available, manual segmentations of the striatum, globus pallidus, and thalamus are used to derive a silver standard for evaluation. Four different metrics, including the kappa statistic, the mean distance between the surfaces, the maximum distance between surfaces, and the total structure volume are used to compare the warping techniques. The results show that nonlinear techniques perform statistically better than linear and piece-wise linear techniques. In addition, the results demonstrate statistically significant differences between the nonlinear techniques, with the ANIMAL algorithm yielding better results.
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C03	`04`	`X`	`ENG`	`@0 Nonlinearity @5 10`
C03	`04`	`X`	`SPA`	`@0 No linealidad @5 10`
C03	`05`	`X`	`FRE`	`@0 Atlas @5 11`
C03	`05`	`X`	`ENG`	`@0 Atlas @5 11`
C03	`05`	`X`	`SPA`	`@0 Atlas @5 11`
C03	`06`	`X`	`FRE`	`@0 Homme @5 12`
C03	`06`	`X`	`ENG`	`@0 Human @5 12`
C03	`06`	`X`	`SPA`	`@0 Hombre @5 12`
C03	`07`	`X`	`FRE`	`@0 Technique @5 13`
C03	`07`	`X`	`ENG`	`@0 Technique @5 13`
C03	`07`	`X`	`SPA`	`@0 Técnica @5 13`
C03	`08`	`X`	`FRE`	`@0 Souscortex @5 14`
C03	`08`	`X`	`ENG`	`@0 Subcortex @5 14`
C03	`08`	`X`	`SPA`	`@0 Subcorteza @5 14`
C03	`09`	`X`	`FRE`	`@0 Chirurgie @5 15`
C03	`09`	`X`	`ENG`	`@0 Surgery @5 15`
C03	`09`	`X`	`SPA`	`@0 Cirugía @5 15`
C03	`10`	`X`	`FRE`	`@0 Planification @5 17`
C03	`10`	`X`	`ENG`	`@0 Planning @5 17`
C03	`10`	`X`	`SPA`	`@0 Planificación @5 17`
C03	`11`	`X`	`FRE`	`@0 Thalamotomie @5 18`
C03	`11`	`X`	`ENG`	`@0 Thalamotomy @5 18`
C03	`11`	`X`	`SPA`	`@0 Talamotomía @5 18`
C03	`12`	`X`	`FRE`	`@0 Radiodiagnostic @5 19`
C03	`12`	`X`	`ENG`	`@0 Radiodiagnosis @5 19`
C03	`12`	`X`	`SPA`	`@0 Radiodiagnóstico @5 19`
C03	`13`	`X`	`FRE`	`@0 Stimulation cérébrale profonde @4 CD @5 96`
C03	`13`	`X`	`ENG`	`@0 Deep brain stimulation @4 CD @5 96`
C07	`01`	`X`	`FRE`	`@0 Pathologie de l'encéphale @5 37`
C07	`01`	`X`	`ENG`	`@0 Cerebral disorder @5 37`
C07	`01`	`X`	`SPA`	`@0 Encéfalo patología @5 37`
C07	`02`	`X`	`FRE`	`@0 Syndrome extrapyramidal @5 38`
C07	`02`	`X`	`ENG`	`@0 Extrapyramidal syndrome @5 38`
C07	`02`	`X`	`SPA`	`@0 Extrapiramidal síndrome @5 38`
C07	`03`	`X`	`FRE`	`@0 Maladie dégénérative @5 39`
C07	`03`	`X`	`ENG`	`@0 Degenerative disease @5 39`
C07	`03`	`X`	`SPA`	`@0 Enfermedad degenerativa @5 39`
C07	`04`	`X`	`FRE`	`@0 Pathologie du système nerveux central @5 40`
C07	`04`	`X`	`ENG`	`@0 Central nervous system disease @5 40`
C07	`04`	`X`	`SPA`	`@0 Sistema nervosio central patología @5 40`
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N44	`01`			`@1 OTO`
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Le document en format XML

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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Comparison of Piece-Wise Linear, Linear, and Nonlinear Atlas-to-Patient Warping Techniques: Analysis of the Labeling of Subcortical Nuclei for Functional Neurosurgical Applications</title>
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<series><title level="j" type="main">Human brain mapping</title>
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<term>Nonlinearity</term>
<term>Parkinson disease</term>
<term>Planning</term>
<term>Radiodiagnosis</term>
<term>Subcortex</term>
<term>Surgery</term>
<term>Technique</term>
<term>Thalamotomy</term>
</keywords>
<keywords scheme="Pascal" xml:lang="fr"><term>Maladie de Parkinson</term>
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<term>Atlas</term>
<term>Homme</term>
<term>Technique</term>
<term>Souscortex</term>
<term>Chirurgie</term>
<term>Planification</term>
<term>Thalamotomie</term>
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<front><div type="abstract" xml:lang="en">Digital atlases are commonly used in pre-operative planning in functional neurosurgical procedures performed to minimize the symptoms of Parkinson's disease. These atlases can be customized to fit an individual patient's anatomy through atlas-to-patient warping procedures. Once fitted to pre-operative magnetic resonance imaging (MRI) data, the customized atlas can be used to plan and navigate surgical procedures. Linear, piece-wise linear and nonlinear registration methods have been used to customize different digital atlases with varying accuracies. Our goal was to evaluate eight different registration methods for atlas-to-patient customization of a new digital atlas of the basal ganglia and thalamus to demonstrate the value of nonlinear registration for automated atlas-based subcortical target identification in functional neurosurgery. In this work, we evaluate the accuracy of two automated linear techniques, two piece-wise linear techniques (requiring the identification of manually placed anatomical landmarks), and four different automated nonlinear atlas-to-patient warping techniques (where two of the four nonlinear techniques are variants of the ANIMAL algorithm). Since a gold standard of the subcortical anatomy is not available, manual segmentations of the striatum, globus pallidus, and thalamus are used to derive a silver standard for evaluation. Four different metrics, including the kappa statistic, the mean distance between the surfaces, the maximum distance between surfaces, and the total structure volume are used to compare the warping techniques. The results show that nonlinear techniques perform statistically better than linear and piece-wise linear techniques. In addition, the results demonstrate statistically significant differences between the nonlinear techniques, with the ANIMAL algorithm yielding better results.</div>
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<fA11 i1="04" i2="1"><s1>HELLIER (Pierre)</s1>
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<fA11 i1="05" i2="1"><s1>BERTRAND (Gilles)</s1>
</fA11>
<fA11 i1="06" i2="1"><s1>COLLINS (D. Louis)</s1>
</fA11>
<fA14 i1="01"><s1>McConnell Brain Imaging Center, Montréal Neurological Institute, McGill University</s1>
<s2>Montréal, Quebec</s2>
<s3>CAN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>5 aut.</sZ>
<sZ>6 aut.</sZ>
</fA14>
<fA14 i1="02"><s1>Division of Neurosurgery, McGill University</s1>
<s2>Montréal, Quebec</s2>
<s3>CAN</s3>
<sZ>2 aut.</sZ>
<sZ>5 aut.</sZ>
</fA14>
<fA14 i1="03"><s1>INRIA, IRISA Visages team, Campus de Beaulieu</s1>
<s2>Rennes</s2>
<s3>FRA</s3>
<sZ>4 aut.</sZ>
</fA14>
<fA14 i1="04"><s1>INSERM, Visages-U746, IRISA, Campus de Beaulieu</s1>
<s2>Rennes</s2>
<s3>FRA</s3>
<sZ>4 aut.</sZ>
</fA14>
<fA20><s1>3574-3595</s1>
</fA20>
<fA21><s1>2009</s1>
</fA21>
<fA23 i1="01"><s0>ENG</s0>
</fA23>
<fA43 i1="01"><s1>INIST</s1>
<s2>26079</s2>
<s5>354000171239110100</s5>
</fA43>
<fA44><s0>0000</s0>
<s1>© 2009 INIST-CNRS. All rights reserved.</s1>
</fA44>
<fA45><s0>2 p.1/4</s0>
</fA45>
<fA47 i1="01" i2="1"><s0>09-0447014</s0>
</fA47>
<fA60><s1>P</s1>
</fA60>
<fA61><s0>A</s0>
</fA61>
<fA64 i1="01" i2="1"><s0>Human brain mapping</s0>
</fA64>
<fA66 i1="01"><s0>USA</s0>
</fA66>
<fC01 i1="01" l="ENG"><s0>Digital atlases are commonly used in pre-operative planning in functional neurosurgical procedures performed to minimize the symptoms of Parkinson's disease. These atlases can be customized to fit an individual patient's anatomy through atlas-to-patient warping procedures. Once fitted to pre-operative magnetic resonance imaging (MRI) data, the customized atlas can be used to plan and navigate surgical procedures. Linear, piece-wise linear and nonlinear registration methods have been used to customize different digital atlases with varying accuracies. Our goal was to evaluate eight different registration methods for atlas-to-patient customization of a new digital atlas of the basal ganglia and thalamus to demonstrate the value of nonlinear registration for automated atlas-based subcortical target identification in functional neurosurgery. In this work, we evaluate the accuracy of two automated linear techniques, two piece-wise linear techniques (requiring the identification of manually placed anatomical landmarks), and four different automated nonlinear atlas-to-patient warping techniques (where two of the four nonlinear techniques are variants of the ANIMAL algorithm). Since a gold standard of the subcortical anatomy is not available, manual segmentations of the striatum, globus pallidus, and thalamus are used to derive a silver standard for evaluation. Four different metrics, including the kappa statistic, the mean distance between the surfaces, the maximum distance between surfaces, and the total structure volume are used to compare the warping techniques. The results show that nonlinear techniques perform statistically better than linear and piece-wise linear techniques. In addition, the results demonstrate statistically significant differences between the nonlinear techniques, with the ANIMAL algorithm yielding better results.</s0>
</fC01>
<fC02 i1="01" i2="X"><s0>002B24A06</s0>
</fC02>
<fC02 i1="02" i2="X"><s0>002B24D02</s0>
</fC02>
<fC03 i1="01" i2="X" l="FRE"><s0>Maladie de Parkinson</s0>
<s2>NM</s2>
<s5>01</s5>
</fC03>
<fC03 i1="01" i2="X" l="ENG"><s0>Parkinson disease</s0>
<s2>NM</s2>
<s5>01</s5>
</fC03>
<fC03 i1="01" i2="X" l="SPA"><s0>Parkinson enfermedad</s0>
<s2>NM</s2>
<s5>01</s5>
</fC03>
<fC03 i1="02" i2="X" l="FRE"><s0>Pathologie du   système nerveux</s0>
<s5>02</s5>
</fC03>
<fC03 i1="02" i2="X" l="ENG"><s0>Nervous system diseases</s0>
<s5>02</s5>
</fC03>
<fC03 i1="02" i2="X" l="SPA"><s0>Sistema nervioso patología</s0>
<s5>02</s5>
</fC03>
<fC03 i1="03" i2="X" l="FRE"><s0>Etude comparative</s0>
<s5>09</s5>
</fC03>
<fC03 i1="03" i2="X" l="ENG"><s0>Comparative study</s0>
<s5>09</s5>
</fC03>
<fC03 i1="03" i2="X" l="SPA"><s0>Estudio comparativo</s0>
<s5>09</s5>
</fC03>
<fC03 i1="04" i2="X" l="FRE"><s0>Non linéarité</s0>
<s5>10</s5>
</fC03>
<fC03 i1="04" i2="X" l="ENG"><s0>Nonlinearity</s0>
<s5>10</s5>
</fC03>
<fC03 i1="04" i2="X" l="SPA"><s0>No linealidad</s0>
<s5>10</s5>
</fC03>
<fC03 i1="05" i2="X" l="FRE"><s0>Atlas</s0>
<s5>11</s5>
</fC03>
<fC03 i1="05" i2="X" l="ENG"><s0>Atlas</s0>
<s5>11</s5>
</fC03>
<fC03 i1="05" i2="X" l="SPA"><s0>Atlas</s0>
<s5>11</s5>
</fC03>
<fC03 i1="06" i2="X" l="FRE"><s0>Homme</s0>
<s5>12</s5>
</fC03>
<fC03 i1="06" i2="X" l="ENG"><s0>Human</s0>
<s5>12</s5>
</fC03>
<fC03 i1="06" i2="X" l="SPA"><s0>Hombre</s0>
<s5>12</s5>
</fC03>
<fC03 i1="07" i2="X" l="FRE"><s0>Technique</s0>
<s5>13</s5>
</fC03>
<fC03 i1="07" i2="X" l="ENG"><s0>Technique</s0>
<s5>13</s5>
</fC03>
<fC03 i1="07" i2="X" l="SPA"><s0>Técnica</s0>
<s5>13</s5>
</fC03>
<fC03 i1="08" i2="X" l="FRE"><s0>Souscortex</s0>
<s5>14</s5>
</fC03>
<fC03 i1="08" i2="X" l="ENG"><s0>Subcortex</s0>
<s5>14</s5>
</fC03>
<fC03 i1="08" i2="X" l="SPA"><s0>Subcorteza</s0>
<s5>14</s5>
</fC03>
<fC03 i1="09" i2="X" l="FRE"><s0>Chirurgie</s0>
<s5>15</s5>
</fC03>
<fC03 i1="09" i2="X" l="ENG"><s0>Surgery</s0>
<s5>15</s5>
</fC03>
<fC03 i1="09" i2="X" l="SPA"><s0>Cirugía</s0>
<s5>15</s5>
</fC03>
<fC03 i1="10" i2="X" l="FRE"><s0>Planification</s0>
<s5>17</s5>
</fC03>
<fC03 i1="10" i2="X" l="ENG"><s0>Planning</s0>
<s5>17</s5>
</fC03>
<fC03 i1="10" i2="X" l="SPA"><s0>Planificación</s0>
<s5>17</s5>
</fC03>
<fC03 i1="11" i2="X" l="FRE"><s0>Thalamotomie</s0>
<s5>18</s5>
</fC03>
<fC03 i1="11" i2="X" l="ENG"><s0>Thalamotomy</s0>
<s5>18</s5>
</fC03>
<fC03 i1="11" i2="X" l="SPA"><s0>Talamotomía</s0>
<s5>18</s5>
</fC03>
<fC03 i1="12" i2="X" l="FRE"><s0>Radiodiagnostic</s0>
<s5>19</s5>
</fC03>
<fC03 i1="12" i2="X" l="ENG"><s0>Radiodiagnosis</s0>
<s5>19</s5>
</fC03>
<fC03 i1="12" i2="X" l="SPA"><s0>Radiodiagnóstico</s0>
<s5>19</s5>
</fC03>
<fC03 i1="13" i2="X" l="FRE"><s0>Stimulation cérébrale profonde</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<fC03 i1="13" i2="X" l="ENG"><s0>Deep brain stimulation</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<fC07 i1="01" i2="X" l="FRE"><s0>Pathologie de l'encéphale</s0>
<s5>37</s5>
</fC07>
<fC07 i1="01" i2="X" l="ENG"><s0>Cerebral disorder</s0>
<s5>37</s5>
</fC07>
<fC07 i1="01" i2="X" l="SPA"><s0>Encéfalo patología</s0>
<s5>37</s5>
</fC07>
<fC07 i1="02" i2="X" l="FRE"><s0>Syndrome extrapyramidal</s0>
<s5>38</s5>
</fC07>
<fC07 i1="02" i2="X" l="ENG"><s0>Extrapyramidal syndrome</s0>
<s5>38</s5>
</fC07>
<fC07 i1="02" i2="X" l="SPA"><s0>Extrapiramidal síndrome</s0>
<s5>38</s5>
</fC07>
<fC07 i1="03" i2="X" l="FRE"><s0>Maladie dégénérative</s0>
<s5>39</s5>
</fC07>
<fC07 i1="03" i2="X" l="ENG"><s0>Degenerative disease</s0>
<s5>39</s5>
</fC07>
<fC07 i1="03" i2="X" l="SPA"><s0>Enfermedad degenerativa</s0>
<s5>39</s5>
</fC07>
<fC07 i1="04" i2="X" l="FRE"><s0>Pathologie du   système nerveux central</s0>
<s5>40</s5>
</fC07>
<fC07 i1="04" i2="X" l="ENG"><s0>Central nervous system disease</s0>
<s5>40</s5>
</fC07>
<fC07 i1="04" i2="X" l="SPA"><s0>Sistema nervosio central patología</s0>
<s5>40</s5>
</fC07>
<fN21><s1>327</s1>
</fN21>
<fN44 i1="01"><s1>OTO</s1>
</fN44>
<fN82><s1>OTO</s1>
</fN82>
</pA>
</standard>
</inist>
</record>

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	La maladie de Parkinson au Canada (serveur d'exploration)
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La maladie de Parkinson au Canada (serveur d'exploration)

Comparison of Piece-Wise Linear, Linear, and Nonlinear Atlas-to-Patient Warping Techniques: Analysis of the Labeling of Subcortical Nuclei for Functional Neurosurgical Applications

Comparison of Piece-Wise Linear, Linear, and Nonlinear Atlas-to-Patient Warping Techniques: Analysis of the Labeling of Subcortical Nuclei for Functional Neurosurgical Applications

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