Effect of nonrigid registration algorithms on deformation-based morphometry: a comparative study with control and Williams syndrome subjects
Deformation-based morphometry (DBM) is a widely used method for characterizing anatomical differences across groups. DBM is based on the analysis of the deformation fields generated by nonrigid registration algorithms, which warp the individual volumes to a DBM atlas. Although several studies have c...
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| Published in: | Magnetic resonance imaging Vol. 30; no. 6; pp. 774 - 788 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
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01.07.2012
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| ISSN: | 0730-725X, 1873-5894, 1873-5894 |
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| Abstract | Deformation-based morphometry (DBM) is a widely used method for characterizing anatomical differences across groups. DBM is based on the analysis of the deformation fields generated by nonrigid registration algorithms, which warp the individual volumes to a DBM atlas. Although several studies have compared nonrigid registration algorithms for segmentation tasks, few studies have compared the effect of the registration algorithms on group differences that may be uncovered through DBM. In this study, we compared group atlas creation and DBM results obtained with five well-established nonrigid registration algorithms using 13 subjects with Williams syndrome and 13 normal control subjects. The five nonrigid registration algorithms include the following: (1) the adaptive bases algorithm, (2) the image registration toolkit, (3) The FSL nonlinear image registration tool, (4) the automatic registration tool, and (5) the normalization algorithm available in Statistical Parametric Mapping (SPM8). Results indicate that the choice of algorithm has little effect on the creation of group atlases. However, regions of differences between groups detected with DBM vary from algorithm to algorithm both qualitatively and quantitatively. Some regions are detected by several algorithms, but their extent varies. Others are detected only by a subset of the algorithms. Based on these results, we recommend using more than one algorithm when performing DBM studies. |
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| AbstractList | Abstract Deformation-based morphometry (DBM) is a widely used method for characterizing anatomical differences across groups. DBM is based on the analysis of the deformation fields generated by nonrigid registration algorithms, which warp the individual volumes to a DBM atlas. Although several studies have compared nonrigid registration algorithms for segmentation tasks, few studies have compared the effect of the registration algorithms on group differences that may be uncovered through DBM. In this study, we compared group atlas creation and DBM results obtained with five well-established nonrigid registration algorithms using 13 subjects with Williams syndrome and 13 normal control subjects. The five nonrigid registration algorithms include the following: (1) the adaptive bases algorithm, (2) the image registration toolkit, (3) The FSL nonlinear image registration tool, (4) the automatic registration tool, and (5) the normalization algorithm available in Statistical Parametric Mapping (SPM8). Results indicate that the choice of algorithm has little effect on the creation of group atlases. However, regions of differences between groups detected with DBM vary from algorithm to algorithm both qualitatively and quantitatively. Some regions are detected by several algorithms, but their extent varies. Others are detected only by a subset of the algorithms. Based on these results, we recommend using more than one algorithm when performing DBM studies. Deformation-based morphometry (DBM) is a widely used method for characterizing anatomical differences across groups. DBM is based on the analysis of the deformation fields generated by nonrigid registration algorithms, which warp the individual volumes to a DBM atlas. Although several studies have compared nonrigid registration algorithms for segmentation tasks, few studies have compared the effect of the registration algorithms on group differences that may be uncovered through DBM. In this study, we compared group atlas creation and DBM results obtained with five well-established nonrigid registration algorithms using 13 subjects with Williams syndrome and 13 normal control subjects. The five nonrigid registration algorithms include the following: (1) the adaptive bases algorithm, (2) the image registration toolkit, (3) The FSL nonlinear image registration tool, (4) the automatic registration tool, and (5) the normalization algorithm available in Statistical Parametric Mapping (SPM8). Results indicate that the choice of algorithm has little effect on the creation of group atlases. However, regions of differences between groups detected with DBM vary from algorithm to algorithm both qualitatively and quantitatively. Some regions are detected by several algorithms, but their extent varies. Others are detected only by a subset of the algorithms. Based on these results, we recommend using more than one algorithm when performing DBM studies.Deformation-based morphometry (DBM) is a widely used method for characterizing anatomical differences across groups. DBM is based on the analysis of the deformation fields generated by nonrigid registration algorithms, which warp the individual volumes to a DBM atlas. Although several studies have compared nonrigid registration algorithms for segmentation tasks, few studies have compared the effect of the registration algorithms on group differences that may be uncovered through DBM. In this study, we compared group atlas creation and DBM results obtained with five well-established nonrigid registration algorithms using 13 subjects with Williams syndrome and 13 normal control subjects. The five nonrigid registration algorithms include the following: (1) the adaptive bases algorithm, (2) the image registration toolkit, (3) The FSL nonlinear image registration tool, (4) the automatic registration tool, and (5) the normalization algorithm available in Statistical Parametric Mapping (SPM8). Results indicate that the choice of algorithm has little effect on the creation of group atlases. However, regions of differences between groups detected with DBM vary from algorithm to algorithm both qualitatively and quantitatively. Some regions are detected by several algorithms, but their extent varies. Others are detected only by a subset of the algorithms. Based on these results, we recommend using more than one algorithm when performing DBM studies. Deformation-based morphometry (DBM) is a widely used method for characterizing anatomical differences across groups. DBM is based on the analysis of the deformation fields generated by nonrigid registration algorithms, which warp the individual volumes to a DBM atlas. Although several studies have compared nonrigid registration algorithms for segmentation tasks, few studies have compared the effect of the registration algorithms on group differences that may be uncovered through DBM. In this study, we compared group atlas creation and DBM results obtained with five well-established nonrigid registration algorithms using 13 subjects with Williams syndrome and 13 normal control subjects. The five nonrigid registration algorithms include the following: (1) the adaptive bases algorithm, (2) the image registration toolkit, (3) The FSL nonlinear image registration tool, (4) the automatic registration tool, and (5) the normalization algorithm available in Statistical Parametric Mapping (SPM8). Results indicate that the choice of algorithm has little effect on the creation of group atlases. However, regions of differences between groups detected with DBM vary from algorithm to algorithm both qualitatively and quantitatively. Some regions are detected by several algorithms, but their extent varies. Others are detected only by a subset of the algorithms. Based on these results, we recommend using more than one algorithm when performing DBM studies. |
| Author | Dykens, Elisabeth M. Thornton-Wells, Tricia A. Gore, John C. Dawant, Benoit M. Han, Zhaoying |
| Author_xml | – sequence: 1 givenname: Zhaoying surname: Han fullname: Han, Zhaoying email: natalie.hanz@gmail.com organization: Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37235, USA – sequence: 2 givenname: Tricia A. surname: Thornton-Wells fullname: Thornton-Wells, Tricia A. organization: Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA – sequence: 3 givenname: Elisabeth M. surname: Dykens fullname: Dykens, Elisabeth M. organization: Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA – sequence: 4 givenname: John C. surname: Gore fullname: Gore, John C. organization: Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA – sequence: 5 givenname: Benoit M. surname: Dawant fullname: Dawant, Benoit M. organization: Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37235, USA |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/22459439$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1111_jon_13091 crossref_primary_10_1371_journal_pone_0140567 crossref_primary_10_1007_s12021_018_9355_3 crossref_primary_10_1016_j_neuroimage_2013_06_004 crossref_primary_10_1016_j_redii_2023_100035 crossref_primary_10_1016_j_mri_2013_08_008 |
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| Keywords | Deformation-based morphometry Brain atlas Nonrigid registration Williams syndrome |
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| Snippet | Deformation-based morphometry (DBM) is a widely used method for characterizing anatomical differences across groups. DBM is based on the analysis of the... Abstract Deformation-based morphometry (DBM) is a widely used method for characterizing anatomical differences across groups. DBM is based on the analysis of... |
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| SubjectTerms | Adult Algorithms Brain - pathology Brain atlas Deformation-based morphometry Female Humans Image processing Magnetic resonance imaging Magnetic Resonance Imaging - methods Male Mapping Morphometry Nonrigid registration Radiology Segmentation Statistics Williams syndrome Williams Syndrome - pathology Young Adult |
| Title | Effect of nonrigid registration algorithms on deformation-based morphometry: a comparative study with control and Williams syndrome subjects |
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