Skip to main content
Erschienen in: Neuroinformatics 3/2014

01.07.2014 | Original Article

Intensity Based Methods for Brain MRI Longitudinal Registration. A Study on Multiple Sclerosis Patients

verfasst von: Yago Diez, Arnau Oliver, Mariano Cabezas, Sergi Valverde, Robert Martí, Joan Carles Vilanova, Lluís Ramió-Torrentà, Àlex Rovira, Xavier Lladó

Erschienen in: Neuroinformatics | Ausgabe 3/2014

Einloggen, um Zugang zu erhalten

Abstract

Registration is a key step in many automatic brain Magnetic Resonance Imaging (MRI) applications. In this work we focus on longitudinal registration of brain MRI for Multiple Sclerosis (MS) patients. First of all, we analyze the effect that MS lesions have on registration by synthetically eliminating some of the lesions. Our results show how a widely used method for longitudinal registration such as rigid registration is practically unconcerned by the presence of MS lesions while several non-rigid registration methods produce outputs that are significantly different. We then focus on assessing which is the best registration method for longitudinal MRI images of MS patients. In order to analyze the results obtained for all studied criteria, we use both descriptive statistics and statistical inference: one way ANOVA, pairwise t-tests and permutation tests.
Fußnoten
1
Xinapse Systems, JIM software webpage, http://​www.​xinapse.​com/​home.​php.
 
2
Insight Segmentation and Registration Toolkit webpage, http://​www.​itk.​org/​.
 
3
 
6
NITRC Automatic Registration Toolbox webpage, http://​www.​nitrc.​org/​projects/​art/​.
 
7
Statistical Parameter Mapping webpage, http://​www.​fil.​ion.​ucl.​ac.​uk/​spm/​ For the computations related to this paper we used the SPM8 version.
 
9
We used ITK implementation for both Demons and Diffeomorphic Demons. Specifically, the Diffeomorphic demons implementation can be downloaded at http://​www.​insight-journal.​org/​browse/​publication/​154/​. See “the itk programming guide” for details on how to download the code for classical itk demons.
 
Literatur
Zurück zum Zitat Ardekani, B.A., Guckemus, S., Bachman, A., Hoptman, M.J., Wojtaszek, M., Nierenberg, J. (2005). Quantitative comparison of algorithms for inter-subject registration of 3D volumetric brain MRI scans. NeuroImage, 142(1), 67–76. Ardekani, B.A., Guckemus, S., Bachman, A., Hoptman, M.J., Wojtaszek, M., Nierenberg, J. (2005). Quantitative comparison of algorithms for inter-subject registration of 3D volumetric brain MRI scans. NeuroImage, 142(1), 67–76.
Zurück zum Zitat Ashburner, J. (2007). A fast diffeomorphic image registration algorithm. NeuroImage, 38(1), 95–113.PubMedCrossRef Ashburner, J. (2007). A fast diffeomorphic image registration algorithm. NeuroImage, 38(1), 95–113.PubMedCrossRef
Zurück zum Zitat Ashburner, J., & Friston, K.J. (2004). Human Brain Function, chap High-dimensional image warping, 2nd edn. (pp. 673–694). Academic Press. Ashburner, J., & Friston, K.J. (2004). Human Brain Function, chap High-dimensional image warping, 2nd edn. (pp. 673–694). Academic Press.
Zurück zum Zitat Avants, B.B., Epstein, C.L., Grossman, M., Gee, J.C. (2008). Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Medical Image Analysis, 12(1), 26–41.PubMedCentralPubMedCrossRef Avants, B.B., Epstein, C.L., Grossman, M., Gee, J.C. (2008). Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Medical Image Analysis, 12(1), 26–41.PubMedCentralPubMedCrossRef
Zurück zum Zitat Cabezas, M., Oliver, A., Lladó, X., Freixenet, J., Bach Cuadra, M. (2011). A review of atlas-based segmentation for magnetic resonance brain images. Computer Methods and Programs in Biomedicine, 104(3), e158–e177.PubMedCrossRef Cabezas, M., Oliver, A., Lladó, X., Freixenet, J., Bach Cuadra, M. (2011). A review of atlas-based segmentation for magnetic resonance brain images. Computer Methods and Programs in Biomedicine, 104(3), e158–e177.PubMedCrossRef
Zurück zum Zitat Chard, D.T., Jackson, J.S., Miller, D.H., Wheeler-Kingshott, C.A.M. (2010). Reducing the impact of white matter lesions on automated measures of brain gray and white matter volumes. Journal of Magnetic Resonance Imaging, 32(1), 223–228.PubMedCrossRef Chard, D.T., Jackson, J.S., Miller, D.H., Wheeler-Kingshott, C.A.M. (2010). Reducing the impact of white matter lesions on automated measures of brain gray and white matter volumes. Journal of Magnetic Resonance Imaging, 32(1), 223–228.PubMedCrossRef
Zurück zum Zitat Denton, E.R., Sonoda, L.I., Rueckert, D., Rankin, S.C., Hayes, C., Leach, M.O., Hill, D.L., Hawkes, D.J. (1999). Comparison and evaluation of rigid and non-rigid registration of breast MR images. Journal of Computer Assisted Tomography, 23(5), 800–805.PubMedCrossRef Denton, E.R., Sonoda, L.I., Rueckert, D., Rankin, S.C., Hayes, C., Leach, M.O., Hill, D.L., Hawkes, D.J. (1999). Comparison and evaluation of rigid and non-rigid registration of breast MR images. Journal of Computer Assisted Tomography, 23(5), 800–805.PubMedCrossRef
Zurück zum Zitat Diez, Y., Oliver, A., Llad´o, X., Freixenet, J., Mart´ı, J., Vilanova, J.C., Martí, R. (2011). Revisiting intensity-based image registration appplied to mammography. IEEE Transactions on Information Technology in BioMedicine, 15(5), 716–725.PubMedCrossRef Diez, Y., Oliver, A., Llad´o, X., Freixenet, J., Mart´ı, J., Vilanova, J.C., Martí, R. (2011). Revisiting intensity-based image registration appplied to mammography. IEEE Transactions on Information Technology in BioMedicine, 15(5), 716–725.PubMedCrossRef
Zurück zum Zitat Elliott, C., Arnold, D.L., Collins, D.L. (2013). Temporally consistent probabilistic detection of new multiple sclerosis lesions in brain mri. IEEE Transactions on Medical Imaging, 32(8), 1490–1502.PubMedCrossRef Elliott, C., Arnold, D.L., Collins, D.L. (2013). Temporally consistent probabilistic detection of new multiple sclerosis lesions in brain mri. IEEE Transactions on Medical Imaging, 32(8), 1490–1502.PubMedCrossRef
Zurück zum Zitat García-Lorenzo, D., Francis, S., Narayanan, S., Arnold, D.L., Collins, D.L. (2013). Review of automatic segmentation methods of multiple sclerosis white matter lesions on conventional magnetic resonance imaging. Medical Image Analysis, 17(1), 1–18.PubMedCrossRef García-Lorenzo, D., Francis, S., Narayanan, S., Arnold, D.L., Collins, D.L. (2013). Review of automatic segmentation methods of multiple sclerosis white matter lesions on conventional magnetic resonance imaging. Medical Image Analysis, 17(1), 1–18.PubMedCrossRef
Zurück zum Zitat Klein, A., Andersson, J., Ardekani, B.A., Ashburner, J., Avants, B.B., Chiang, M., Christensen, G.E., Collins, D.L., Gee, J., Hellier, P., Song Hyun, J., Jenkinson, M., Lepage, C., Rueckert, D., Thompson, P., Vercauteren, T., Woods, R.P., Mann, J.J., Parseya, R. (2009). Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration. NeuroImage, 46(3), 786–802.PubMedCentralPubMedCrossRef Klein, A., Andersson, J., Ardekani, B.A., Ashburner, J., Avants, B.B., Chiang, M., Christensen, G.E., Collins, D.L., Gee, J., Hellier, P., Song Hyun, J., Jenkinson, M., Lepage, C., Rueckert, D., Thompson, P., Vercauteren, T., Woods, R.P., Mann, J.J., Parseya, R. (2009). Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration. NeuroImage, 46(3), 786–802.PubMedCentralPubMedCrossRef
Zurück zum Zitat Liao, S., Wu, G., Shen, D. (2012). A statistical framework for inter-group image registration. Neuroinformatics, 10(4), 367–378.PubMedCrossRef Liao, S., Wu, G., Shen, D. (2012). A statistical framework for inter-group image registration. Neuroinformatics, 10(4), 367–378.PubMedCrossRef
Zurück zum Zitat Liu, C., Iglesias, J.E., Tu, Z. (2013). Deformable templates guided discriminative models for robust 3d brain mri segmentation for the alzheimer’s disease neuroimaging initiative. Neuroinformatics, 11(4), 447–468.PubMedCrossRef Liu, C., Iglesias, J.E., Tu, Z. (2013). Deformable templates guided discriminative models for robust 3d brain mri segmentation for the alzheimer’s disease neuroimaging initiative. Neuroinformatics, 11(4), 447–468.PubMedCrossRef
Zurück zum Zitat Lladó, X., Ganiler, O., Oliver, A., Martí, R., Freixenet, J., Valls, L., Rovira A (2012a). Automated detection of multiple sclerosis lesions in serial brain MRI. Neuroradiology, 54(8), 787–807.CrossRef Lladó, X., Ganiler, O., Oliver, A., Martí, R., Freixenet, J., Valls, L., Rovira A (2012a). Automated detection of multiple sclerosis lesions in serial brain MRI. Neuroradiology, 54(8), 787–807.CrossRef
Zurück zum Zitat Lladó, X., Oliver, A., Cabezas, M., Freixenet, J., Vilanova, J.C., Quiles, A., Valls, L., Ramió-Torrentà, L., Rovira, A. (2012b). Segmentation of multiple sclerosis lesions in brain MRI: a review of automated approaches. Information Sciences, 186(1), 164–185.CrossRef Lladó, X., Oliver, A., Cabezas, M., Freixenet, J., Vilanova, J.C., Quiles, A., Valls, L., Ramió-Torrentà, L., Rovira, A. (2012b). Segmentation of multiple sclerosis lesions in brain MRI: a review of automated approaches. Information Sciences, 186(1), 164–185.CrossRef
Zurück zum Zitat Menke, J., & Martinez, T. (2004). Using permutations instead of student’s t distribution for p-values in paired difference algorithm comparisons. In Proceedings IEEE international joint conference on neural networks (pp. 1331–1335). Menke, J., & Martinez, T. (2004). Using permutations instead of student’s t distribution for p-values in paired difference algorithm comparisons. In Proceedings IEEE international joint conference on neural networks (pp. 1331–1335).
Zurück zum Zitat Modat, M., Ridgway, G.R., Taylor, Z.A., Lehmann, M., Barnes, J., Hawkes, D.J., Fox, N.C., Ourselin, S. (2010). Fast free-form deformation using graphics processing units. Computer Methods and Programs in Biomedicine, 98(3), 278–284.PubMedCrossRef Modat, M., Ridgway, G.R., Taylor, Z.A., Lehmann, M., Barnes, J., Hawkes, D.J., Fox, N.C., Ourselin, S. (2010). Fast free-form deformation using graphics processing units. Computer Methods and Programs in Biomedicine, 98(3), 278–284.PubMedCrossRef
Zurück zum Zitat Moraal, B., Meier, D.S., Poppe, P.A., Geurts, J.J., Vrenken, H., Jonker, W.M., Knol, D.L., van Schijndel, R.A., Pouwels, P.J., Pohl, C., Bauer, L., Sandbrink, R., Guttman, C.R., Barkhof, F. (2009). Subtraction mr images in a multiple sclerosis multicenter clinical trial setting. Radiology, 250(2), 506–514.PubMedCentralPubMedCrossRef Moraal, B., Meier, D.S., Poppe, P.A., Geurts, J.J., Vrenken, H., Jonker, W.M., Knol, D.L., van Schijndel, R.A., Pouwels, P.J., Pohl, C., Bauer, L., Sandbrink, R., Guttman, C.R., Barkhof, F. (2009). Subtraction mr images in a multiple sclerosis multicenter clinical trial setting. Radiology, 250(2), 506–514.PubMedCentralPubMedCrossRef
Zurück zum Zitat Moraal, B.,Wattjes, M.P., Geurts, J.J., Knol, D.L., van Schijndel, R.A., Pouwels, P.J., Vrenken, H., Barkhof, F. (2010). Improved detection of active multiple sclerosis lesions: 3d subtraction imaging. Radiology, 255(1), 154–163.PubMedCrossRef Moraal, B.,Wattjes, M.P., Geurts, J.J., Knol, D.L., van Schijndel, R.A., Pouwels, P.J., Vrenken, H., Barkhof, F. (2010). Improved detection of active multiple sclerosis lesions: 3d subtraction imaging. Radiology, 255(1), 154–163.PubMedCrossRef
Zurück zum Zitat Ou, Y., Sotiras, A., Paragios, N., Davatzikos, C. (2011). Dramms: deformable registration via attribute matching and mutual-saliency weighting. Medical Image Analysis, 15(4), 622–639.PubMedCentralPubMedCrossRef Ou, Y., Sotiras, A., Paragios, N., Davatzikos, C. (2011). Dramms: deformable registration via attribute matching and mutual-saliency weighting. Medical Image Analysis, 15(4), 622–639.PubMedCentralPubMedCrossRef
Zurück zum Zitat Parisot, S., Duffau, H., Chemouny, S., Paragios, N. (2012). Joint tumor segmentation and dense deformable registration of brain MR images. In Proceedings medical image computing and computer assisted intervention (pp. 651–658). Parisot, S., Duffau, H., Chemouny, S., Paragios, N. (2012). Joint tumor segmentation and dense deformable registration of brain MR images. In Proceedings medical image computing and computer assisted intervention (pp. 651–658).
Zurück zum Zitat Prados, F., Boada, I., Feixas, M., Prats-Galino, A., Blasco, G., Puig, J., Pedraza, S. (2012). Information-theoretic approach for automated white matter fiber tracts reconstruction. Neuroinformatics, 10(3), 305–318.PubMedCrossRef Prados, F., Boada, I., Feixas, M., Prats-Galino, A., Blasco, G., Puig, J., Pedraza, S. (2012). Information-theoretic approach for automated white matter fiber tracts reconstruction. Neuroinformatics, 10(3), 305–318.PubMedCrossRef
Zurück zum Zitat Rohlfing, T. (2012). Image similarity and tissue overlaps as surrogates for image registration accuracy: widely used but unreliable. IEEE Transactions on Medical Imaging, 31(2), 153–163.PubMedCentralPubMedCrossRef Rohlfing, T. (2012). Image similarity and tissue overlaps as surrogates for image registration accuracy: widely used but unreliable. IEEE Transactions on Medical Imaging, 31(2), 153–163.PubMedCentralPubMedCrossRef
Zurück zum Zitat Rueckert, D., Sonoda, L.I., Hayes, C., Hill, D.L., Leach, M.O., Hawkes, D.J. (1999). Non-rigid registration using free-form deformations: application to breast MR images. IEEE Transactions on Medical Imaging, 18(8), 712–721.PubMedCrossRef Rueckert, D., Sonoda, L.I., Hayes, C., Hill, D.L., Leach, M.O., Hawkes, D.J. (1999). Non-rigid registration using free-form deformations: application to breast MR images. IEEE Transactions on Medical Imaging, 18(8), 712–721.PubMedCrossRef
Zurück zum Zitat Rueckert, D., Aljabar, P., Heckemann, R.A., Hajnal, J.V., Hammers, A. (2006). Diffeomorphic registration using B-splines. In Proceedings medical image computing and computer assisted intervention (pp. 702–709). Rueckert, D., Aljabar, P., Heckemann, R.A., Hajnal, J.V., Hammers, A. (2006). Diffeomorphic registration using B-splines. In Proceedings medical image computing and computer assisted intervention (pp. 702–709).
Zurück zum Zitat Schnabel, J., Rueckert, D., Quist, M., Blackall, J., Castellano-Smith, A., Hartkens, T., Penney, G., Hall, W., Liu, H., Truwit, C., Gerritsen, F., Hill, D., Hawkes, D.J. (2001). A generic framework for non-rigid registration based on non-uniform multi-level free-form deformations. In Proceedings medical image computing and computer assisted intervention (pp. 573–581). Schnabel, J., Rueckert, D., Quist, M., Blackall, J., Castellano-Smith, A., Hartkens, T., Penney, G., Hall, W., Liu, H., Truwit, C., Gerritsen, F., Hill, D., Hawkes, D.J. (2001). A generic framework for non-rigid registration based on non-uniform multi-level free-form deformations. In Proceedings medical image computing and computer assisted intervention (pp. 573–581).
Zurück zum Zitat Sdika, M., & Pelletier, D. (2009). Nonrigid registration of multiple sclerosis brain images using lesion inpainting for morphometry or lesion mapping. Human Brain Mapping, 30(4), 1060–1067.PubMedCrossRef Sdika, M., & Pelletier, D. (2009). Nonrigid registration of multiple sclerosis brain images using lesion inpainting for morphometry or lesion mapping. Human Brain Mapping, 30(4), 1060–1067.PubMedCrossRef
Zurück zum Zitat Shah, M., Xiao, Y., Subbanna, N., Francis, S., Arnold, D.L., Arbel, T. (2011). Evaluating intensity normalization on MRIs of human brain with multiple sclerosis. Medical Image Analysis, 15(2), 267–282.PubMedCrossRef Shah, M., Xiao, Y., Subbanna, N., Francis, S., Arnold, D.L., Arbel, T. (2011). Evaluating intensity normalization on MRIs of human brain with multiple sclerosis. Medical Image Analysis, 15(2), 267–282.PubMedCrossRef
Zurück zum Zitat Shi, W., Zhuang, X., Pizarro, L., Bai, W., Wang, H., Tung, K., Edwards, P., Rueckert, D. (2012). Registration using sparse free-form deformations. In Proceedings medical image computing and computer assisted intervention (pp. 659–666). Shi, W., Zhuang, X., Pizarro, L., Bai, W., Wang, H., Tung, K., Edwards, P., Rueckert, D. (2012). Registration using sparse free-form deformations. In Proceedings medical image computing and computer assisted intervention (pp. 659–666).
Zurück zum Zitat Thirion, J.P. (1996). Non-rigid matching using demons. In Proceedings IEEE conference on computer vision and pattern recognition (pp. 245–261). Thirion, J.P. (1996). Non-rigid matching using demons. In Proceedings IEEE conference on computer vision and pattern recognition (pp. 245–261).
Zurück zum Zitat Vercauteren, T., Pennec, X., Perchant, A., Ayache, N. (2009). Diffeomorphic demons: efficient non-parametric image registration. NeuroImage, 45(1 (S1)), S61–S72.PubMedCrossRef Vercauteren, T., Pennec, X., Perchant, A., Ayache, N. (2009). Diffeomorphic demons: efficient non-parametric image registration. NeuroImage, 45(1 (S1)), S61–S72.PubMedCrossRef
Metadaten
Titel
Intensity Based Methods for Brain MRI Longitudinal Registration. A Study on Multiple Sclerosis Patients
verfasst von
Yago Diez
Arnau Oliver
Mariano Cabezas
Sergi Valverde
Robert Martí
Joan Carles Vilanova
Lluís Ramió-Torrentà
Àlex Rovira
Xavier Lladó
Publikationsdatum
01.07.2014
Verlag
Springer US
Erschienen in
Neuroinformatics / Ausgabe 3/2014
Print ISSN: 1539-2791
Elektronische ISSN: 1559-0089
DOI
https://doi.org/10.1007/s12021-013-9216-z

Weitere Artikel der Ausgabe 3/2014

Neuroinformatics 3/2014 Zur Ausgabe

Leitlinien kompakt für die Neurologie

Mit medbee Pocketcards sicher entscheiden.

Seit 2022 gehört die medbee GmbH zum Springer Medizin Verlag

Hirnblutung unter DOAK und VKA ähnlich bedrohlich

17.05.2024 Direkte orale Antikoagulanzien Nachrichten

Kommt es zu einer nichttraumatischen Hirnblutung, spielt es keine große Rolle, ob die Betroffenen zuvor direkt wirksame orale Antikoagulanzien oder Marcumar bekommen haben: Die Prognose ist ähnlich schlecht.

Was nützt die Kraniektomie bei schwerer tiefer Hirnblutung?

17.05.2024 Hirnblutung Nachrichten

Eine Studie zum Nutzen der druckentlastenden Kraniektomie nach schwerer tiefer supratentorieller Hirnblutung deutet einen Nutzen der Operation an. Für überlebende Patienten ist das dennoch nur eine bedingt gute Nachricht.

Thrombektomie auch bei großen Infarkten von Vorteil

16.05.2024 Ischämischer Schlaganfall Nachrichten

Auch ein sehr ausgedehnter ischämischer Schlaganfall scheint an sich kein Grund zu sein, von einer mechanischen Thrombektomie abzusehen. Dafür spricht die LASTE-Studie, an der Patienten und Patientinnen mit einem ASPECTS von maximal 5 beteiligt waren.

Update Neurologie

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.