Image registration driven by combined probabilistic and geometric descriptors

Linh Ha, Marcel Prastawa, Guido Gerig, John H. Gilmore, Cláudio T. Silva, Sarang Joshi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Deformable image registration in the presence of considerable contrast differences and large-scale size and shape changes represents a significant challenge for image registration. A representative driving application is the study of early brain development in neuroimaging, which requires co-registration of images of the same subject across time or building 4-D population atlases. Growth during the first few years of development involves significant changes in size and shape of anatomical structures but also rapid changes in tissue properties due to myelination and structuring that are reflected in the multi-modal Magnetic Resonance (MR) contrast measurements. We propose a new registration method that generates a mapping between brain anatomies represented as a multi-compartment model of tissue class posterior images and geometries. We transform intensity patterns into combined probabilistic and geometric descriptors that drive the matching in a diffeomorphic framework, where distances between geometries are represented using currents which does not require geometric correspondence. We show preliminary results on the registrations of neonatal brain MRIs to two-year old infant MRIs using class posteriors and surface boundaries of structures undergoing major changes. Quantitative validation demonstrates that our proposed method generates registrations that better preserve the consistency of anatomical structures over time.

Original languageEnglish (US)
Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings
Pages602-609
Number of pages8
Volume6362 LNCS
EditionPART 2
DOIs
StatePublished - 2010
Event13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010 - Beijing, China
Duration: Sep 20 2010Sep 24 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6362 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010
CountryChina
CityBeijing
Period9/20/109/24/10

Fingerprint

Image registration
Image Registration
Magnetic resonance imaging
Registration
Descriptors
Brain
Brain mapping
Tissue
Neuroimaging
Geometry
Magnetic resonance
Compartment Model
Magnetic Resonance
Atlas
Anatomy
Correspondence
Transform
Demonstrate
Class

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Ha, L., Prastawa, M., Gerig, G., Gilmore, J. H., Silva, C. T., & Joshi, S. (2010). Image registration driven by combined probabilistic and geometric descriptors. In Medical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings (PART 2 ed., Vol. 6362 LNCS, pp. 602-609). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6362 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-15745-5_74

Image registration driven by combined probabilistic and geometric descriptors. / Ha, Linh; Prastawa, Marcel; Gerig, Guido; Gilmore, John H.; Silva, Cláudio T.; Joshi, Sarang.

Medical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings. Vol. 6362 LNCS PART 2. ed. 2010. p. 602-609 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6362 LNCS, No. PART 2).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ha, L, Prastawa, M, Gerig, G, Gilmore, JH, Silva, CT & Joshi, S 2010, Image registration driven by combined probabilistic and geometric descriptors. in Medical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings. PART 2 edn, vol. 6362 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 6362 LNCS, pp. 602-609, 13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010, Beijing, China, 9/20/10. https://doi.org/10.1007/978-3-642-15745-5_74
Ha L, Prastawa M, Gerig G, Gilmore JH, Silva CT, Joshi S. Image registration driven by combined probabilistic and geometric descriptors. In Medical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings. PART 2 ed. Vol. 6362 LNCS. 2010. p. 602-609. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). https://doi.org/10.1007/978-3-642-15745-5_74
Ha, Linh ; Prastawa, Marcel ; Gerig, Guido ; Gilmore, John H. ; Silva, Cláudio T. ; Joshi, Sarang. / Image registration driven by combined probabilistic and geometric descriptors. Medical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings. Vol. 6362 LNCS PART 2. ed. 2010. pp. 602-609 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).
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