Multimodal non-rigid registration methods based on Demons models and local uncertainty quantification used in 3D brain images

Isnardo Reducindo, Aldo R. Mejía-Rodríguez, Edgar Arce-Santana, Daniel U. Campos-Delgado, Elisa Scalco, Giovanni M. Cattaneo, Giovanna Rizzo

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

Abstract

In this work, we propose a novel fully automated method to solve the 3D multimodal non-rigid image registration problem. The proposed strategy overcomes the monomodal intensity restriction of fluid-like registration (FLR) models, such as Demons-based registration algorithms, by applying a mapping that relies on an intensity uncertainty quantification in a local neighbourhood, bringing the target and source images into a common domain where they are comparable, no matter their image modalities or mismatched intensities between them. The proposed methodology was tested with T1, T2 and PD weighted brain magnetic resonance (MR) images with synthetic deformations, and CT-MR brain images from a radiotherapy clinical case. The performance of the proposed approach was evaluated quantitatively by standard indices that assess the correct alignment of anatomical structures of interest. The results obtained in this work show that the addition of the local uncertainty mapping properly resolve the monomodal restriction of FLR algorithms when same anatomic counterparts exists in the images to register, and suggest that the proposed strategy can be an option to achieve multimodal 3D registrations.

Original languageEnglish
Title of host publicationAdvances in Visual Computing - 10th International Symposium, ISVC 2014, Proceedings
PublisherSpringer Verlag
Pages11-20
Number of pages10
Volume8888
ISBN (Print)9783319143637
Publication statusPublished - 2014
Event10th International Symposium on Visual Computing, ISVC 2014 - Las Vegas, United States
Duration: Dec 8 2014Dec 10 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8888
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other10th International Symposium on Visual Computing, ISVC 2014
CountryUnited States
CityLas Vegas
Period12/8/1412/10/14

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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  • Cite this

    Reducindo, I., Mejía-Rodríguez, A. R., Arce-Santana, E., Campos-Delgado, D. U., Scalco, E., Cattaneo, G. M., & Rizzo, G. (2014). Multimodal non-rigid registration methods based on Demons models and local uncertainty quantification used in 3D brain images. In Advances in Visual Computing - 10th International Symposium, ISVC 2014, Proceedings (Vol. 8888, pp. 11-20). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8888). Springer Verlag.