De-enhancing the dynamic contrast-enhanced breast MRI for robust registration

Yuanjie Zheng, Jingyi Yu, Chandra Kambhamettu, Sarah Englander, Mitchell D. Schnall, Dinggang Shen

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

Abstract

Dynamic enhancement causes serious problems for registration of contrast enhanced breast MRI, due to variable uptakes of agent on different tissues or even same tissues in the breast. We present an iterative optimization algorithm to de-enhance the dynamic contrastenhanced breast MRI and then register them for avoiding the effects of enhancement on image registration. In particular, the spatially varying enhancements are modeled by a Markov Random Field, and estimated by a locally smooth function with boundaries using a graph cut algorithm. The de-enhanced images are then registered by conventional Bspline based registration algorithm. These two steps benefit from each other and are repeated until the results converge. Experimental results show that our two-step registration algorithm performs much better than conventional mutual information based registration algorithm. Also, the effects of tumor shrinking in the conventional registration algorithms can be effectively avoided by our registration algorithm.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages933-941
Number of pages9
Volume4791 LNCS
EditionPART 1
Publication statusPublished - 2007 Dec 1
Externally publishedYes
Event10th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2007 - Brisbane, Australia
Duration: 2007 Oct 292007 Nov 2

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume4791 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other10th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2007
CountryAustralia
CityBrisbane
Period07/10/2907/11/2

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ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Zheng, Y., Yu, J., Kambhamettu, C., Englander, S., Schnall, M. D., & Shen, D. (2007). De-enhancing the dynamic contrast-enhanced breast MRI for robust registration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 1 ed., Vol. 4791 LNCS, pp. 933-941). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4791 LNCS, No. PART 1).