Comparison of four breast tissue segmentation algorithms for multi-modal MRI to X-ray mammography registration

E. Garcìa, A. Oliver, Y. Diez, O. Diaz, A. Gubern-Mèrida, X. Lladò, J. Martì

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

3 Citations (Scopus)


Breast MRI to X-ray mammography registration using patient-specific biomechanical models is one challenging task in medical imaging. To solve this problem, the accurate knowledge about internal and external factors of the breast, such as internal tissues distribution, is needed for modelling a suitable physical behavior. In this work, we compare four different tissue segmentation algorithms, two intensity-based segmentation algorithms (Fuzzy C-means and Gaussian mixture model) and two improvements that incorporate spatial information (Kernelized Fuzzy C-means and Markov Random Fields, respectively), and analyze their effect to the multi-modal registration. The overall framework consists on using a density estimation software (Volpara™) to extract the glandular tissue from full-field digital mammograms, meanwhile, a biomechanical model is used to mimic the mammographic acquisition from the MRI, computing the glandular tissue traversed by the X-ray beam. Results with 40 patients show a high agreement between the amount of glandular tissue computed for each method.

Original languageEnglish
Title of host publicationBreast Imaging - 13th International Workshop, IWDM 2016, Proceedings
EditorsKristina Lang, Anders Tingberg, Pontus Timberg
PublisherSpringer Verlag
Number of pages8
ISBN (Print)9783319415451
Publication statusPublished - 2016
Event13th International Workshop on Breast Imaging, IWDM 2016 - Malmo, Sweden
Duration: 2016 Jun 192016 Jun 22

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other13th International Workshop on Breast Imaging, IWDM 2016

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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