Multimodal Breast Parenchymal Patterns Correlation Using a Patient-Specific Biomechanical Model

Eloy García, Yago Diez, Oliver Diaz, Xavier Lladó, Albert Gubern-Mérida, Robert Martí, Joan Martí, Arnau Oliver

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


In this paper, we aim to produce a realistic 2-D projection of the breast parenchymal distribution from a 3-D breast magnetic resonance image (MRI). To evaluate the accuracy of our simulation, we compare our results with the local breast density (i.e., density map) obtained from the complementary full-field digital mammogram. To achieve this goal, we have developed a fully automatic framework, which registers MRI volumes to X-ray mammograms using a subject-specific biomechanical model of the breast. The optimization step modifies the position, orientation, and elastic parameters of the breast model to perform the alignment between the images. When the model reaches an optimal solution, the MRI glandular tissue is projected and compared with the one obtained from the corresponding mammograms. To reduce the loss of information during the ray-casting, we introduce a new approach that avoids resampling the MRI volume. In the results, we focus our efforts on evaluating the agreement of the distributions of glandular tissue, the degree of structural similarity, and the correlation between the real and synthetic density maps. Our approach obtained a high-structural agreement regardless the glandularity of the breast, whilst the similarity of the glandular tissue distributions and correlation between both images increase in denser breasts. Furthermore, the synthetic images show continuity with respect to large structures in the density maps.

Original languageEnglish
Pages (from-to)712-723
Number of pages12
JournalIEEE Transactions on Medical Imaging
Issue number3
Publication statusPublished - 2018 Mar


  • Breast cancer
  • cross-modality
  • parenchymal patterns
  • subject-specific biomechanical models

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering


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