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Automated Multimodal Breast CAD Based on Registration of MRI and Two View Mammography

  • T. Hopp
  • P. Cotic Smole
  • N. V. Ruiter
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10553)

Abstract

Computer aided diagnosis (CAD) of breast cancer is mainly focused on monomodal applications. Here we present a fully automated multimodal CAD, which uses patient-specific image registration of MRI and two-view X-ray mammography. The image registration estimates the spatial correspondence between each voxel in the MRI and each pixel in cranio-caudal and mediolateral-oblique mammograms. Thereby we can combine features from both modalities. As a proof of concept we classify fixed regions of interest (ROI) into normal and suspect tissue. We investigate the classification performance of the multimodal classification in several setups against a classification with MRI features only. The average sensitivity of detecting suspect ROIs improves by approximately 2% when combining MRI with both mammographic views compared to MRI-only detection, while the specificity stays at a constant level. We conclude that automatically combining MRI and X-ray can enhance the result of a breast CAD system.

Keywords

Computer aided diagnosis Multimodal image registration X-ray mammography MRI 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Institute for Data Processing and ElectronicsKarlsruhe Institute of TechnologyKarlsruheGermany

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