Image Reconstruction using Microwave Tomography for Breast Cancer Detection on Distributed Memory Machine

  • Authors:

  • Meilian Xu;Abas Sabouni;Parimala Thulasiraman;Sima Noghanian;Stephen Pistorius

  • Affiliations:

  • University of Manitoba, Canada;University of Manitoba, Canada;University of Manitoba, Canada;University of Manitoba, Canada;CancerCare Manitoba, Canada

  • Venue:
  • ICPP '07 Proceedings of the 2007 International Conference on Parallel Processing
  • Year:
  • 2007

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Abstract

Breast cancer, with the exception of lung cancer, is the leading cause of cancer deaths in women. It is also one of the few cancers that can be controlled by using asymptomatic screening method, followed by effective treatments. One recent screening modality under development, microwave tomography, uses the apparent dielectric property contrasts between different breast tissues at microwave frequencies. Microwave tomography uses a numerical model and the image reconstruction consists of iteratively searching the breast structures, applying the numerical model to the breast structures, and matching measured data with computation results of the model. This paper focuses on Finite-Difference Time-Domain (FDTD) for the numerical model and Genetic Algorithm (GA) for the iterative searches. FDTD and GA are time-consuming, yet they are data parallel in nature. In this paper, a parallel algorithm integrating GA and FDTD for detecting tumors using microwave tomography technique is presented. The algorithm is implemented on distributed memory machines usingMPI.