An inverse scattering problem estimates the distribution of key physical parameters such as dielectric constant and conductivity (electromagnetic problem) or compressibility and density (acoustic problem), based on the measured samples of the scattered field. It is usually formulated using the volume integral equations, which after proper discretization turns out to be ill-posed, ill-conditioned, and often under-determined.
Nonlinear inverse scattering algorithms can be used for microwave imaging, diffraction tomography and buried object detection. Within MiXIL, we apply the nonlinear inverse scattering technique for the detection of breast tumors. Detecting tumors at an early stage is the key in increasing the survival rate of breast cancer patients. Compared with other imaging methods for cancer screening and diagnosis, microwave imaging can be used without the risks inherent in ionizing radiation and with relatively low cost.
In previous work, we have presented nonlinear inverse scattering algorithms with multi-parameter optimization for microwave imaging, and we are currently developing a customized GPU-accelerated algorithm to address the computationally intense nature of reconstructing high resolution breast images.
High resolution reconstruction of a realistic breast phantom using a GPU accelerated inverse scattering algorithm
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