Experimental Validation of Microwave Imaging Prototype and DBIM-IMATCS Algorithm for Bone Health Monitoring

Abstract

The evaluation of the microwave imaging (MWI) prototype and imaging algorithms on experimental bone phantoms is a precursor step before clinical testing for measuring in vivo dielectric properties of human bones. To this end, this paper presents microwave tomographic image reconstruction of experimental phantoms of normal and diseased human calcaneus bone using an MWI prototype and distorted Born iterative method (DBIM) algorithm for bone health monitoring application. A two-layered simplified cylindrical-shaped 3-D printed phantom was used to mimic the human calcaneus bone. The external and internal layers of the bone phantom mimic the cortical bone and trabecular bone, respectively. Liquid tissue-mimicking mixtures (TMM) for normal bone, osteoporotic bone, and osteoarthritis bone were prepared. The phantoms were placed in the imaging prototype and the electromagnetic inverse scattering problem was solved using the DBIM to create the complex permittivity images. An L_{2} -based regularization approach was adopted along with the iterative method with adaptive thresholding for compressed sensing (IMATCS) to overcome the ill-posedness and to solve the underdetermined set of linear equations at each DBIM iteration. The reconstruction of dielectric properties of bone phantoms have shown that L_{2} -IMATCS approach provides a robust reconstruction of diverse bone phantoms with acceptable accuracy. Moreover, the osteoporotic and osteoarthritis bone phantoms were distinguished based on reconstructed dielectric properties with an average percentage difference of 26% at 3 GHz. This paper has made the first attempt to validate an MWI prototype for bone imaging application. A DBIM-based iterative method has been employed to classify normal and diseased bone phantoms.