A modified well-conditioned iterative solution to the 1D inverse scattering problem using the Born iterative method

2006 ◽  
Author(s):  
I. Jeffrey ◽  
V.I. Okhmatovski ◽  
J. LoVetri
Keyword(s):  
Iterative Method ◽  
Inverse Scattering ◽  
Scattering Problem ◽  
Inverse Scattering Problem ◽  
Iterative Solution

scholarly journals Microwave Bone Imaging: A Preliminary Investigation on Numerical Bone Phantoms for Bone Health Monitoring

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6320
Author(s):  
Bilal Amin ◽  
Atif Shahzad ◽  
Martin O’Halloran ◽  
Muhammad Adnan Elahi
Keyword(s):  
Dielectric Properties ◽  
Compressed Sensing ◽  
Iterative Method ◽  
Inverse Scattering ◽  
Bone Health ◽  
Preliminary Investigation ◽  
Scattering Problem ◽  
Inverse Scattering Problem ◽  
Linear Inversion ◽  
Trabecular Bones

Microwave tomography (MWT) can be used as an alternative modality for monitoring human bone health. Studies have found a significant dielectric contrast between healthy and diseased human trabecular bones. A set of diverse bone phantoms were developed based on single-pole Debye parameters of osteoporotic and osteoarthritis human trabecular bones. The bone phantoms were designed as a two-layered circular structure, where the outer layer mimics the dielectric properties of the cortical bone and the inner layer mimics the dielectric properties of the trabecular bone. The electromagnetic (EM) inverse scattering problem was solved using a distorted Born iterative method (DBIM). A compressed sensing-based linear inversion approach referred to as iterative method with adaptive thresholding for compressed sensing (IMATCS) has been employed for solving the underdetermined set of linear equations at each DBIM iteration. To overcome the challenges posed by the ill-posedness of the EM inverse scattering problem, the L2-based regularization approach was adopted in the amalgamation of the IMATCS approach. The simulation results showed that osteoporotic and osteoarthritis bones can be differentiated based on the reconstructed dielectric properties even for low values of the signal-to-noise ratio. These results show that the adopted approach can be used to monitor bone health based on the reconstructed dielectric properties.

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