Examination of the sensitivity matrix during the iterative reconstruction process for microwave tomography
Paper in proceeding, 2018

We have reconstructed microwave tomographic images utilizing a Gauss-Newton scheme with a log transformation. While the recovered images are quite good, we have analyzed the behavior of the associated Jacobian, or sensitivity, matrix with respect to how it evolves during the reconstruction process. We found that in general the highest sensitivities are along the periphery of the imaging zone confirming the fact that most algorithms operate best for features nearest the outside. Interestingly, our log transformed algorithm appears to evolve during the reconstruction process to increase its internal sensitivity once the major exterior ones have been resolved. These results provide useful insight into a key driver of the reconstruction process and provide useful tools for assessing different system design criteria.

log transformation.

microwave tomography

sensitivity matrix

Author

Paul M Meaney

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering

Thayer School of Engineering at Dartmouth

Shireen D. Geimer

Thayer School of Engineering at Dartmouth

Keith D. Paulsen

Thayer School of Engineering at Dartmouth

2018 IEEE Conference on Antenna Measurements and Applications, CAMA 2018

8530594

2018 IEEE Conference on Antenna Measurements and Applications, CAMA 2018
Vasteras, Sweden,

Subject Categories

Signal Processing

Computer Vision and Robotics (Autonomous Systems)

Medical Image Processing

DOI

10.1109/CAMA.2018.8530594

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