Magnetic Induction Tomography: Separation of the Ill-Posed and Non-Linear Inverse Problem into a Series of Isolated and Less Demanding Subproblems
Round 1
Reviewer 1 Report
Please see attached report
Comments for author File: 
Comments.pdf
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 2 Report
The work is required to highlight the improvement based on analysis of this research. However, the analysis part is missing.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 3 Report
This thesis focuses on Magnetic Induction Tomography: (MIT) carrying out a non-linear inverse problem study with creativity. But some issues need to be considered, as follows in the attachment
Comments for author File: Comments.pdf
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
The authors addressed all my concerns in this new version. Nonetheless, a discussion on the reference [2-in my previous review] has not been implemented in the manuscript, although it is strongly related to the current study. Furthermore, it is based on shape gradient descent optimization. The Landweber method, on which this manuscript is based, is a variant of the standard steepest gradient descent linear iterative method. As the author mentioned it is "widely used in optimization theory to solve ill-posed inverse problems"
It is then important in my view to discuss the pros and cons of the current work in regard to other work to showcase the current strength and competitivity.
Overall, I keep this comment to the authors while proofreading, as I appreciate the substantial work done so far.
Reviewer 2 Report
The manuscript is now ready for publication
Reviewer 3 Report
This manuscript has been revised according to the comments. I recommend accepting the manuscript.
