Pre-Reconstruction Processing with the Cycle-Consist Generative Adversarial Network Combined with Attention Gate to Improve Image Quality in Digital Breast Tomosynthesis
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThe study proposed and evaluated residual squeeze and excitation attention gate (rSEAG), a novel network that can improve image quality by reducing distortion attributed to artifacts and noise and by improving contrast. The paper is well written and achieved remarkable results. My decision is accept in present form.
The method proposed gave good results. U-net method seems having better results according to the visuals.
I have one question for the paper. What is the reason that authors only selected Homogeneity and Contrast features in GLCM method? Why were the other features not used for quality measurement?
Author Response
Please refer to the attached files for responses to reviewer's comments and corrections.
Author Response File: Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsPlease refer to the attachment.
Comments for author File: Comments.pdf
Good
Author Response
Please refer to the attached files for responses to reviewer's comments and corrections.
Author Response File: Author Response.pdf