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Article
Peer-Review Record

Ultrasound Ultrafast Power Doppler Imaging with High Signal-to-Noise Ratio by Temporal Multiply-and-Sum (TMAS) Autocorrelation

Sensors 2022, 22(21), 8349; https://doi.org/10.3390/s22218349
by Che-Chou Shen * and Feng-Ting Guo
Reviewer 1: Anonymous
Reviewer 2:
Sensors 2022, 22(21), 8349; https://doi.org/10.3390/s22218349
Submission received: 31 August 2022 / Revised: 21 October 2022 / Accepted: 27 October 2022 / Published: 31 October 2022

Round 1

Reviewer 1 Report

Please find the attached comments.

Comments for author File: Comments.pdf

Author Response

The authors appreciate the comments from reviewer. Please see the attached file for our detailed responses to these comments.

Author Response File: Author Response.pdf

Reviewer 2 Report

In this manuscript, the authors proposed a temporal multiply-and-sum (TMAS) method to improve the signal-to-noise (SNR) ratio in ultrasound ultrafast power Doppler images. The results, especially the simulations, indicate that the proposed method can significantly improve the SNR. However, the novelty of this manuscript was not very well demonstrated. The authors used only a little more than half page in Section 2.3 to explain their proposed method. Equation (4), which is critical in this study, does not seem quite right. Section 2.1 and 2.2 are more like common basis of Doppler imaging. It is suggested that the authors describe their proposed method in detail or use more mathematical equations to explain why the method is able to improve the SNR.

Author Response

The authors appreciate the comments from reviewer. Please see the attached file for our detailed responses to these comments.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

The authors have made revisions according to the reviewer's comments. However, I still encourage the authors to further strengthen the description of the proposed method. For example, what is the characteristics of the signal? Why would magnitude scaling help reduce noise level? What is the theoretical foundation of this method?

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

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