PONE-D-21-09994

Automatic Semantic Segmentation of Breast Tumors in Ultrasound Images Based on Combining Fuzzy Logic and Deep Learning – A Feasibility Study

PLOS ONE

Dear Dr. GadAllah,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Based on the suggestions from the reviewers and my own observation I recommend minor revisions for this paper.

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We look forward to receiving your revised manuscript.

Kind regards,

Thippa Reddy Gadekallu

Academic Editor

PLOS ONE

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1. We noted in your submission details that a portion of your manuscript may have been presented or published elsewhere. „Our submitted manuscript intitled: “Automatic Semantic Segmentation of Breast Tumors in Ultrasound Images Based on Combining Fuzzy Logic and Deep Learning – A Feasibility Study”, is a replacement to the submission No. PONE-D-21-07670 ( Efficient Automatic Semantic Segmentation of Breast Tumors in Ultrasound Images Based on Combining Fuzzy Logic and Deep Learning  ). „ Please clarify whether this publication was peer-reviewed and formally published. If this work was previously peer-reviewed and published, in the cover letter please provide the reason that this work does not constitute dual publication and should be included in the current manuscript.

4. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: According to my understanding, this paper presentse a combination of fuzzy logic and deep learning for automatic semantic segmentation (SS) of tumors in breast ultrasound (BUS) images is proposed.

- The abbrivation should be used only first time, then only acroyyms should be used in the entire paper.

- This paper need minor modifications. Below are my comments:

- Abstract can be reduced. ​The abstract is NOT satisfactory because it didn't contain the following parts:

​i. The importance of or motivation for the research.

​ii. The issue/argument of the research.

​iii. The methodology.

​iv. The result/findings.

​v. The implications of the result/findings.

- In the first four paragraphs of literature review section, the authors have presented a good references, but they need to present the recent and most updated references

- Authos should discuss the dataset extensively.

- The quality of the figures can be improved more. Figures should be eye-catching. It will enhance the interest of the reader.

- Please highlight the contribution clearly in the introduction

- Some Paragraphs in the paper can be merged and some long paragraphs can be split into two.

- The discussion is very important in research paper. Nevertheless, this section is short and should be presented completely.

-- Authors should add the most recent reference:

1) BCD-WERT: a novel approach for breast cancer detection using whale optimization based efficient features and extremely randomized tree algorithm, PeerJ Computer Science 7, e390

2) Classification of COVID-19 individuals using adaptive neuro-fuzzy inference system, Multimedia Systems, 1-15

Reviewer #2: In Introduction section, the drawbacks of each conventional technique should be described clearly.

The authors should emphasize the difference between other methods to clarify the position of this work further.

The motivation for the present research would be clearer, by providing a more direct link between the importance of choosing your own method.

Define all the variables before using

The writing of the paper needs a lot of improvement in terms of grammar, spellings, and presentations. The paper needs careful English polishing since there are many typos and poorly written sentences.

The authors can cite the following references

Antlion re-sampling based deep neural network model for classification of imbalanced multimodal stroke dataset

An AI-based intelligent system for healthcare analysis using Ridge-Adaline Stochastic Gradient Descent Classifier

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Reviewer #1: No

Reviewer #2: No

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Automatic Semantic Segmentation of Breast Tumors in Ultrasound Images Based on Combining Fuzzy Logic and Deep Learning – A Feasibility Study

PONE-D-21-09994R1

Dear Dr. GadAllah,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Thippa Reddy Gadekallu

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors have addressed my suggestions. I would like to accept this paper.

The authors have addressed my suggestions. I would like to accept this paper.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No