Dear Dr. Saladi,

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.

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• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

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We look forward to receiving your revised manuscript.

Kind regards,

Ananth JP

Academic Editor

PLOS ONE

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Additional Editor Comments (if provided):

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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?

Reviewer #1: Yes

Reviewer #2: Yes

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

Reviewer #1: N/A

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

Reviewer #1: Yes

Reviewer #2: Yes

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

Reviewer #1: No

Reviewer #2: No

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Reviewer #1: The article on brain tumor segmentation using fused MRI-PET images and a modified U-Net framework is commendable. The integration of PCA for fusion and the comprehensive U-Net architecture is methodically laid out.

Here are some suggestions to strengthen your paper:

Clarify the term "Permutate U-Net" – What exactly is being permutated? Currently, the paper does not justify this terminology.

Please improve the language and grammar throughout the manuscript. Several sections are hard to follow due to sentence construction errors.

Include model complexity analysis – number of parameters, inference time, and training duration.

Consider using cross-validation or at least testing on an external validation set.

In comparative results, ensure that benchmarks are done on the same datasets. Add statistical tests to validate the improvements.

Visual fusion comparisons across methods (not just quantitative) would enhance understanding.

Some figures (especially block diagrams) could be redrawn for clarity and better resolution.

Reviewer #2: The title should be revised to include specific and detailed information reflecting the core contribution of the paper.

Keywords should be arranged in alphabetical order for clarity and consistency.

Avoid the use of first-person pronouns such as "our" and "we" to maintain an objective academic tone.

Ensure all sections are properly numbered. For example, "Contribution of the Proposed Work" should be listed as Section 2.

Maintain consistency and clarity in section headings throughout the paper.

The paper currently lacks a clear structure and reads more like lecture notes; a more formal academic organization is recommended.

The literature review section should incorporate recent research developments, as its current form lacks coverage of contemporary studies. Without a comprehensive and up-to-date survey, the novelty and relevance of the proposed work are significantly compromised.

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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.

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Reviewer #1: No

Reviewer #2: Yes:  Dr.Jasneet Kaur

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Brain Tumour Segmentation in Fused MRI-PET Images With 

 Permutate U-Net Framework

PONE-D-25-25213R1

Dear Dr. Saladi,

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.

An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager®  and clicking the ‘Update My Information' link at the top of the page. For questions related to billing, please contact billing support .

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Ananth JP

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

Reviewer #3: All comments have been addressed

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

Reviewer #1: Yes

Reviewer #3: Yes

**********

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

Reviewer #1: N/A

Reviewer #3: Yes

**********

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

The PLOS Data policy

Reviewer #1: Yes

Reviewer #3: Yes

**********

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

Reviewer #1: Yes

Reviewer #3: Yes

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Reviewer #1: The authors have clearly indicated that all datasets used in this study are publicly available and have provided appropriate links to open repositories

Reviewer #3: General Comments:

The authors present a well-designed and systematic approach to brain tumour segmentation using a novel Permutate U-Net architecture. The paper is technically sound, clearly written, and well-supported by quantitative evidence. The combination of PCA-based image fusion and modified U-Net structure demonstrates notable improvement over traditional U-Net and CNN models. The methodology, dataset description, and comparative results are thorough and well-documented.

Specific Comments for Minor Revision:

Please clarify how the permutation or modification of the U-Net differs structurally from Dense U-Net or Residual U-Net—this will help emphasize novelty.

Include a brief computational complexity or inference-time comparison between the proposed model and baseline U-Net.

Provide a short description of limitations or potential future improvements in the Conclusion section to strengthen the academic tone.

Ensure that all dataset citations are standardized with their DOIs or persistent links.

Proofread minor grammatical errors and unify capitalization in figure captions (e.g., “Figure 9 Segmented tumour region…”).

Overall Recommendation:

The manuscript is technically strong and contributes meaningfully to brain tumour segmentation research. It meets the PLOS ONE publication criteria, with only minor revisions recommended before acceptance.

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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

Reviewer #3: No

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