Content of review 1, reviewed on December 08, 2020

Comments on abstract, title, references

  1. In the title, the word "Empowered" is not completely representing the main aim of the authors, it should be more clearly represented to show the readers that this review is only based on a deep learning-based method.

  2. Abstract is not a good place to discuss the overall background of the area. Mention these in your abstract: Problem (why this work is needed) -> your solution (how you solve the current problem/your contributions) ->what kind of results you got (in terms of the survey, how it will help others to contribute to this area).

Comments on introduction/background

  1. What are the main contributions of this survey, how this survey is different from others, I did not see any convincing contribution.

  2. There are many facts and figures without any reference i.e., Figure 3.

Comments on methodology

  1. The authors provided a thorough review of the existing methods, however, I did not find the review of existing surveys. The authors need to add a detailed section related to existing surveys and compared their survey that how it is novel from them.

  2. Table 1 is too diverse; the authors need to divide the methods based on datasets as they mentioned taxonomy in their title.

  3. In Table 1, if the methods do not mention their data source and acquisition method, why the authors include them in the dataset table?

Comments on data and results

  1. The authors need to divide the methods based on segmentation, classification, and evaluation, etc. as their main aim is a review with taxonomy.

  2. Most of the figures are of very low quality even it is difficult to read the text.

Comments on discussion and conclusions

  1. The future directions mentioned in the paper are not completely clear and explained very well. As mentioned in the abstract their main focus is on presenting a thorough review, taxonomy, and future challenges. Their findings and future challenges should be divided into segmentation, classification, and evaluation, etc. to guide the researchers intended to work in a specific area.

Source

    © 2020 the Reviewer.

References

    Waqas, N. M., Al, G. M. A., Muzammil, H., Adnan, K. M., Masood, K. K., H., A. S., Ashfaq, B. S. 2020. Brain Tumor Analysis Empowered with Deep Learning: A Review, Taxonomy, and Future Challenges. Brain Sciences.