Next Article in Journal
A Data-Driven Machine Learning Approach for Corrosion Risk Assessment—A Comparative Study
Previous Article in Journal
AI Governance and the Policymaking Process: Key Considerations for Reducing AI Risk
 
 
Article
Peer-Review Record

Automatic Human Brain Tumor Detection in MRI Image Using Template-Based K Means and Improved Fuzzy C Means Clustering Algorithm

Big Data Cogn. Comput. 2019, 3(2), 27; https://doi.org/10.3390/bdcc3020027
by Md Shahariar Alam 1,†, Md Mahbubur Rahman 1,†, Mohammad Amazad Hossain 2,†,‡, Md Khairul Islam 3,†, Kazi Mowdud Ahmed 1,†, Khandaker Takdir Ahmed 1,†, Bikash Chandra Singh 1,4,† and Md Sipon Miah 1,*,†,‡
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Big Data Cogn. Comput. 2019, 3(2), 27; https://doi.org/10.3390/bdcc3020027
Submission received: 3 April 2019 / Revised: 28 April 2019 / Accepted: 30 April 2019 / Published: 13 May 2019

Round  1

Reviewer 1 Report

This paper describes a novel approach for brain tumor detection in MRI images.

The paper is interesting; however, there are several grammatical errors, long sentences or sentences which are very hard to understand or repeated sentences. Therefore, I suggest to carefully revise the paper.

The parameters and the notation used in the text is summarized in table 1, before introducing the main concepts of the paper. I suggest to explain the notation when the related equations are introduced in the paper. Moreover, the “Meaning” column gives information about the notation with different styles (sometimes the description is a single word, sometime a sentence).

Concerning the algorithms description (Section 3), I suggest to insert a pseudocode or to better explain the steps. As an example, for the K-means algorithm, it is not specified that the distance between centroids could be evaluated with different metrics, such as Manhattan distance. Moreover, it is not described how the convergence is evaluated (is there a threshold or a maximum number of iterations?). Another important point is about the quality of clustering: typically, the K-means is repeated several times with different initializations in order to identify the best centroids. Did the authors perform this?

On page 6 and 7 authors described six features that they extracted. How have these features been chose?

The figure 1 is blurred; moreover, it is not a standard flow chart because the START and STOP blocks are missing.

On page 11 authors give information about the time comparisons. The last sentences of the page should be changed avoiding expressions like “Software=MATLAB2016a”. Finally, the expression “Windows=Windows10” is not correct, Windows is an operating system, thus, it should be “Operating system=Windows 10”, but, again, I suggest to avoid this notation.


Author Response

Dear Reviewer,

I wonder if could you find attachment....

Best regards

Md Sipon Miah

Author Response File: Author Response.doc


Reviewer 2 Report

The following revision are needed to be made:

(1.) Page 1 and Page 2:  First paragraph in Introduction needs to be subdivided into smaller paragraphs to make more comprehensible. This single paragraph extends from bottom of page 1 to over half of page 2 in a single paragraph. It is difficult to read and comprehend and also not an attractive start of the paper that would plan to attract readers.

(2.) Page 2 send to last line: "The rest of this paper is presented as follows:" should be reworded such as "The following parts of paper are presented as follows:"

(3.) Page 3 last paragraph and Page 4: This paragraph is starts on bottom of page 3 and extends to almost middle of page 4 and is too long and difficult to read and comprehend. It needs to be subdivided into smaller paragraphs so that is comprehensible.

(4.) Page 4 8th line form end of last paragraph of section 2: "Now a days, ANN is one of the most" should be reworded as "ANN is currently one of the most ..."

(5.) Page 10 Figure 2: Title of part (b) need to be in same format of the title of part (a) and should appear as "(b) Database 2" instead of "(b) The Database 2".

(6.) Page 14 section 6 line 2:  two words are missing so that "Moreover, this algorithm is shown that is an optimum than the conventional schemes" needs to be re-worded as "Moreover, this algorithm is shown that it is an optimum over the conventional schemes".

(7.) Pages 15, 16 and 17: The references of titles of Conference Proceedings need to be appear in Italics and also the wording of "Proceedings of" need to appear in these titles. References 18 and 35 have "Proceedings of" in the titles but References 5, 9, 24, 26, 39, 49, 42 and 43 do not.

(8.) A final note to the authors is that this paper needs a careful editing of wording and other possible revisions to make submission in a final form that is comprehensible by the readers, and all References in correct format.


Author Response

Dear Reviewer,

I wonder if could you find attachment....

Best regards

Md Sipon Miah

Author Response File: Author Response.doc


Reviewer 3 Report

There are many grammar mistakes and typos. Sufficient improvement is required. 

Euclidian -> Euclidean.

Punctuation marks are missing at the end of expressions.

Please provide extended explanations for Tables 2&3.

Authors need to write the Conclusion section with a focus on both an impact and insights of the manuscript. Please state clearly your unique research contributions in the Conclusion section.

Some more explanation is required for eq.(6). The members 2 and 3 are generally the same. Then you offer to multiply d^2 by d^2. I am getting lost here. Does this procedure have any geometrical sense? What is the final output range of the objective function? Please give as many details as possible.


Author Response

Dear Reviewer,

I wonder if could you find attachment....

Best regards

Md Sipon Miah

Author Response File: Author Response.doc


Round  2

Reviewer 1 Report

Authors successfully addressed all my comments.


Reviewer 3 Report

My comments have been considered. I see no objections why this paper cannot be accepted now.

Back to TopTop