Discrimination of the Skin Cells from Cellular-Resolution Optical Coherence Tomography by Deep Learning

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

please see the attachment.

Comments for author File: Comments.pdf

Author Response

Thanks for your comments.

Please see the attached file.

 

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript titled “Discrimination of the skin cells from cellular-resolution optical coherence tomography images by deep learning” by Jui-Yun Yi et al proposed four models to classify the images of five types of 2D-OCT skin cells. keratinocyte (HaCaT cell line), melanocyte, squamous cell carcinoma cell line and 2 melanoma cell lines were well recognized by their deep learning method. I think this work is interesting as it can automatically differenticate types of cells, enabling a time-effective and precise cell recognition. Overall, I would recommend its publication after some minor revisions, to follow:

1) In the OCT system development part, I would sugget the authors to provide more information of the used system, such as the axial resolution and lateral resolution. Especially, the lateral resolution would definitely influence the predicting results in the deep learning method. So the NA, magnification of the objective should be provided in the manuscript;

2) In Table 1, what does the “parameters” mean? It is sort of confusing, the authors should clarify them;

3) In Figure 8, the labels are too small to read. Would be better if the authors make it more clear;

4) For the heated maps of the 5 types of cells, I am not sure why the authors put these results here? Will the heated maps improve the discrimination accuracy?

Author Response

Thanks for your comments.

Please see the attached file.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

I have no further comments.

Author Response

Dear Reviewer,

In round 2, I see no further comments and no more questions.  

Is that right? 

Best regards.

Jui-Yun Yi