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Article
Peer-Review Record

ChroSegNet: An Attention-Based Model for Chromosome Segmentation with Enhanced Processing

Appl. Sci. 2023, 13(4), 2308; https://doi.org/10.3390/app13042308
by Xiaoyu Chen 1, Qiang Cai 2,*, Na Ma 2,* and Haisheng Li 1
Reviewer 1: Anonymous
Reviewer 2:
Appl. Sci. 2023, 13(4), 2308; https://doi.org/10.3390/app13042308
Submission received: 23 December 2022 / Revised: 1 February 2023 / Accepted: 2 February 2023 / Published: 10 February 2023
(This article belongs to the Special Issue AI-Based Biomedical Signal Processing)

Round 1

Reviewer 1 Report

The grayscale conversion formula is standard and seemed to be redundant to be included.

in equation 2, how b was determined? setting everything above 255 to 255 may cause washed out images in saturated region. How would that impact image quality.

section 3.1.2, how would images underwent different data enhancement be distributed. Are there even number of each category?

Is the unique feature for ChroSegnet having more subsampling and convolution layers, apart from conventional attention based U-net? I feel the description of network architecture could be improved/condensed to more clearly state its new features.

I feel there is little need to include equation 4, 5, 6, because these are standard metrics.

 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report


Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.docx

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