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Article
Peer-Review Record

Multi-Stage Platform for (Semi-)Automatic Planning in Reconstructive Orthopedic Surgery

J. Imaging 2022, 8(4), 108; https://doi.org/10.3390/jimaging8040108
by Florian Kordon 1,2,3,*, Andreas Maier 1,2, Benedict Swartman 4, Maxim Privalov 4, Jan Siad El Barbari 4 and Holger Kunze 1,3
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
J. Imaging 2022, 8(4), 108; https://doi.org/10.3390/jimaging8040108
Submission received: 28 February 2022 / Revised: 5 April 2022 / Accepted: 8 April 2022 / Published: 12 April 2022

Round 1

Reviewer 1 Report

This work shows how difficult semiautomated is as the author’s show that the proximal tibia could not be segmented reliably, whereas the distal femur could.  The authors also were noting that positioning was often difficult and time consuming.  These honest observations are extremely helpful.  Oftentimes papers attempt to prove they have solved all problems.  The authors do the subject a significant favor by “showing where the holes are” and where to direct future research attention.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

Dear Authors,

After reviewing your article I found it interesting and I think it can be interesting to Journal's readers. However, some minor revisions are recommended. Please see the attached document for details.

Kind regards,

Reviewer

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 3 Report

Very interesting work:

I have just one remark:

Please depict in details the best architecture of your deep learning system, i.e. number of layers, nodes etc.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

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