Venue: MICCAI 2021 Challenge KiTS

Reviews:

final_score: rating: 9: Top 15% of accepted papers, strong accept
review_content: This paper does an excellent job at providing an in-depth explanation of the approach used by this team for their submission. The authors also make effective use of figures and tables to improve clarity and support their arguments. I have no complaints or comments other than to request that the authors add their final results once they are known.
review_title: Official Review

final_score: rating: 8: Top 50% of accepted papers, clear accept
review_content: The authors present a transformer-based approach to the problem that they have termed COTRNet. The paper does a great job explaining it in detail, but one crucial detail is missing. How were the multiple annotations per instance aggregated in order to produce composite masks that were then used for training and validation? Most teams used majority voting (aggregated_MAJ), is this what you used as well? This should be made clear within the manuscript.
review_title: Official Review

Meta-review: Please address the reviewer comments and resubmit
Decision: Minor Revisions