Venue: MIDL 2023 Short_Paper_Track

Reviews:

final_score: rating: 5: Marginally below acceptance threshold
review_content: This paper proposed a landmark localization approach for post-surgical evaluation of total knee replacement. The approach incorporates dilation and erosion operations and a reweighting scheme in the training process to improve a Unet-based baseline prediction.  Drawbacks of the proposed method is that (1) description of the dilation/Erosion label augmentation method is unclear. The author need to provide more details regarding the dilation and erosion operations; (2) the baseline methods in the experiment are not the state-of-the-art methods, the author may find this paper is useful:

Yao, Qingsong, et al. "One-shot medical landmark detection." Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th International Conference, Strasbourg, France, September 27–October 1, 2021, Proceedings, Part II 24. Springer International Publishing, 2021.

I’d like to suggest the author to compare their method with other state-of-the-art medical landmark localization approaches. In addition, it is better to illustrate what the 6 anatomic landmarks look like.

review_title: Review

final_score: rating: 8: Top 50% of accepted papers, clear accept
review_content: Nice paper, cool application

Interesting and novel technical contribution, based on dilating and eroding segmentation labels during the training process

Is of interest to the community
review_title: interesting method and application

Decision: Accept(Poster)