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CityU-AIM-Group / D2Net

[TMI' 22] D2-Net: Dual Disentanglement Network for Brain Tumor Segmentation with Missing Modalities
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Inquiry about D2Net for Brain Tumor Segmentation on BraTS2018 Dataset #4

Open MaggieLSY opened 1 year ago

MaggieLSY commented 1 year ago

I hope this email finds you well. I am currently working on applying missing modality models for brain tumor segmentation, and I have some questions regarding your experiments on the BraTS2018 dataset. I hope you don't mind sharing some details with me.

  1. Having carefully studied the U2NET paper, I found the section on the three-fold data partitioning particularly intriguing. To further explore this aspect, I kindly request if you could provide me with the list that outlines the specific division of data into three folds. This information would greatly enhance my understanding of the experimental setup and facilitate my own research.

  2. While reading the paper, I noticed that the authors mentioned the use of three-fold cross-validation. However, the reported results consist of a single value rather than the more conventional form of mean and standard deviation. I am curious to know how the performance metric was calculated and whether it represents an average value across the three folds.

Your valuable insights into these inquiries would be immensely helpful to me. I greatly appreciate your time and effort in addressing my questions. Thank you in advance for your kind assistance.

MaggieLSY commented 1 year ago

Sorry, I just spelled incorrectly, it should be D2Net instead of U2NET. I would like to ask about the details of D2Net. Can you send me the data split in the D2Net paper and how the dice calculation of three-fold cross validation is calculated?