miccaiif / DGMIL

Official PyTorch implementation of our MICCAI 2022 paper: DGMIL: Distribution Guided Multiple Instance Learning for Whole Slide Image Classification.
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Inquiry Regarding FROC Score Calculation #10

Closed Alireza-Alipanah closed 8 months ago

Alireza-Alipanah commented 9 months ago

We have encountered challenges in replicating the FROC score calculations. To ensure accuracy and consistency, we would greatly appreciate your assistance with the following inquiries:

If not could you please guide us on:

miccaiif commented 8 months ago

We have encountered challenges in replicating the FROC score calculations. To ensure accuracy and consistency, we would greatly appreciate your assistance with the following inquiries:

  • Could you kindly provide us with the complete pipeline code you used to calculate the FROC score?

If not could you please guide us on:

  • How did you determine the coordinates of the points used in the calculations?
  • If clustering was involved in the selection of coordinates, could you elaborate on the process? For instance, did you extract the count of clusters from the XML file containing tumor region coordinates before doing the clustering on model probability scores? Additionally, was the center of each cluster chosen for calculations?
  • Could you specify the number of coordinates you chose for the FROC score calculations (or if it's not constant how you choose this number)?

Thank you for your question. It seems that calculating FROC (Free-response Receiver Operating Characteristic curve) is a rather difficult and tedious task. You can refer to the repository at https://github.com/fpgdubost/FROC-Free-response-Receiver-Operating-Characteristic-curve and explore the examples provided there. Thank you!