Dear Metric Reloaded Team,
I have worked with Brain metastases data, and I was confused when I evaluated lesion-wise (instance-level) detection metrics (F1 -score) from predicted segmentation. Currently, I match each lesion if there is overlap, or overlap(DSC) > 0.1. And I observed that there are quite multiple assigned cases in both ways (one pred - multiple GTs, multiple pred - one GT). That's how I visit your great work (Metric Reloaded) to get some guidance.
I have briefly checked resolve ambiguity code, but I'm still not sure whether this code also treat the remained GTs as FN or ignore them. Or counting TPs is always based on GTs?
I illustrated this issue with the image in the below repository as well, since I used their code.
rachitsaluja/BraTS-2023-Metrics#11
Dear Metric Reloaded Team,
I have worked with Brain metastases data, and I was confused when I evaluated lesion-wise (instance-level) detection metrics (F1 -score) from predicted segmentation. Currently, I match each lesion if there is overlap, or overlap(DSC) > 0.1. And I observed that there are quite multiple assigned cases in both ways (one pred - multiple GTs, multiple pred - one GT). That's how I visit your great work (Metric Reloaded) to get some guidance.
I have briefly checked resolve ambiguity code, but I'm still not sure whether this code also treat the remained GTs as FN or ignore them. Or counting TPs is always based on GTs?
I illustrated this issue with the image in the below repository as well, since I used their code.
rachitsaluja/BraTS-2023-Metrics#11