I am trying to understand the code and have read the research paper, which states that when using the cascading model, voxels from CNN1 are supposed to be thresholded and then fed to CNN2. Specifically, the paper mentions that "the mean of 20 forward passes (or predictions) was thresholded at >0.1 (equivalent to rejecting bottom 10 percentile probabilities); voxels surviving this threshold served as the input to sample patches for CNN-2."
However, I have been unable to find the code for this thresholding operation in the train.py and base.py (train_mode()l method) file.
I would appreciate it if someone could help me locate this code or provide further information on how it is implemented.
Additional information:
I have read the research paper and the relevant sections of the code.
I have searched for the relevant keywords in the code, but I have not been able to find the specific code for the thresholding operation.
Description
I am trying to understand the code and have read the research paper, which states that when using the cascading model, voxels from CNN1 are supposed to be thresholded and then fed to CNN2. Specifically, the paper mentions that "the mean of 20 forward passes (or predictions) was thresholded at >0.1 (equivalent to rejecting bottom 10 percentile probabilities); voxels surviving this threshold served as the input to sample patches for CNN-2."
However, I have been unable to find the code for this thresholding operation in the train.py and base.py (train_mode()l method) file. I would appreciate it if someone could help me locate this code or provide further information on how it is implemented.
Additional information: