Closed meegoStar closed 4 years ago
Hi, this is our solution writeup. We have three pipelines for single 2D CNN training (3 different preprocessing methods). The uploaded code is one of the three which only applies the 2nd preprocessing method (Spatially adjacent 3 slices with one window). You can get similar performance with the other two preprocessing methods. Ensemble of the three pipelines can give you a boost on final score.
Got it. Thank you very much!!!
Hi, thanks for sharing your great work. According to your README, brain, subdural, & bone windows are used when preprocessing dicoms to pngs.
But in prepare_data.py, it seems that window parameters are extracted from dicoms' metadata, no explicit windows given. And in dataset.py, s-1, s, s+1 images are simply loaded, concatenated, applied data augmentation, no other preprocessing introduced. So I just wonder are brain, subdural, & bone windows actually used?