Comments (3)
During training and inference, we directly standardized original 12-bit integer values without rescaling the images to 0-255 range. The images have values typically in the 0-4095 range. We did not apply any preprocessing that is not mentioned in the paper. Depending on the manufacturer, their proprietary preprocessing algorithms may have been applied in the images.
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If I remember correctly, all valid mammograms we have were within the 0-4095 range.
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Thank you for the quick response! Regarding the following:
The images have values typically in the 0-4095 range.
Can you please clarify: does this mean that some images had values outside this range? If so, do you know approximately how many, and in which ranges?
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Related Issues (13)
- When I used the parameters you provided and the pre-trained model, I used the DDSM data set to fine-tune the network, but the AUC value was 0.5. I wonder why the results in your paper could not be reached
- Could I use the models you provide to retrain my data set directly? HOT 1
- PyTorch model has two-views instead of four? HOT 2
- Birads 3 Categories HOT 5
- dataset HOT 1
- Source code HOT 1
- How can I use your model to train my data set and look forward to your reply HOT 1
- How can I use your model to train my data set HOT 1
- Is the model in this code a trained model, and where is its weight saved HOT 1
- Can the code of your training network be published HOT 1
- How is your training data distributed when you train the network HOT 1
- When training the network, what's your batch number? How do you input n times 4 images into the network for training
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