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We tried to recreate your pretrained model in: [Link](https://github.com/mlmed/torchxrayvision/releases/download/v1/nih-pc-chex-mimic_ch-google-openi-kaggle-densenet121-d121-tw-lr001-rot45-tr15-sc15-s…
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thank you for the very useful library!
I was wondering if the pre-trained DenseNet on the NIH dataset was trained on the official train split provided here: https://nihcc.app.box.com/v/ChestXray-NIH…
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* https://arxiv.org/abs/1909.01940
* 2019
ディープラーニングモデルが普及する一方で、目に見えないデータを扱い、どのようなシナリオに対しても一般化する能力はまだ課題となっています。
医用画像処理では、画像を生成する機器やそのパラメトリック化によって、画像間の分布に高い不均一性がある。
この不均一性は、ドメインシフトと呼ばれる機械学習における共通の…
e4exp updated
4 years ago
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Hello, I guess you're maintaining the [torrent file](https://academictorrents.com/details/e0aeda79626589f31e8bf016660da801f5add88e) of PadChest resized (224x224) images referenced from the `dataset.py…
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Hi,
I started playing with your cool package and wanted to make sure I follow. How do I work with the output of the final linear layer of the kaggle model?
if
`model = xrv.models.DenseNet(weigh…
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I have several questions:
1- how many images are available in total?
2- if the protocol is 10 fold cross validation why there are only 9 files in the balanced-tsv folder? I guess that files insi…
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Hello,
First of all thanks a lot for the effort you are putting to gather all these xray and ct measurements!
I am wondering if bounding box/masks for the detection of problematic regions can be…