Comments (6)
xmengli
commented on July 16, 2024
What is your result?
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Apple-zly
commented on July 16, 2024
What is your result?
Hello,
The test result is submitted in the codalab
lesion_dice_global: 0.732
lesion_dice: 0.76
lesion_dice_per_case: 0.645
liver_dice_global: 0.899
liver_dice: 0.903
liver_dice_per_case: 0.903
Looking forward to your reply！
Thank you very much
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Williamwsk
commented on July 16, 2024
What is your result?
Hello,
The test result is submitted in the codalab
lesion_dice_global: 0.732
lesion_dice: 0.76
lesion_dice_per_case: 0.645
liver_dice_global: 0.899
liver_dice: 0.903
liver_dice_per_case: 0.903Looking forward to your reply！
Thank you very much
When I run the step 5, the training loss is bigger than 0.05. I am still trying to get the final result. Can we discuss through email or qq,[email protected].
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AshStuff
commented on July 16, 2024
Hi, we ran into the same result - has anyone figured out the source of the discrepancy? Perhaps there's a change in implementation?
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Kyfafyd
commented on July 16, 2024
What is your result?
Hello,
The test result is submitted in the codalab
lesion_dice_global: 0.732
lesion_dice: 0.76
lesion_dice_per_case: 0.645
liver_dice_global: 0.899
liver_dice: 0.903
liver_dice_per_case: 0.903Looking forward to your reply！
Thank you very much
Hi! How do you evaluate dice?
Can you please provide some scripts?
Thanks!
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Apple-zly
commented on July 16, 2024
LiTS 2017 Challenge submission
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kemgine_zly
邮箱：[email protected]
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Signature is customized by Netease Mail Master
On 04/07/2020 10:07, Kyfafyd wrote:
What is your result?
Hello,
The test result is submitted in the codalab
lesion_dice_global: 0.732
lesion_dice: 0.76
lesion_dice_per_case: 0.645
liver_dice_global: 0.899
liver_dice: 0.903
liver_dice_per_case: 0.903
Looking forward to your reply！
Thank you very much
Hi! How do you evaluate dice?
Can you please provide some scripts?
Thanks!
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Related Issues (20)
- keras.layers.input batch_shape 最基本問題 HOT 1
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- About generate livermask HOT 1
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