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xmengli / H-DenseUNet

TMI 2018. H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes
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a question about result #46

Open Apple-zly opened 5 years ago

Apple-zly commented 5 years ago

hello, author. I run the whole code, the result is not same as your result in the paper and competition. I want to know what improvements you have made.

Looking forward to your reply！ Thank you very much

xmengli commented 5 years ago

What is your result?

Apple-zly commented 5 years ago

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

Williamwsk commented 5 years ago

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

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,1069582001@qq.com.

AshStuff commented 4 years ago

Hi, we ran into the same result - has anyone figured out the source of the discrepancy? Perhaps there's a change in implementation?

Kyfafyd commented 4 years ago

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!

Apple-zly commented 4 years ago

LiTS 2017 Challenge submission

kemgine_zly 邮箱：kemgine_zly@163.com

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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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