Comments (4)
Hi @nikku1234 , sorry for my late response.
You can use asyndgan_model https://github.com/tommy-qichang/AsynDGAN/blob/master/models/asyndgan_model.py#L112 for training and pix2pix_model for testing since you just neet the generator.
Also, please notice to change the discriminator number in the model file. for instance:
AsynDGAN/models/asyndgan_model.py
Line 112 in 767b20d
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Okay, thanks! My doubt was did you guys use MASK-RCNN for the segmentation process, for nuclei?
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@nikku1234 The synthetic dataset was generated using the code @tommy-qichang mentioned. After that, we used U-net instead of Mask-RCNN for nuclei segmentation on the synthetic dataset. Training details can be found in Section 4.2 of the paper.
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Okay, thanks @huiqu18 and @tommy-qichang !
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Related Issues (15)
- 请教测试结果如何重建为3d 图像? HOT 1
- Segmentation process HOT 4
- 10 subsets HOT 2
- Testing the BraTS Dataset HOT 1
- Some questions about practical applications HOT 6
- data HOT 3
- 测试的具体细节 HOT 2
- How to build this work amongs differents institutions? HOT 1
- Could you give me a training process? Thank you HOT 3
- The data processing HOT 7
- Questions about test HOT 3
- Can you provide pre-trained generator on BraTs 2018 dataset? HOT 2
- preprocess data HOT 1
- Nuclei dataset preprocessing HOT 2
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