Comments (2)
Hello,
I think you have to firstly train the model to obtain a snapshot, which will be automatically saved in filefolder such as ''../model/TU_Synapse224/TU_pretrain_R50-ViT-B_16_skip3_bs24_224/'. Afterwards, run the test.py, where the snapshot will be loaded to network and testing data will be inferenced by the network.
Secondly, I don't know if you downloaded the correct dataset in Synapse official website, where some files displayed there are not the multi-organ dataset we used. Instead, you have to sign up first and then a filefolder called as abdominal should be the multi-organ dataset. There is an alternative way that you can send an Email to jienengchen01 AT gmail.com to request the preprocessed data.
The reason why we need to clip an orignal CT image is that the HU value in CT images will range from [-1000, 2000] with many redudant information..
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Hello Beckschen,
thank you for your detailed response, I really appreciate it.
I found the Abdomen folder after all.
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Related Issues (20)
- Different input size (width x height)
- Reason for [-125, 275] input clipping
- "ZeroDivisionError: integer division or modulo by zero" when vit_patches_size=8 HOT 3
- Need R50+ViT-B_16 rather than R50-ViT-B_16!
- 当我在运行TransUNet-main的train.py时出现错误:KeyError: 'Transformer/encoderblock_0/Multi5HeadDotProductAttention_1/query/kernel is not a file in the archive' 这是在我进行KeyError: 'Transformer/encoderblock_0/MultiHeadDotProductAttention_1/query\\kernel is not a file in the archive'后的更改出现的错误,csdn说这是os.path.join 合并路径的时候出现的问题,更改后仍然出现以上错误 HOT 3
- Even if we fix the seed, the results change for each training.
- asking for you help
- ACDC dataset 100 cases of data
- Training for three-channel dataset
- Need R50+ViT-L_16 pretrained model rather than R50+ViT-L_32 HOT 1
- 导入包报错,文件夹重名导致的坑 HOT 2
- Data preprocessing HOT 2
- Training with different image size HOT 1
- Is the Synapse multi-organ segmentation dataset experimental result obtained from is the 20 samples official test set?
- change patch_size during test
- PreActBottleneck
- Training performance issues on small-sized targets
- The issue arises from the absence of the "lists_Synapse" folder.
- ACDC dataset
- About the solution of problems like "have 3 channels, but got 1000 channels instead"
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