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DragonDescentZerotsu / SSM-SAM

Code for WACV 2024, Self-Sampling Meta SAM: Enhancing Few-shot Medical Image Segmentation with Meta-Learning
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Result in Liver case #4

Open UreMine02 opened 1 month ago

UreMine02 commented 1 month ago

I don't know why my model reaches your performance in LK, RK, and Spleen. But in Liver, it's surprisingly low

DragonDescentZerotsu commented 1 month ago

In my memory, Liver should be the easiest to train, since it's bigger and has clearer boundaries. Try checking your dataset to see if the images are arranged as I instructed in the Readme. Maybe there are out-of-order images leading to the undesired performance on Liver.

In another word, there maybe query images and support images not matching each other in your dataset.

Best,

Tianang

UreMine02 @.***> 于 2024年6月24日周一 10:49写道：

I don't know why my model reaches your performance in LK, RK, and Spleen. But in Liver, it's surprisingly low

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