Closed wonkicho closed 6 months ago
Additional, Is it possible to generate new data accurately according to the segmentation mask? Or does the mask only serve as a reference in the generative reasoning process? I am curious about this part because it seems to be created in the same position according to the mask while checking after learning, and some are not.
Sorry for interupt your time. Thanks!
Hello, Thank you for your questions! I'm happy to help. I'll try to answer one at a time.
segmentations
folder in https://drive.google.com/file/d/1yaLLdzMhAjWUEzdkTa5FjbX3d7fKvQxM/view) have all breast, dense tissue and blood vessel segmentations for the corresponding real images. However, please note that some slice images that have breast segmentations do not have any dense tissue and/or blood vessels (the segmentations are not incomplete, those objects are just not in all slices). Maybe that's why you're not seeing any vessels?thanks to fast reply from my question! i understood your description. On question 3, The direction of inference I'm expecting is whether i can create a new style depending on the part of the mask when i give a mask with the desired shape as an input value (Ex. figure2 in your paper input mask ane Seg-Diff output Pair) if possible, can i get some train parameters?
Thanks and sorry to ask a lot
Hi, I'm still not sure that I get your question, but to try to answer: once the model is trained, it will generate an image that accurately follows an input mask, even if the input mask is totally new/unseen in training (which is why we evaluate on masks from the test set, e.g. in figure 2).
Check out the pretrained model parameters here: https://github.com/mazurowski-lab/segmentation-guided-diffusion?tab=readme-ov-file#2b-train-your-own-models.
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Thanks for kindly reply!! i understood about that. if i have more questions after, i will ask!!!
Thank you~~
Thanks for your interesting works! i have two questions about your work.