Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

somet question about label value #2

Open
songwaimai opened this issue Nov 23, 2019 · 9 comments
Open

somet question about label value #2

songwaimai opened this issue Nov 23, 2019 · 9 comments

Comments

@songwaimai
Copy link

Hello, I have changed your program, and it can run smoothly without any error. However, I have observed that the value of label does not seem to be passed in. May I ask if there is such a problem in your program.

@MinaRe
Copy link
Member

MinaRe commented Nov 23, 2019

Please check the load image sequence in utils.py, indeed each 3d Seg0,1,2 has corresponded to the segmentation region!

@songwaimai
Copy link
Author

thanks! Actually, I use the iseg2017 dataset, maybe the format of label is different. which dataset do u use??

@MinaRe
Copy link
Member

MinaRe commented Nov 23, 2019

I applied this code for LiTS2017, ACDC 2017, BraTS 2015-2019 and ,... for semantic segmentation, in order to get a better result I would recommend changing loss_weights = [10, 1] in train.py and adding a complementary label in the training time.

@songwaimai
Copy link
Author

Thanks very much! I will try it~

@MinaRe
Copy link
Member

MinaRe commented Nov 23, 2019

CL

@MinaRe
Copy link
Member

MinaRe commented Nov 23, 2019

and weight must be adjusted regarding the imbalanced ratio and/or difficulties of training ....

@songwaimai
Copy link
Author

so kind of u~ do you have published the related article? Would you mind sending me the name of your article or the link for me to learn about...

@songwaimai
Copy link
Author

Also, I wonder if the data sets you use have multiple labels? label of iseg 2017 is only one corresponded to one T1 and one T2 of a subject, so i want to know how each to process can make 3d Seg0,1,2 has corresponded to the segmentation region?

@MinaRe
Copy link
Member

MinaRe commented Nov 23, 2019

Nice, in this case (http://iseg2017.web.unc.edu/files/2019/02/Benchmark-on-Automatic-6-month-old-Infant-Brain-Segmentation-Algorithms.pdf) I would solve the segmentation (which is not imbalanced) with probabilistic 3D GAN, which is similar to this code but you need to add 2 prior losses for T1 and T2 and dropout in the generator.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants