tutorial on occlusion sensitivity

[robsver]

Hi everyone,
I’ve been trying to run the 3D classification example based on the DenseNet tutorial on occlusion sensitivity (from tutorials/3d_classification/densenet_training_array.ipynb), as mentioned in Project-MONAI/tutorials#1971 with @ericspod.

It seems like the notebook might not be running as expected on my end. I might be missing something too, so I’d really appreciate any suggestions or guidance you might have!

Thanks a lot in advance :) !

[ericspod]

Hi @KumoLiu @Nic-Ma I think the issue is that monai.visualize.OcclusionSensitivity has different expectations of what's going on internally. In older versions of MONAI the tutorial worked so some code change or assumption is different now, perhaps how we're doing sliding window is now different.

[robsver]

Hi there! Sorry for bothering you, I was wondering if you had any updates on the issue mentioned above.
Take your time, I really appreciate it.

Thanks a lot! 😄

[kavin2003]

Hi robsver,I'm interested in this issue, I just checked the code implementation of version 0.7.0 against the current version and I think it's the small overlap of the current siliding window that's causing the issue, I think you can simply add occ_sens = monai.visualize. OcclusionSensitivity(nn_module=model, mask_size=32, n_batch=10) by adding a parameter occ_sens = monai.visualize. mask_size=32, n_batch=10,overlap=0.75) to solve this problem, hope it helps!

[ericspod]

Hi @kavin2003 thanks for looking into this. @robsver would you please look at the PR and try things on your end with the changed overlap value? I think it looks good so it can be merged if you're happy with the results. Thanks!

[robsver]

Hi @kavin2003, Thank you so much! I really appreciate your help. I'm almost certain the different activation is due to the short training performed for the tutorial, and that it has learned to distinguish other features.

But now it definitely makes sense!!

Thanks a lot @kavin2003 and @ericspod for your time!

[ericspod]

I have merged the change now so if we've resolved the expected behaviour we can close this issue as completed now. Thanks all!

[PARODBE]

Hi @ericspod, I’m running your code innmy own data and it works well, but I have a few questions. In my case, I have three sequences (three channels) with different sizes and a different number of slices between patients, so I need to resample without “inventing” slices. What strategy would you recommend? Because when I later run the occlusion code, I see it with a lot of zoom, and I would like to see it in its original size.

Thanks a lot!

Best regards,
Pablo

[PARODBE]

By the way, My problema is multiclass, and also I'd like implement a grad-cam, is It possible with monai?