Add blurring in data augmentation

[tanguyduval]

Some regions suffer from bad focus which bias the results: much fewer small axons detected. Would be nice to detect that.

Bad Focus:

On Focus:

[perone]

Blurry images can really degrade the CNN performance, there is a paper evaluating that [1] (the x-axis is the σ of the kernel):

It would be nice to test a blur augmentation to see if it improves. Do we have similar patches in the training/test set ?

Another approach to this is to try to plug a super-resolution network (i.e. [2]) to do deblurring on a parallel branch of the original net.

[1] https://arxiv.org/pdf/1604.04004.pdf [2] https://www.doc.ic.ac.uk/~oo2113/publications/MICCAI2016_camera_ready.pdf

[tanguyduval]

In folder /Volumes/data_processing/tanguy/Histo/Human slices T4 and C2A show bad focus

[maxwab]

To be noted: blurring as a data augmentation function has been implemented and is part of the transformations that we apply during the training.

However, I am not sure of the exact effects it had on the training itself, other than that it should improve the performance.

[perone]

I would be very cautious with blur augmentation because we haven't done any validation of it as I recall. Since CNNs are VERY sensitive to blurring (see paper above), it may be detrimental to the final prediction of images that aren't blurred.