Patch2Self Denoising - Quick tutorial - How to install and use in seconds!

Speaker: Shreyas Fadnavis, PhD Candidate, Indiana University

This video describes Patch2Self (NeurIPS paper): https://papers.nips.cc/paper/2020/hash/bc047286b224b7bfa73d4cb02de1238d-Abstract.html

Additional information is provided in this blog: https://shreyasfadnavis.medium.com/patch2self-self-supervised-denoising-via-statistical-independence-4601fda38c20

For now you can install the current nightly build wheel: https://anaconda.org/scipy-wheels-nightly/dipy (use before Jan 2021)
See video for instructions.

After, January 1st 2021, DIPY 1.4.0 will be released, then to access Patch2Self upgrade DIPY using : pip install -U dipy

We assume that you have anaconda installed in your system. If not download it here first https://www.anaconda.com/products/individual

To ask questions, there is a live chatroom here:
DIPY Gitter: https://gitter.im/dipy/dipy

To report any issues please go here:
DIPY GitHub: https://github.com/dipy/dipy/issues

To register to our mailing list ([email protected]), subscribe here
https://mail.python.org/mailman3/lists/dipy.python.org/

And if you use the method, please cite the original paper:
[1] Fadnavis, Shreyas, Joshua Batson, and Eleftherios Garyfallidis. "Patch2Self: Denoising Diffusion MRI with Self-Supervised Learning." Advances in Neural Information Processing Systems 33 (2020).

and DIPY that hosts the bullet proof implementation:
[2] Garyfallidis E, Brett M, Amirbekian B, Rokem A, van der Walt S, Descoteaux M, Nimmo-Smith I and Dipy Contributors (2014). DIPY, a library for the analysis of diffusion MRI data. Frontiers in Neuroinformatics, vol.8, no.8.

Thank you!