Immigration / Installation:

• VISA | Student/Working permit
• How to find an apartment in Montreal?

Life at NeuroPoly Lab:

• Starting at NeuroPoly Lab
• How to write scientific articles

Below are the workshops/hackathons organized by the Lab:

• 5th Spinal Cord MRI Workshop, Paris 2018
• 4th Spinal Cord MRI Workshop, Honolulu 2017
• 3rd Spinal Cord MRI Workshop, Singapore 2016
• QBIN - Workshop Super-Big Brain, Montreal 2016
• Brainhack, Montreal 2015
• 2nd Spinal Cord MRI Workshop, Toronto 2015
• Brainhack EDT conference (2014)
• 1st Spinal Cord Hack, Milan 2014

• Netherlands eScience Center Guide

Videos:

• Videos: Paul Callaghan explaining NMR

Slides:

• Course material from NYU
• Interactive course on Diffusion MRI (Stikov et al.)

Software:

• spinbench
• Bloch simulator for education in NMR and MRI
• Gadgetron: open source framework for medical image reconstruction
• MRI Unbound: open source software for image recon and pulse seq design
• http://mrilab.sourceforge.net/

Pulse sequences

• Open source pulse sequence programming (Matlab): http://pulseq.github.io/
• MR Pulse Sequences: What Every Radiologist Wants to Know but Is Afraid to Ask
• Understanding MRI: basic MR physics for physicians
• AAPM/RSNA Physics: Tutorial for Residents - Fundamental Physics of MR Imaging

• Open source hardware at 7T from UMCU
• Open-source Console for Real-time Acquisition (OCRA)
• Open source coil design

• https://github.com/ISMRM/mrhub

• https://github.com/raamana/visualqc

• Jülich Extensible MRI Simulator (JEMRIS). Provides an MRI sequence development and simulation environment.
• Birdcage builder (PennState)

• ilastik is a simple, user-friendly tool for interactive image classification, segmentation and analysis. It is built as a modular software framework, which currently has workflows for automated (supervised) pixel- and object-level classification, automated and semi-automated object tracking, semi-automated segmentation and object counting without detection.
• Trainable Weka Segmentation: A Fiji plugin that combines a collection of machine learning algorithms with a set of selected image features to produce pixel-based segmentations using Weka. Provides a framework to use and compare any available classifier to perform image segmentation based on pixel classification, bridging machine learning and image processing. Has GUI support.
• CDeep3M: Plug-and-Play cloud based deep learning for image segmentation of light, electron and X-ray microscopy

• Biospective
• NeuroRX
• Rogue Research