Introduction to neuroscience and neuroimaging#
Contents
Artificial Intelligence in Medical Imaging#
Fig. 1 Artificial Intelligence tasks in Medical Imaging.#
Datasets#
Datasets used (please get a personal account and complete data use agreement):
Software#
Software used (please get a personal account and complete usage agreement):
MRI Machine Learning and Deep Learning Tools#
Python libraries for the analysis of neuroimaging data (see more in the nipy.org):
Deep Learning:
More Deep Learning tools for MRI you can find in GitHub Repository (last update in 2022).
Docker#
Top docker commands:
docker run hello-world #test
docker pull miykael/nipype_tutorial:latest # pulling images
docker images # to check available images on your system
docker run -it –rm -v /path/to/nipype_tutorial/:/home/neuro/nipype_tutorial -v /path/to/data/:/data -v /path/to/output/:/output -p 8888:8888 miykael/nipype_tutorial jupyter notebook
docker run –rm kaczmarj/neurodocker:v0.4.0 generate [docker|singularity] –base neurodebian:stretch –pkg-manager apt –install afni ants git vim
docker rmi -f IMAGE_ID # To delete a specific docker image
docker exec -it IMAGE_ID /bin/bash # runs a new command in a running container.
docker save -o nipype_tutorial.tar miykael/nipype_tutorial # Export docker image miykael/nipype_tutorial
docker load –input nipype_tutorial.tar # Import docker image on another PC
Docker tutorials:
Python intro#
If you haven’t worked with Python before and don’t understand what’s going on, see other parts of Introduction.
Survey#
Please, take a survey. It will help us to adjust course to your skills.
Credits#
This text prepared by Polina Druzhinina and Nadezhda Alsahanova.