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NEUROML2022
Neuroimaging and Machine Learning for Biomedicine
This is a repository containing seminars and lecture materials for the Skoltech course on Machine Learning in Neuroimaging data, Fall 2022.
Main links
Course description:
This course is specifically aimed at MSc and PhD students with basic knowledge of Machine Learning techniques pursuing further growth in neuroimaging data analysis, either in clinical practice or in neuroscience research. The course will provide you with training in the aspects of human neuroimaging methods, data properties and applied Machine Learning techniques. The course is focused on brain biophysics, scanning techniques and methods of data analysis. Students will develop a broad set of skills that are essential to study brain function, brain pathology and solve biomedical tasks with state-of-the-art Machine Learning and Computer Vision techniques.
The list of the current seminars published (will be updated with time):
SEMINAR 0 (05.09) Intro
SEMINAR 1 (09.09, 12.09) EEG analysis, Machine Learning in EEG
SEMINAR 2 (16.09) MRI data analysis, sources, databases, tools Note: To Follow seminar you will need docker installed and supplementary data downloaded
Install Docker;
Download
NEUROML-data.zip
from YaDisk and unzip it to local directory;Clone repository to your local machine;
Run docker locally and ensure it working with command
docker run hello-world
;In terminal:
cd NEUROML2022/seminar2
Type command
docker build -t neuroml/seminar2:0.0.1 .
and wait for successfull build (the dot . is importaint)Run
docker run --rm -it -v /directory/to/downloaded/data/on/step/2:/workspace/data -p 8080:8080 neuroml/seminar2:0.0.1
; Note: If you have Windows, pay attention to paths, type paths in conventional powershell scriptC:\directory\to\downloaded\data\on\step\2
Open browser (preferebly Chrome) -> localhost:8080
SEMINAR 3 (19.09) Machine Learning for structural MRI data analysis
SEMINAR 4 (23.09) fMRI data preprocessing, analysis, GLM
First follow the instruction for geting the docker image: https://miykael.github.io/nipype_tutorial/notebooks/introduction_docker.html.
Clone the seminar4 repository
Run the container and mount the folder: docker run -it --rm -p 8888:8888 -v /path_to_seminar-4:/home/neuro/nipype_tutorial/notebooks/seminar miykael/nipype_tutorial jupyter notebook
Dowload the data from: https://www.openfmri.org/dataset/ds000114/
SEMINAR 5 (26.09) Functional connectivity analysis and Machine Learning modelling
SEMINAR 6 (30.09) Deep Learning models and fMRI data analysis
SEMINAR 7 (03.10) Interpretation of ML models
Datasets used (please get a personal account and complete data use agreement):
Human Connectome Project https://db.humanconnectome.org/data/projects/HCP_1200
UCLA Consortium for Neuropsychiatric Phenomics LA5c Study https://openneuro.org/datasets/ds000030/versions/1.0.0
Autism Brain Imaging Data Exchange http://fcon_1000.projects.nitrc.org/indi/abide/
EEG Motor Movement/Imagery Dataset https://www.physionet.org/content/eegmmidb/1.0.0/
ADNI Alzheimer Disease Neuoroimaging Initiative https://ida.loni.usc.edu/services/NewUser.jsp
Software used (please get a personal account and complete usage agreement):
FreeSurfer https://surfer.nmr.mgh.harvard.edu/
FmriPrep https://fmriprep.org/en/stable/
Docker https://www.docker.com/
MNE python library https://mne.tools/stable/index.html