2-biomedical_imaging

Biomedical imaging in time and space

Learning objectives

In the following series of seven Jupyter notebooks will explore multichannel imaging data from two quite different imaging modalities (in terms of physical principles and spatial resolution):

• Imaging Mass Cytometry (IMC)
• Magnetic Resonance Imaging (MRI)

and illustrate the generic nature of computational imaging.

More specifically:

• image processing, image noise, image filtering (e.g. Gabor filters)
• supervised and unsupervised tissue classification in structural MRI (sMRI) recordings
• the nature of 4D (3D + time) resting state BOLD functional MRI (rs-fMRI)
• brain connectivity and graph representation towards Network science

Presentations: "Biomedical imaging in time and space"

• [Part 1] (May 4th)
• [Part 2] (May 9th)
• Recording, May 9th: https://youtu.be/Ld8zk4uYktA

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If you want to install this imaging lab locally, do:

Install and activate the conda environment (see local setup-img.md) before you start:

# This you only need to do initially, and only once
conda env create -f environment-img.yml

# Activate the environment
conda activate dln2022-img

# Install the specific `DLN2022-IMG` Jupyter kernel (only once):
python -m ipykernel install --user --name dln2022-img --display-name "DLN2022-IMG"

Update:

The code and environment can be updated during the course. Run the following commands regularly from within this (2-biomedical_imaging) directory:

• Update this particular dln2022-img environment:

conda activate dln2022-img
conda env update --file environment-img.yml

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The series of notebooks:

• 0-test-installation.ipynb (relevant for local installation, cf. environment-img.yml and setup-img.md, but has some important components for Introduction to machine learning)

• 1-get-MRI-IMC-data.ipynb

• 2-imaging-intro.ipynb

• 3-MRI-intro.ipynb

• 4-IMC-intro.ipynb

• 5-sMRI-KNN-tissue-classification.ipynb

• 6-sMRI-Kmeans-tissue-classification.ipynb

• 7-fMRI-resting-state.ipynb

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Sources of information related to MRI principles and applications

Introductory videos

• How Does an MRI Scan Work? 1:20 (https://youtu.be/1CGzk-nV06g)
• MRI vs. CT 2:31 (https://youtu.be/aQZ8tTZnQ8A)
• Brain MRI scan protocols, positioning and planning 9:34 (https://youtu.be/R5LQzoFynqI)
• MRI: Basic Physics & a Brief History 25:51 (https://youtu.be/djAxjtN_7VE)
• Bergen fMRI group - the birth of a research group 19:45 (https://youtu.be/6UhfAX3RusE)

Awesome Magnetic Resonance Imaging (MRI)

• A curated list of delightful Magnetic Resonance courses, books, lectures, papers, blogs and free resources by Daniel Gomez, Donders Institute for Brain, Cognition and Behaviour (https://github.com/dangom/awesome-mri)
• MRIMASTER.COM (https://mrimaster.com)

Simulators and more

• The (web) compass simulator from the Danish Research Centre for Magnetic Resonance and TDU (http://www.drcmr.dk/CompassMR)

• The (web) Bloch simulator from the Danish Research Centre for Magnetic Resonance and TDU (http://drcmr.dk/BlochSimulator)

• MRiLab A Numerical Magnetic Resonance Imaging Simulation Platform in MATLAB by Fang Liu(https://github.com/leoliuf/MRiLab)

• MRI-education-resources UCSF Peder Larson Research Group (https://github.com/LarsonLab/MRI-education-resources/tree/master/Notebooks)

• Pulse sequence graphics by Daniel Gomez (https://github.com/dangom/mr-sequence-diagrams/blob/master/README.org)

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In your spare time - relax and enjoy biological vision:

See this webpage containing demos of many beautiful and fascinating optical illusions and visual phenomena. Michael Bach gives detailed descriptions of these phenomena also from a theoretical perspective.
Even more interested? see https://foundationsofvision.stanford.edu by Brian A. Wandell at Stanford.