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Structural Neuroimaging Analysis in Python

Home Page: https://carpentries-incubator.github.io/SDC-BIDS-sMRI/

License: Other

Ruby 0.01% Makefile 0.05% R 0.05% Shell 0.01% Python 0.44% Jupyter Notebook 97.02% MATLAB 0.71% HTML 1.72%

lesson english pre-alpha carpentries-incubator python mri bids neuroimaging

sdc-bids-smri's Introduction

Introduction to sMRI (Pre)processing and Analysis in Python

Background

This is one sub-module within the [Neuroimaging curriculum][neuro_curriculum]. Visit the link to view all the modules associated with the Neuroimaging Carpentries program.

sMRI Analysis in Python is a programme developed to facilitate reproducibility in structural neuroimaging analyses. Python is emerging as a standard language of data analysis, visualization, and workflow building. More recently, it has rapidly been adopted by the neuroimaging community as a means of developing powerful open-source tools in favour of historically used opaque software such as AFNI, FSL and SPM. In addition, the barrier to entry to Python is low - meaning that you as the user can easily develop your own packages and contribute to the open-source codebase of neuroimaging!

The sMRI Analysis in Python is a workshop series started up via a collaboration between researchers and staff at the Centre for Addiction and Mental Health (Toronto, ON), the University of Western Ontario (London, Ontario), and McGill University (Montreal, Quebec).

About the lesson

This lesson covers a typrical sMRI imaging pipeline by introducing 1) image modalities, 2) image preprocessing, 3) phoenotype quantification, and 4) statistical analyses.

The primary goals of this workshop are:

Understand the basics of strcutural MR image acquisition
Familiarize with structural MR image (pre)processing pipeline
Perform and visualize group-level neuroanatomical analyses

Episodes

Time	Episode	Question(s) Answered
	Setup	Download files required for the lesson
00:00	1. sMRI Acquisition and Modalities	How is MR image acquired? What anatomical features do different modalities capture?
00:30	2. sMRI Clean-up	How do we remove intensity artifacts and extract brains?
01:15	3. sMRI Spatial Normalization	What are "coordinate spaces", "templates", "atlases"? What is image registration?
02:00	4. sMRI Segmentation and Parcellation	How do we delineate brain anatomy and quantify phenotypes?
02:45	5. sMRI Quality-control	How do we identify image preprocessing failures?
03:15	6. Statistical Analysis	How to compare regional anatomical differences in case-control groups?
04:00	7. Reproducibility Considerations	How sensitive are the findings to your MR pipeline parameters?
04:30	Finish

You Are Here!

Contributing

We welcome all contributions to improve the lesson! Maintainers will do their best to help you if you have any questions, concerns, or experience any difficulties along the way.

We'd like to ask you to familiarize yourself with our Contribution Guide and have a look at the more detailed guidelines on proper formatting, ways to render the lesson locally, and even how to write new episodes.

Please see the current list of issues for ideas for contributing to this repository. For making your contribution, we use the GitHub flow, which is nicely explained in the chapter Contributing to a Project in Pro Git by Scott Chacon. Look for the tag . This indicates that the mantainers will welcome a pull request fixing this issue.

Maintainer(s)

Authors

A list of contributors to the lesson can be found in AUTHORS

Citation

To cite this lesson, please consult with CITATION

sdc-bids-smri's People

Contributors

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nikhil153 jbpoline neurorepro devdinie shannyfoo htylab sheriff-alimi josephmje mary-tziraki healthbioscienceideas margosolo mri4brain renxiaonan hfxcarl mirhnius jhlegarreta leon-wang521

sdc-bids-smri's Issues

fmriprep docker link

The Docker image link in the second notebook doesn't work.
https://fmriprep.org/en/stable/docker.html#running-fmriprep-with-the-fmriprep-docker-wrapper

Issue with append in the first notebook

In the T1 and T2 relaxation and image contrast section, there is a tiny bug. You have tried to concatenate two data frames with append attribute. append is deprecated and if you try to run the cell, you will face an error. Use concate instead.

T1_dict = {'GM':1200, 'WM':800, 'CSF':4000, 'Bone':500}  
T2_dict = {'GM':110, 'WM':80, 'CSF':750, 'Bone':50}
T1_duration = np.arange(0,4500,500)
T2_duration = np.arange(0,500,100)
relax_df = pd.DataFrame()

for tissue,T1 in T1_dict.items():
    _df = pd.DataFrame()
    Mz = get_Mz(T1,T1_duration)
    _df['time'] = T1_duration
    _df['signal'] = Mz
    _df['relaxation'] = 'T1'
    _df['tissue'] = tissue

  relax_df = relax_df.append(_df)

  relax_df = pd.concat([relax_df,_df])

Environment Set Up

I tried to follow the instructions for Linux to create a Conda environment. However, I could not run the notebooks.

cd SDC-BIDS-sMRI
conda create -p ./SDC_sMRI_workshop_2021
source activate $(pwd)/SDC_sMRI_workshop_2021
conda install numpy pandas scipy scikit-learn matplotlib seaborn jupyter ipykernel nb_conda
conda install -c conda-forge awscli nibabel nilearn lxml statsmodels
pip install pybids

It seems there is a problem with nb_conda package. I tried once without this package; all other libraries work fine but I have a problem with pybids and Conda could not find it.

Update contact details and license file

Hi folks, we received an email to The Carpentries account requesting permission to re-use one of the images from this lesson in a publication, and asking for a copy of that image at higher resolution.

We received that email because the contact email address on the lesson site is still set to [email protected]. Please could you update it to an address where interested people can reach the authors?

Regarding the permission request: I informed the requester that the CC-BY license of the lesson granted them permission as long as they cited the source of the material. However, the license file for the lesson talks about citing it as copyright of Software Carpentry (this is a problem across most lessons in the Incubator, related to how we create the lesson repositories from a template). I advised them to cite it differently, but you may like to update your LICENSE.md to contain information specific to this lesson.

Finally, I could not help with providing a copy of the image in higher resolution, and have suggested that they open an issue here to request it.