# Visualization resources!

A list of resources compiled during the OHBM Brainhack 2020.

Should this be added to this hackathon project? ----> https://github.com/learn-neuroimaging/tutorials-and-resources

Additional Visualization Tools findable [here via NITRC](https://www.nitrc.org/search/?type_of_search=group&cat=341:Visualization).

| Tool | Pros | Cons | Examples |
| -------- | -------- | -------- |-------- |
| [MIPAV](https://mipav.cit.nih.gov/) | Very versatile 2D/3D/4D viewer, with lots of tools for trying out simple image analysis. Great set of tools for manual delineation. Very nice volumetric and surface 3D rendering engine. | Tends to mess up Nifti headers when writing images, can be overwhelming. | Tends to mess up Nifti headers when writing images, can be overwhelming.| [Brain Painter](https://brainpainter.csail.mit.edu/) | | |
| [pysurfer](pysurfer.github.io) | |You are limited to freesurfer generated surfaces and annotations | |
| [mrivis](raamana.github.io/mrivis) | Carpet plots and advanced classes for slicing and dicing n-dim images (3D/4D/nD); various methods of comparing alignment | No CLI| https://raamana.github.io/mrivis/vis_classes_usage.html |
| [Mango](http://ric.uthscsa.edu/mango/) | User-friendly GUI, surface and slice options, configurable layouts, includes template and colormap creation options| GUI-based, less well-suited for automation|[Download + info](http://ric.uthscsa.edu/mango/), [surface + slices example](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6326731/figure/F3/) |
| [CARET](http://brainvis.wustl.edu/wiki/index.php/Caret:About) | | | |
| [Brain Life](https://brainlife.io/) | Integrated platform, pretty, can import data via datalad | a singular instance in the world | |
| [Nilearn](https://nilearn.github.io/) | Tools for surface, activation, connectome, ROIs, etc. etc., pythonic! , easy to use, well-documented, lots of available examples, built-in template and atlas fetching, can automate figure curation | python (a con if you're not a python user) | [Nilearn reference](https://nilearn.github.io/plotting/index.html)|
| [bioimagesuite](https://bioimagesuiteweb.github.io/alphaapp/dualviewer.html?repo=https://datasets.datalad.org/labs/haxby/attention) | Web UI, datasets.datalad.org support | Web UI | |
| [Plotly](https://plotly.com) | Text | Text | |
| [fsleyes](https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLeyes) | versatile | | |
| [AFNI, SUMA](https://afni.nimh.nih.gov) | mature, VERY versatile | old, works best with BRIK/HEAD | |
| [MRIcroGL](https://www.nitrc.org/projects/mricrogl) | pretty pictures, scriptable, Really fast and easy way to view volumes in 3-D, no freesurfer needed. | Can be a little fiddly, need to make a nifti for each element you want to visualize. | Figure 1B [here](https://academic.oup.com/neurosurgery/article/79/2/204/2837407) and 1A [here](https://www.nature.com/articles/nature17435/figures/1) are some of the better ones I've made. |
|[Gephi](https://gephi.org/)|create graphs| not trivial to install
|[BrainSpace](https://brainspace.readthedocs.io/en/latest/) | Available in both Python and MATLAB. Looks good out-of-the-box. | Currently lacks simple figure custimization. |
|[BrainNet](https://www.nitrc.org/projects/bnv/)

Some guidelines, tools, and helpful tutorials
| Source | Description |
| -------- | -------- |
| [Visualization Cheat Sheets](https://visualizationcheatsheets.github.io/index.html) | |
| [Paletton](https://paletton.com/)| Great complementary color picker, good for making discrete color maps |
| [Data to Viz](https://www.data-to-viz.com/)| |
| [Fundamentals of Data Visualization](https://serialmentor.com/dataviz/index.html)| Free e-book on data visualization |
| [Gallery of D3 visualizations](https://observablehq.com/@d3/gallery)| Nice source of inspiration (cf DataViz) |
| [Visual Vocabulary](https://gramener.github.io/visual-vocabulary-vega/)| Another chart/graph picker site. |
| [Guidelines on color-blindness figures](https://jfly.uni-koeln.de/color/)| |
| [Colorcet](https://colorcet.holoviz.org/user_guide/Categorical.html)| Categorical colors |