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jeremykawahara committed Dec 12, 2018
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Expand Up @@ -38,5 +38,26 @@ You can see the output in [this minimal example notebook](https://github.com/jer

You can find a more [comprehensive example here](https://github.com/jeremykawahara/derm7pt/blob/master/notebooks/example.ipynb) that includes an example of how to classify some of the seven-point checklist.

# Installation Instructions
You can see the dependencies and versions `derm7pt` was tested on [here](https://github.com/jeremykawahara/derm7pt/blob/master/version_check.ipynb).

To use `derm7pt`:
1. Download the [data](http://derm.cs.sfu.ca) and unzip it to your folder (we will use the folder `/local-scratch/jer/data/argenziano/release_v0` for this example)
2. Clone this repository
3. Run the [minimal_example.py](https://github.com/jeremykawahara/derm7pt/blob/master/minimal_example.py). Make sure to change the directory to match your data folder.

Steps #2 and #3 are shown below,
```
git clone https://github.com/jeremykawahara/derm7pt.git
cd derm7pt
python minimal_example.py '/local-scratch/jer/data/argenziano/release_v0'
```
This should output a view of the data that is similar to what is [shown in this notebook](https://github.com/jeremykawahara/derm7pt/blob/master/notebooks/minimal_example.ipynb).

# Related Publications
More information about this data can be found in our publication, and if you use the data or code, please cite our work,
> J. Kawahara, S. Daneshvar, G. Argenziano, and G. Hamarneh, “Seven-Point Checklist and Skin Lesion Classification using Multi-Task Multi-Modal Neural Nets,” IEEE Journal of Biomedical and Health Informatics, pp. 1–8, 2018. [[pdf]](http://www.cs.sfu.ca/~hamarneh/ecopy/jbhi2018a.pdf) [[doi]](https://doi.org/10.1109/JBHI.2018.2824327)
You can read more about the seven-point checklist here:
> G. Argenziano, G. Fabbrocini, P. Carli, D. G. Vincenzo, E. Sammarco, and M. Delfino, “Epiluminescence microscopy for the diagnosis of doubtful melanocytic skin lesions. Comparison of the ABCD rule of dermatoscopy and a new 7-point checklist based on pattern analysis,” Arch. Dermatol., vol. 134, no. 12, pp. 1563–1570, 1998.

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