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cornerstone_widget's Introduction

chestrays

Chestrays, like xrays but for chests

Software setup

We use conda to setup dependencies:

conda env create -f environment.yml

To use the shared kaggle account run the following command in the directory of this README:

export KAGGLE_CONFIG_DIR=`pwd`/secrets

To check if worked run kaggle kernels list -m. It should list some kernels and not print any warnings or errors.

Tools

There are currently two tools in this package: krun and kfetch.

krun takes a notebook (with existing metadata file) and runs it as a kaggle kernel. Optionally waiting for it to complete and downloading the output.

kfetch takes a notebook (with existing metadata file) and waits for it to complete running, then fetches the output.

To initially fetch a notebook from a kernel and have the metadata created use: kaggle kernels pull -p kernels/create-dataturks-nih chestrays/create-pneumonia-dataturks-dataset This will fetch the kernel called chestrays/create-pneumonia-dataturks-dataset and put it in the kernels/create-dataturks-nih subdirectory.

Secrets

To get access to the secrets stored in secrets/ install git-crypt and contact one of the people who have the key:

  • Tim Head

cornerstone_widget's People

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cornerstone_widget's Issues

hammer for mobile devices?

hammer should let us zoom, window, etc on mobile, and is already mostly supported just requires some cornerstone.external hacks

end-to-end testing

based on the failed PR #9 the idea would be to have javascript style/testing to make sure the code is reasonable #1 and full end-to-end testing to make sure it actually works in a browser (Chrome ATM) running the notebook

support for stacks?

having stacks would be very cool, but probably require a different image loader

add pixel dimension fields

right now the measurement fields are based on a pixel size of 1mm, this should be updated to the actual values

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