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Dataloader that serves (f)MRI images from key-value databases (mongo and Redis to start with)

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mindfultensors

Dataloader that serves MRI images from a mogodb.

The main idea is to keep MRI images and corresponding training labels for segmentation tasks in a mongo database. However, each 3D MRI tensor even in 8 bit precision is 16Mb. mongo's records cannot be larger than this limit and we need to also store the labels of the same dimensions. mindfultensors fetches and aggregates each tensor stored across multiple records, together with corresponding labels either for gray and white matter, 104 regions atlas, volume of each of 104 ROIs, or a 50 region atlas.

installation

The package is on pypy and the simplest way to install it is

pip install mindfultensors

However, to tinker with it you can also clone the repo:

git clone [email protected]:neuroneural/mindfultensors.git

Then change directory to the newly cloned repository:

cd mindfultensors

And install locally by

pip intall -e .

usage

A detailed example of how to create a dataloader using provided dataset class and the corresponding tools is in scripts/usage_example.py

Do not forget to move the batches to the GPU once obtained.

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Dataloader that serves (f)MRI images from key-value databases (mongo and Redis to start with)

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