# MONAI

* **apps**: high level medical domain specific deep learning applications.

* **config**: for system configuration and diagnostic output.

* **data**: for the datasets, readers/writers, and synthetic data

* **engines**: engine-derived classes for extending Ignite behaviour.

* **handlers**: defines handlers for implementing functionality at various stages in the training process.

* **inferers**: defines model inference methods. 

* **losses**: classes defining loss functions.

* **metrics**: defines metric tracking types.

* **networks**: contains network definitions, component definitions, and Pytorch specific utilities.

* **transforms**: defines data transforms for preprocessing and postprocessing.

* **utils**: generic utilities intended to be implemented in pure Python or using Numpy,
and not with Pytorch, such as namespace aliasing, auto module loading.

* **visualize**: utilities for data visualization.