API Reference

This is the class and function reference of ClinicaDL. Please refer to the user guide for more information and usage examples, as the raw specifications of classes and functions may not be enough to give full guidelines on their use.

---

callbacks	For monitoring and customizing the training and evaluation phases.
data	For building PyTorch objects able to manipulate neuroimaging data.
infer	For customizing the inference stage, such as performing post-processing or combining outputs from multiple neural networks.
io	Input/Output (IO) module for manipulating file directories produced and read by ClinicaDL.
losses	For creating a criterion to minimize during training.
metrics	For evaluating models.
models	For defining models, which encompass neural networks, loss functions, optimizers, and the training and evaluation logic.
networks	For building neural networks.
optim	For configuring optimization during training.
split	For splitting data into training, validation and test sets.
transforms	For transforming 3D neuroimaging data.
train	For training and evaluating a model.
utils	Utility classes and functions.