Medical images have a heterogenous number of dimensions. For example, MRI volumes can be treated as 2D slices, 3D volumes, or nD tensors (e.g. multi-echo, time, etc.). It is important to have built-in modules be able to handle tensors of arbitrary dimensions with some (but little) opinion about the behavior of the model across these different dimensions.
Proposal
Currently, frameworks require the user to keep track of the order of dimensions for tensors. We may be able to simplify this by having a tensor dim_order value that is managed and manipulated by the meddlr ecosystem.
TODOs
Medical images have a heterogenous number of dimensions. For example, MRI volumes can be treated as 2D slices, 3D volumes, or nD tensors (e.g. multi-echo, time, etc.). It is important to have built-in modules be able to handle tensors of arbitrary dimensions with some (but little) opinion about the behavior of the model across these different dimensions.
Proposal
Currently, frameworks require the user to keep track of the order of dimensions for tensors. We may be able to simplify this by having a tensor
dim_ordervalue that is managed and manipulated by the meddlr ecosystem.TODOs
forward.mri.SenseModelas a sample use case for managing multiple dimensions