to_categorical_volume: Split a Label Volume in One-hot Encoding
In neuroimaginador/dl4ni: Deep Learning Flows for Neuroimaging
Description
Usage
Arguments
Value
Description
This function splits a volume (representing a labelling, such as the result of a segmentation) into several binary volumes (concetenated as a 4D volume) such that each individual 3D volume indicates the presence of a class in the image.
Usage
1
to_categorical_volume(V, unique_labels = sort(unique(as.vector(V))))
Arguments
V
(3D array) Input volume
Value
A 4D volume representing the one-hot encoding of the input 3D volume.
neuroimaginador/dl4ni documentation built on May 3, 2019, 5:47 p.m.
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Description Usage Arguments Value
Description
This function splits a volume (representing a labelling, such as the result of a segmentation) into several binary volumes (concetenated as a 4D volume) such that each individual 3D volume indicates the presence of a class in the image.
Usage
1 | to_categorical_volume(V, unique_labels = sort(unique(as.vector(V))))
|
Arguments
V |
(3D array) Input volume |
Value
A 4D volume representing the one-hot encoding of the input 3D volume.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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