fat_768x384x1: Tensors for U-Net Neural Nets
In ventri2020/rraysplot: Make 2D Arrays Plots Less Aggravating
Description
Usage
Format
Details
Description
Tensors were created from 151 768x384 images
of the 160 patients,
along with manually created masks for
subcutaneous adipose tissue (SCAT)
and visceral adipose tissue (VSAT).
Usage
1
Format
A list of tensors. Images resolution 768x384.
- train
number of samples 141
- test
number of samples 10
Details
Tensors are arranged into two lists,
train and test list, respectively.
There are eight tensors:
train$image, train$mask, train$scat, train$vsat,
test$image, test$mask, test$scat, test$vsat.
Each tensor is an array of image data
with shape: train – 141x768x384, test – 10x768x384,
Fat 768x384x1
ventri2020/rraysplot documentation built on Jan. 1, 2021, 12:38 p.m.
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Description Usage Format Details
Description
Tensors were created from 151 768x384 images of the 160 patients, along with manually created masks for subcutaneous adipose tissue (SCAT) and visceral adipose tissue (VSAT).
Usage
1 |
Format
A list of tensors. Images resolution 768x384.
- train
number of samples 141
- test
number of samples 10
Details
Tensors are arranged into two lists, train and test list, respectively. There are eight tensors: train$image, train$mask, train$scat, train$vsat, test$image, test$mask, test$scat, test$vsat.
Each tensor is an array of image data with shape: train – 141x768x384, test – 10x768x384, Fat 768x384x1
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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