The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
Abstract
AiES is a free and open-source R-package for (high-throughput) axonal integrity analysis of micrographs such as murine dorsal root ganglia explant cultures. AiES offers tools to segment neurites, extract quantitative features, generate SVM models, and quantify axon integrity.AiES is available under the 3-Clause BSD license.The AiES package provides an integrated workflow for axon
image analysis, including feature extraction, machine learning
classification, and quantitative assessment.
The main functions are:
axDistmap()
: Extracts morphological features from axon
images.axSvm()
: Builds an SVM classifier using extracted
features.axQnt()
: Quantifies Axon Integrity Index (AII) and
Degeneration Index (DI) for new data using a trained SVM.axDistmap
)The axDistmap() function creates distance maps and binary images from TIFF image files, extracting relevant features.
library(AiES)
# Specify a sample image folder included in the package
img_dir1 <- system.file("extdata", "Degenerate_Images", package = "AiES")
img_dir2 <- system.file("extdata", "Intact_Images", package = "AiES")
# Extract features from multiple folders (recursive search)
axDistmap(
folder_paths = c(img_dir1, img_dir2), # Multiple folders supported
subBack = 30,
resizeW = 900,
output_path = tempdir()
)
This function processes all TIFF files in the selected directory, generating for each image:
axSvm
)The axSvm() function built an SVM model using the extracted features.
# Specify feature data folders
Degenerate_dir <- system.file("extdata", "Degenerate_txt", package = "AiES")
Intact_dir <- system.file("extdata", "intact_txt", package = "AiES")
# Train an SVM classifier
axSvm(
degenerate_path = Degenerate_dir,
intact_path = Intact_dir,
output_data_path = tempdir(),
output_model_path = tempdir(),
nCst = 3, nGmm = 0.1, nCrss = 5
)
This function generates:
axQnt
)The axQnt() function uses the created SVM model to calculate the Axon Integrity Index and Degeneration Index for new image data.
# Specify a sample image folder included in the package
img_dir1 <- system.file("extdata", "Degenerate_Images", package = "AiES")
img_dir2 <- system.file("extdata", "Intact_Images", package = "AiES")
# Quantify AII/DI for new image data
result <- axQnt(
input_dir = c(img_dir1, img_dir2), # Multiple folders supported
svm_model_path = system.file("extdata", "svm_example_model.svm", package = "AiES"),
output_dir = tempdir()
)
# Visualize the results
library(ggplot2)
ggplot(result, aes(x = AxonIntegrityIndex)) +
geom_histogram(binwidth = 0.1, fill = "blue", alpha = 0.7) +
ggtitle("AII Distribution")
This function generates:
With AiES, you can perform feature extraction, machine
learning, and quantitative analysis in a seamless
workflow.
For more details, see the help pages for each function (e.g.,
?axDistmap
, ?axSvm
, ?axQnt
).
You can find the development version of AiES on GitHub.
For bug reports and feature requests, please use the GitHub Issues page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.