Package: DynClust 3.24
DynClust: Denoising and Clustering for Dynamical Image Sequence (2D or 3D)+t
A two-stage procedure for the denoising and clustering of stack of noisy images acquired over time. Clustering only assumes that the data contain an unknown but small number of dynamic features. The method first denoises the signals using local spatial and full temporal information. The clustering step uses the previous output to aggregate voxels based on the knowledge of their spatial neighborhood. Both steps use a single keytool based on the statistical comparison of the difference of two signals with the null signal. No assumption is therefore required on the shape of the signals. The data are assumed to be normally distributed (or at least follow a symmetric distribution) with a known constant variance. Working pixelwise, the method can be time-consuming depending on the size of the data-array but harnesses the power of multicore cpus.
Authors:
DynClust_3.24.tar.gz
DynClust_3.24.zip(r-4.5)DynClust_3.24.zip(r-4.4)DynClust_3.24.zip(r-4.3)
DynClust_3.24.tgz(r-4.4-any)DynClust_3.24.tgz(r-4.3-any)
DynClust_3.24.tar.gz(r-4.5-noble)DynClust_3.24.tar.gz(r-4.4-noble)
DynClust_3.24.tgz(r-4.4-emscripten)DynClust_3.24.tgz(r-4.3-emscripten)
DynClust.pdf |DynClust.html✨
DynClust/json (API)
# Install 'DynClust' in R: |
install.packages('DynClust', repos = c('https://yrozen-biostm.r-universe.dev', 'https://cloud.r-project.org')) |
- adu340_4small - Calcium-imaging dataset using Fura-2
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:5945736f5c. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 19 2024 |
R-4.5-win | OK | Nov 19 2024 |
R-4.5-linux | OK | Nov 19 2024 |
R-4.4-win | OK | Nov 19 2024 |
R-4.4-mac | OK | Nov 19 2024 |
R-4.3-win | OK | Nov 19 2024 |
R-4.3-mac | OK | Nov 19 2024 |
Exports:GetClusteringResultsGetDenoisingResultsMultiTestH0RunClusteringRunDenoising
Dependencies:
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Denoising and clustering for dynamical image sequence (2D or 3D)+T | DynClust-package |
Calcium-imaging dataset using Fura-2 | adu340_4small |
Get clustering step result | GetClusteringResults |
Get denoising step result | GetDenoisingResults |
Statistical test of zero mean for dynamics | MultiTestH0 |
Clustering of a dynamical image sequence | RunClustering |
Denoising step of a dynamical image sequence | RunDenoising |