Package: neuroSCC 1.0.2

neuroSCC: Bridging Simultaneous Confidence Corridors and PET Neuroimaging

Tools for the structured processing of PET neuroimaging data in preparation for the estimation of Simultaneous Confidence Corridors (SCCs) for one-group, two-group, or single-patient vs group comparisons. The package facilitates PET image loading, data restructuring, integration into a Functional Data Analysis framework, contour extraction, identification of significant results, and performance evaluation. It bridges established packages (e.g., 'oro.nifti') with novel statistical methodologies (e.g., 'ImageSCC') and enables reproducible analysis pipelines, including comparison with Statistical Parametric Mapping ('SPM').

Authors:Juan A. Arias Lopez [aut, cre, cph], Virgilio Gomez Rubio [rev], Pablo Aguiar Fernandez [ths], Andrew Haddon Kemp [ths]

neuroSCC_1.0.2.tar.gz
neuroSCC_1.0.2.zip(r-4.7-any)neuroSCC_1.0.2.zip(r-4.6-any)neuroSCC_1.0.2.zip(r-4.5-any)
neuroSCC_1.0.2.tgz(r-4.6-any)neuroSCC_1.0.2.tgz(r-4.5-any)
neuroSCC_1.0.2.tar.gz(r-4.7-any)neuroSCC_1.0.2.tar.gz(r-4.6-any)
neuroSCC_1.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
neuroSCC/json (API)

# Install 'neuroSCC' in R:
install.packages('neuroSCC', repos = c('https://iguanamarina.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/iguanamarina/neuroscc/issues

Pkgdown/docs site:https://iguanamarina.github.io

Datasets:

On CRAN:

Conda:

functional-data-analysisneuroimaging-analysispositron-emission-tomography

5.08 score 2 stars 6 scripts 363 downloads 14 exports 31 dependencies

Last updated from:e27b25cb14. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK195
source / vignettesOK320
linux-releaseOK180
macos-releaseOK151
macos-oldrelOK201
windows-develOK256
windows-releaseOK236
windows-oldrelOK241
wasm-releaseOK175

Exports:calculateMetricsdatabaseCreatorgeneratePoissonClonesgetDimensionsgetPointsgetSPMbinarymatrixCreatormeanNormalizationneuroCleanerneuroContourplotSCCcomparisonPanelplotSCCpanelplotValidationPanelprocessROIs

Dependencies:abindbitopsclicpp11data.tabledplyrgenericsgluejsonlitelatticelifecyclemagrittrMASSmemiscoro.niftipillarpkgconfigpurrrR6RcpprlangRNiftistringistringrtibbletidyrtidyselectutf8vctrswithryaml

one_vs_group
Introduction | Data Preparation (Conditional) | Single Patient Data and Cloning | SCC Estimation (Conditional Execution) | Visualizing the SCC Result | Visualizing Group Means and SCC Differences | Extracting Significant Points and Evaluating Metrics | Visual Validation Against ROI and SPM | Conclusion
Rendered fromone_vs_group.Rmdusingknitr::rmarkdown

Last update: 2026-04-18
Started: 2025-03-17

two_group_comparison
Introduction | Data Preparation (Conditional) | SCC Estimation (Group vs Group) | Visualizing Group Means and SCC Differences | Extracting Significant Points and Evaluating Metrics | Visual Validation Against ROI and SPM | Conclusion
Rendered fromtwo_group_comparison.Rmdusingknitr::rmarkdown

Last update: 2026-04-18
Started: 2025-03-17

landing_vignette
Introduction | 1. Loading and Inspecting Neuroimaging Data | 2. Creating a Database from Multiple PET Images | 3. Creating the Data Matrix | 4. Normalizing the Data Matrix | 5. Extracting Contours for Triangulation | 6. Conditional Triangulation Setup (optional) | What's Next?
Rendered fromlanding_vignette.Rmdusingknitr::rmarkdown

Last update: 2026-03-25
Started: 2025-03-17