How to quantify and minimise error in coral skeletal density estimates using X-ray µCT

This repository contains Supporting Material with Python and R code as well as data processing tutorials to accompany the following publication: **"How to quantify and minimise error in coral skeletal density estimates using X-ray µCT"** (link to paper and DOI once published). Corresponding author: XXXXX The code is distributed under the MIT license https://en.wikipedia.org/wiki/MIT_License=================== =================== =================== =================== ===================Below, you'll find a brief description of all the directories in this repository, which might have their own 'README' files with further info.## [AvizoTutorials]Instructions for X-ray volume operations using Avizo® covering :- How to align replicate X-ray µCT scans- How to segment X-ray volumes and shrinkwrap them quickly- How to export 16-bit single-binned histogram datasets for large X-ray volumes- How to extract volume metrics (e.g., Volume and SurfaceArea for example)- How to create a '.VolMetrics' file containing information from a respective scan## [PhantomExtraction]Python code for extracting greyscale values from an X-ray stack containing a phantom disc with embedded density standard materials (i.e., 'greyscale probing'):- [SemiAutomated_Extraction_Phantom.py]: Extraction across the stack by prompting user interaction to mark density standard materials embedded in or attached around a radiology phantom. - [Standard_Extract.py]: Automated extraction of phantom density inserts using computer vision to detect regular circular features across the phantom stack. ## [CoralWeightTests]Python code for density calibration and weight tests on X-ray µCT volumes that have been previously shrinkwrapped (Refer to [AvizoTutorials] :- [Phantom_Fittings.py]: Fitting different calibration curves to PhantomExtract results and performing weight tests.- [WeightTest_DiagnosticFigures.py]: Producing diagnostic figures to visualize different calibration fits and how µCT histogram and phantom density standards overlap.- [ResultsAggregator.py]: A wrapper to aggregate and bind weight test results across the ProjectRoot. This also appends volume and area measurements to resulting dataframes. ## [HistogramsReplicateScans]Python code for generating figures of X-ray histograms of replicate scans done under varying settings- [Histogram_overlays.py]: Plotting histogram overlays with kurtosis and skewness measurements. ## [R_ScriptsMainFiguresAndStats]R code to produce all base figures used in the publication. Statistical analyses therein. Code written in R version 4.2.2.Scripts are named based on the figure they generate and are self-explanatory. ## [Data]Data used in the paper and figures.