Add SNR_star covariance-based SNR measurement macro

[Motohiro-TABUCHI]

This macro provides covariance-based SNR estimation for CT images (SNR_star).
Author: Motohiro TABUCHI
GitHub repository: https://github.com/Motohiro-TABUCHI/SNR_star_Tool

[Motohiro-TABUCHI]

This Pull Request adds SNR_star, an ImageJ macro for covariance-based SNR estimation in CT images.

SNR_star estimates signal variance and noise variance using the covariance between two repeated images acquired under identical imaging conditions. It outputs SNR* [dB], ROI size, signal variance, and noise variance.

Features:

• Covariance-based signal variance estimation
• Noise variance estimation from difference of images
• Simple workflow using ImageJ ROI tools
• Unbiased and statistically optimal SNR estimation

Requirements:

• ImageJ 1.53 or later
• Exactly two observed images of identical dimensions acquired under identical imaging conditions

Download & more information:
https://github.com/Motohiro-TABUCHI/SNR_star_Tool

Reference:
Tabuchi M, Kiguchi T, Ikenaga H. SNR estimation for image quality evaluation in X-ray CT. Jpn J Radiol Technol. 2022;78:464–72. https://doi.org/10.6009/jjrt.2022-1154

Author: Motohiro TABUCHI

[ctrueden]

@Motohiro-TABUCHI Thanks! I added you to the repository collaborators, so that you can edit pages directly now without a PR if you wish.