This repository contains the 3D spherical harmonics (SPHARM) decomposition and machine learning code associated with the following published study: Lefebvre TL et al. Predicting histopathology markers of endometrial carcinoma using a novel quantitative image analysis approach based on spherical harmonics in multiparametric MRI. Diagnostic and Interventional Imaging. 2023. Volume 104, Issue 3, Pages 142-152. https://doi.org/10.1016/j.diii.2022.10.007.
This work is largerly based on contributions and MATLAB packages developed by others and reported previously, mainly:
NFFT - Nonequispaced FFT(Keiner et al. Using NFFT 3 - a software library for various nonequispaced fast Fourier transforms. ACM Trans Math Software. 2009. 36, Article 19, 1-30.)TensorReg(Zhou and Li. Regularized matrix regression. Journal of Royal Statistical Society Series B. 2013. 76(2):463-483.)
Please refer to the new repository https://github.com/thierleft/3Dspharm-decomposition-tumor-python for detailed demo in Python.
