nslay / PyRicianNormalization

MRI image normalization scheme based on Rice distribution

PyRicianNormalization

MRI image normalization scheme based on Rice distribution

Introduction

RicianNormalization is a tool that reads T2W images (as DICOM or Nifti, MetaIO, etc...) and potentially other magnitude MR images, fits a Rice distribution to the pixel intensities and normalizes the pixels based on the standard score using the fit Rice mean and standard deviation.

PyRicianNormalization is a Python port of RicianNormalization

https://github.com/nslay/RicianNormalization

The method is loosely based on this work: Lemaître, Guillaume, et al. "Normalization of t2w-mri prostate images using rician a priori." Medical Imaging 2016: Computer-Aided Diagnosis. Vol. 9785. International Society for Optics and Photonics, 2016.

Though the implementation is vastly different employing a maximum log likelihood scheme to fit the Rice distribution.

Installing

TODO

Usage

TODO

Caveats

Saving floating point voxel output to DICOM series does not seem to work correctly. Limitation of SimpleITK?