Generation of Pseudo-CT using High-Degree Polynomial Regression on Dual-Contrast Pelvic MRI Data.

ABSTRACT: Increasing interests in using magnetic resonance imaging only in radiation therapy require methods for predicting the computed tomography numbers from MRI data. Here we propose a simple voxel method to generate the pseudo-CT (pCT) image using dual-contrast pelvic MRI data. The method is first trained with the CT data and dual-contrast MRI data (two sets of MRI with different sequences) of multiple patients, where the anatomical structures in the images after deformable image registration are segmented into several regions, and after MRI intensity normalizations a regression analysis is used to determine a two-variable polynomial function for each region to relate a voxel's two MRI intensity values to its CT number. We first evaluate the accuracy via the Hounsfield unit (HU) difference betw

SUBMITTER: Leu SC 

PROVIDER: S-EPMC7229007 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature