作者
Valentin Hamy, Nikolaos Dikaios, Shonit Punwani, Andrew Melbourne, Arash Latifoltojar, Jesica Makanyanga, Manil Chouhan, Emma Helbren, Alex Menys, Stuart Taylor, David Atkinson
发表日期
2014/2/1
期刊
Medical image analysis
卷号
18
期号
2
页码范围
301-313
出版商
Elsevier
简介
Motion correction in Dynamic Contrast Enhanced (DCE-) MRI is challenging because rapid intensity changes can compromise common (intensity based) registration algorithms. In this study we introduce a novel registration technique based on robust principal component analysis (RPCA) to decompose a given time-series into a low rank and a sparse component. This allows robust separation of motion components that can be registered, from intensity variations that are left unchanged. This Robust Data Decomposition Registration (RDDR) is demonstrated on both simulated and a wide range of clinical data. Robustness to different types of motion and breathing choices during acquisition is demonstrated for a variety of imaged organs including liver, small bowel and prostate. The analysis of clinically relevant regions of interest showed both a decrease of error (15–62% reduction following registration) in tissue time …
引用总数
20142015201620172018201920202021202220232024819142015161713958