Skip to Main content Skip to Navigation
Journal articles

Respiratory motion correction in dynamic MRI using robust data decomposition registration – Application to DCE-MRI

Abstract : 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-intensity curves and improved areas under the curve (AUC 60) at early enhancement.
Complete list of metadata

https://hal.univ-lorraine.fr/hal-03240516
Contributor : Juliette Birker <>
Submitted on : Friday, May 28, 2021 - 10:18:42 AM
Last modification on : Friday, May 28, 2021 - 10:18:44 AM

Links full text

Identifiers

Collections

Citation

Valentin Hamy, Nikolaos Dikaios, Shonit Punwani, Andrew Melbourne, Arash Latifoltojar, et al.. Respiratory motion correction in dynamic MRI using robust data decomposition registration – Application to DCE-MRI. Medical Image Analysis, Elsevier, 2013, 18 (2), pp.301 - 313. ⟨10.1016/j.media.2013.10.016⟩. ⟨hal-03240516⟩

Share

Metrics

Record views

16