HARP-I: A Harmonic Phase Interpolation Method for the Estimation of Motion from Tagged MR Images - Inria - Institut national de recherche en sciences et technologies du numérique
Article Dans Une Revue IEEE Transactions on Medical Imaging Année : 2021

HARP-I: A Harmonic Phase Interpolation Method for the Estimation of Motion from Tagged MR Images

Résumé

We proposed a novel method called HARP-I, which enhances the estimation of motion from tagged Magnetic Resonance Imaging (MRI). The harmonic phase of the images is unwrapped and treated as noisy measurements of reference coordinates on a deformed domain, obtaining motion with high accuracy using Radial Basis Functions interpolations. Results were compared against Shortest Path HARP Refinement (SP-HR) and Sine-wave Modeling (SinMod), two harmonic image-based techniques for motion estimation from tagged images. HARP-I showed a favorable similarity with both methods under noise-free conditions, whereas a more robust performance was found in the presence of noise. Cardiac strain was better estimated using HARP-I at almost any motion level, giving strain maps with less artifacts. Additionally, HARP-I showed better temporal consistency as a new method was developed to fix phase jumps between frames. In conclusion, HARP-I showed to be a robust method for the estimation of motion and strain under ideal and non-ideal conditions.
Fichier principal
Vignette du fichier
HARP_I__A_Harmonic_Phase_Interpolation_Method_for_the_Estimation_of_Motion_from_Tagged_MR_Images_accepted_PREPRINT.pdf (3.79 Mo) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03112239 , version 1 (16-01-2021)

Identifiants

  • HAL Id : hal-03112239 , version 1

Citer

Hernán Mella, Joaquín Mura, Hui Wang, Michael D Taylor, Radomir Chabiniok, et al.. HARP-I: A Harmonic Phase Interpolation Method for the Estimation of Motion from Tagged MR Images. IEEE Transactions on Medical Imaging, 2021, 40 (4), pp.1240-1252. ⟨hal-03112239⟩
69 Consultations
277 Téléchargements

Partager

More