Analytic signal phase-based myocardial motion estimation in tagged MRI sequences by a bilinear model and motion compensation

被引:10
|
作者
Wang, Liang [1 ]
Basarab, Adrian [2 ]
Girard, Patrick R. [1 ]
Croisille, Pierre [1 ,3 ]
Clarysse, Patrick [1 ]
Delachartre, Philippe [1 ]
机构
[1] Univ Lyon 1, CREATIS, CNRS, INSERM,U1044,INSA Lyon,UMR 5220, F-69621 Villeurbanne, France
[2] Univ Toulouse, IRIT, CNRS, UMR 5505, F-31062 Toulouse 9, France
[3] Univ St Etienne, Univ Hosp St Etienne, Dept Radiol, St Etienne, France
关键词
Motion estimation; Iterative bilinear model; Phase invariance assumption; Analytic signal; Cardiac motion and strains; OPTICAL-FLOW ESTIMATION; DISPLACEMENT; TRACKING; COMPLEX; HEART; DENSE;
D O I
10.1016/j.media.2015.06.005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Different mathematical tools, such as multidimensional analytic signals, allow for the calculation of 2D spatial phases of real-value images. The motion estimation method proposed in this paper is based on two spatial phases of the 2D analytic signal applied to cardiac sequences. By combining the information of these phases issued from analytic signals of two successive frames, we propose an analytical estimator for 20 local displacements. To improve the accuracy of the motion estimation, a local bilinear deformation model is used within an iterative estimation scheme. The main advantages of our method are: (1) The phase-based method allows the displacement to be estimated with subpixel accuracy and is robust to image intensity variation in time; (2) Preliminary filtering is not required due to the bilinear model. The proposed algorithm, integrating phase-based optical flow motion estimation and the combination of global motion compensation with local bilinear transform, allows spatio-temporal cardiac motion analysis, e.g. strain and dense trajectory estimation over the cardiac cycle. Results from 7 realistic simulated tagged magnetic resonance imaging (MRI) sequences show that our method is more accurate compared with state-of-the-art method for cardiac motion analysis and with another differential approach from the literature. The motion estimation errors (end point error) of the proposed method are reduced by about 33% compared with that of the two methods. In our work, the frame-to-frame displacements are further accumulated in time, to allow for the calculation of myocardial Lagrangian cardiac strains and point trajectories. Indeed, from the estimated trajectories in time on 11 in vivo data sets (9 patients and 2 healthy volunteers), the shape of myocardial point trajectories belonging to pathological regions are clearly reduced in magnitude compared with the ones from normal regions. Myocardial point trajectories, estimated from our phase-based analytic signal approach, seem therefore a good indicator of the local cardiac dynamics. Moreover, they are shown to be coherent with the estimated deformation of the myocardium. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:149 / 162
页数:14
相关论文
共 50 条
  • [1] Phase-based motion estimation for noisy sequences
    Bruni, V.
    De Canditiis, D.
    Vitulano, D.
    [J]. 2007 14TH INTERNATIONAL WORKSHOP ON SYSTEMS, SIGNALS, & IMAGE PROCESSING & EURASIP CONFERENCE FOCUSED ON SPEECH & IMAGE PROCESSING, MULTIMEDIA COMMUNICATIONS & SERVICES, 2007, : 133 - 136
  • [2] Evaluation of a phase-based motion tracking method for the calculation of myocardial stress and strain from tagged MRI
    Lennart Tautz
    Anja Hennemuth
    Teodora Chitiboi
    Ulrich Kramer
    [J]. Journal of Cardiovascular Magnetic Resonance, 16 (Suppl 1)
  • [3] Cardiac motion estimation by joint alignment of tagged MRI sequences
    Oubel, E.
    De Craene, M.
    Hero, A. O.
    Pourmorteza, A.
    Huguet, M.
    Avegliano, G.
    Bijnens, B. H.
    Frangi, A. F.
    [J]. MEDICAL IMAGE ANALYSIS, 2012, 16 (01) : 339 - 350
  • [4] Motion estimation by phase shift and deformable mesh applied to tagged MRI cardiac sequences
    Basarab, Adrian
    Clarysse, Patrick
    Arts, Theo
    Cachard, Christian
    Croisille, Pierre
    Delachartre, Philippe
    [J]. TRAITEMENT DU SIGNAL, 2011, 28 (06) : 643 - 663
  • [5] Phase-based image motion estimation and registration
    Hemmendorff, M
    Andersson, MT
    Knutsson, H
    [J]. ICASSP '99: 1999 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, PROCEEDINGS VOLS I-VI, 1999, : 3345 - 3348
  • [6] Myocardial motion estimation in tagged MR sequences by using αMI-based non rigid registration
    Oubel, E
    Tobon-Gomez, C
    Hero, AO
    Frangi, AF
    [J]. MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2005, PT 2, 2005, 3750 : 271 - 278
  • [7] Estimation of 3D myocardial motion from tagged MRI using LDDMM
    Kotamraju, Vinay
    McVeigh, Elliot
    Beg, Mirza Faisal
    [J]. MEDICAL IMAGING 2007: PHYSIOLOGY, FUNCTION, AND STRUCTURE FROM MEDICAL IMAGES, 2007, 6511
  • [8] Uncertainty Quantification of Phase-Based Motion Estimation on Noisy Sequence of Images
    Sarrafi, Aral
    Mao, Zhu
    [J]. HEALTH MONITORING OF STRUCTURAL AND BIOLOGICAL SYSTEMS 2017, 2017, 10170
  • [9] COMPARISON OF PHASE-BASED SUB-PIXEL MOTION ESTIMATION METHODS
    Marinel, Cedric
    Mathon, Benjamin
    Losson, Olivier
    Macaire, Ludovic
    [J]. 2022 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP, 2022, : 561 - 565
  • [10] In vivo Estimation of Murine Myocardial Oxygenation with Physiological Signal Gating and Motion Compensation
    Al Mukaddim, Rashid
    Weichmann, Ashley M.
    Mitchell, Carol C.
    Heinmiller, Andrew
    Varghese, Tomy
    [J]. 2022 IEEE INTERNATIONAL ULTRASONICS SYMPOSIUM (IEEE IUS), 2022,