PMID- 34116317
OWN - NLM
STAT- MEDLINE
DCOM- 20210629
LR  - 20210629
IS  - 1724-191X (Electronic)
IS  - 1120-1797 (Linking)
VI  - 87
DP  - 2021 Jul
TI  - Left ventricle motion estimation for cine MR images using sparse representation 
      with shape constraint.
PG  - 49-64
LID - S1120-1797(21)00208-8 [pii]
LID - 10.1016/j.ejmp.2021.05.026 [doi]
AB  - PURPOSE: To propose a left ventricle (LV) motion estimation method based on 
      sparse representation, in order to handle the spatial-varying intensity 
      distortions caused by tissue deformation. METHODS: For each myocardial landmark, 
      an adaptive dictionary was generated by learning transformations from a training 
      dataset. Then the landmark was tracked using sparse representation. Next, a point 
      distribution model was applied to the overall tracking results. Finally, the 
      dense displacement field of the LV myocardium was estimated based on the 
      correspondence between each landmark. Using the dense displacement field 
      estimated, the circumferential strain was calculated to assess the myocardial 
      function. The performance of the proposed method was quantified by the average 
      perpendicular distance (APD), the Dice metric, and the mean symmetric contour 
      distance (SCD). RESULTS: Comparing to the state-of-the-art techniques, the 
      smallest value of APD and SCD, and the highest value of Dice can be obtained 
      using the proposed method, for three public cardiac datasets. Moreover, the mean 
      value of strain difference between the proposed method and the commercial 
      software Medis Suite MR was -0.01, while the intraclass correlation coefficient 
      between these two methods was 0.91. CONCLUSIONS: The proposed method could 
      estimate the dense displacement field of the LV accurately, which outperforms 
      other state-of-the-art techniques. The circumferential strain derived from the 
      proposed method was in excellent agreement with that derived from the Medis Suite 
      MR software, while segmental strain abnormalities were detected for most of the 
      subjects with heart diseases, which indicates the potential of the proposed 
      method for clinical usage.
CI  - Copyright (c) 2021 Associazione Italiana di Fisica Medica. Published by Elsevier 
      Ltd. All rights reserved.
FAU - Wu, Junhao
AU  - Wu J
AD  - Department of Computer Science, Shantou University, Shantou, Guangdong, China. 
      Electronic address: junhwu@stu.edu.cn.
FAU - Yang, Xuan
AU  - Yang X
AD  - College of Computer Science and Software Engineering, Shenzhen University, 
      Shenzhen, Guangdong, China. Electronic address: yangxuan@szu.edu.cn.
FAU - Gan, Ziyu
AU  - Gan Z
AD  - College of Computer Science and Software Engineering, Shenzhen University, 
      Shenzhen, Guangdong, China.
LA  - eng
PT  - Journal Article
DEP - 20210609
PL  - Italy
TA  - Phys Med
JT  - Physica medica : PM : an international journal devoted to the applications of 
      physics to medicine and biology : official journal of the Italian Association of 
      Biomedical Physics (AIFB)
JID - 9302888
SB  - IM
MH  - Heart
MH  - *Heart Ventricles
MH  - Humans
MH  - *Magnetic Resonance Imaging, Cine
MH  - Motion
MH  - Myocardium
OTO - NOTNLM
OT  - Cardiac cine MRI
OT  - Motion estimation
OT  - Myocardial strain
OT  - Sparse representation
EDAT- 2021/06/12 06:00
MHDA- 2021/06/30 06:00
CRDT- 2021/06/11 20:18
PHST- 2020/12/10 00:00 [received]
PHST- 2021/05/12 00:00 [revised]
PHST- 2021/05/17 00:00 [accepted]
PHST- 2021/06/12 06:00 [pubmed]
PHST- 2021/06/30 06:00 [medline]
PHST- 2021/06/11 20:18 [entrez]
AID - S1120-1797(21)00208-8 [pii]
AID - 10.1016/j.ejmp.2021.05.026 [doi]
PST - ppublish
SO  - Phys Med. 2021 Jul;87:49-64. doi: 10.1016/j.ejmp.2021.05.026. Epub 2021 Jun 9.