scholarly journals Segmentation of cardiac cine MR images of left and right ventricles: Interactive semiautomated methods and manual contouring by two readers with different education and experience

2008 ◽  
Vol 27 (4) ◽  
pp. 785-792 ◽  
Author(s):  
Francesco Sardanelli ◽  
Matteo Quarenghi ◽  
Giovanni Di Leo ◽  
Leonardo Boccaccini ◽  
Angelo Schiavi
Keyword(s):  
Mr Images ◽  
Cine Mr ◽  
Cardiac Cine ◽  
Left And Right

Automatic localization of the left ventricular blood pool centroid in short axis cardiac cine MR images

2017 ◽  
Vol 56 (6) ◽  
pp. 1053-1062 ◽  
Author(s):  
Li Kuo Tan ◽  
Yih Miin Liew ◽  
Einly Lim ◽  
Yang Faridah Abdul Aziz ◽  
Kok Han Chee ◽  
...  
Keyword(s):  
Blood Pool ◽  
Left Ventricular ◽  
Short Axis ◽  
Mr Images ◽  
Cine Mr ◽  
Cardiac Cine ◽  
Automatic Localization

Normal signal-void patterns in cardiac cine MR images.

Radiology ◽  
1990 ◽  
Vol 176 (1) ◽  
pp. 49-55 ◽  
Author(s):  
S A Mirowitz ◽  
J K Lee ◽  
F R Gutierrez ◽  
J J Brown ◽  
S S Eilenberg
Keyword(s):  
Mr Images ◽  
Cine Mr ◽  
Cardiac Cine ◽  
Signal Void

scholarly journals Reconstruction of Cardiac Cine MR Images from Partial k-Space

SRX Physics ◽  
2010 ◽  
Vol 2010 ◽  
pp. 1-6
Author(s):  
Josiane Yankam Njiwa ◽  
Yuemin Zhu ◽  
Jianhua Luo ◽  
Bassem Hiba
Keyword(s):  
Mr Images ◽  
Cine Mr ◽  
Cardiac Cine

scholarly journals Simultaneous segmentation of the left and right heart ventricles in 3D cine MR images of small animals

2005 ◽  
Author(s):  
J. Schaerer ◽  
Y. Rouchdy ◽  
P. Clarysse ◽  
B. Hiba ◽  
P. Croisille ◽  
...  
Keyword(s):  
Small Animals ◽  
Mr Images ◽  
Right Heart ◽  
Heart Ventricles ◽  
Cine Mr ◽  
Left And Right

Fully automatic, retrospective enhancement of real-time acquired cardiac cine MR images using image-based navigators and respiratory motion-corrected averaging

2008 ◽  
Vol 59 (4) ◽  
pp. 771-778 ◽  
Author(s):  
Peter Kellman ◽  
Christophe Chefd'hotel ◽  
Christine H. Lorenz ◽  
Christine Mancini ◽  
Andrew E. Arai ◽  
...  
Keyword(s):  
Real Time ◽  
Respiratory Motion ◽  
Mr Images ◽  
Cine Mr ◽  
Cardiac Cine ◽  
Fully Automatic

scholarly journals Automatic segmentation of right ventricle in cardiac cine MR images using a saliency analysis

2016 ◽  
Vol 43 (12) ◽  
pp. 6270-6281 ◽  
Author(s):  
Angélica Atehortúa ◽  
Maria A. Zuluaga ◽  
Juan D. García ◽  
Eduardo Romero
Keyword(s):  
Right Ventricle ◽  
Automatic Segmentation ◽  
Mr Images ◽  
Cine Mr ◽  
Cardiac Cine ◽  
Saliency Analysis

scholarly journals Automatic identification of the left ventricle in cardiac cine-MR images: Dual-contrast cluster analysis and scout-geometry approaches

2006 ◽  
Vol 23 (5) ◽  
pp. 641-651 ◽  
Author(s):  
Amol S. Pednekar ◽  
Raja Muthupillai ◽  
Veronica V. Lenge ◽  
Ioannis A. Kakadiaris ◽  
Scott D. Flamm
Keyword(s):  
Cluster Analysis ◽  
Left Ventricle ◽  
Automatic Identification ◽  
Mr Images ◽  
Cine Mr ◽  
Cardiac Cine

scholarly journals Sequential shape similarity for active contour based left ventricle segmentation in cardiac cine MR image

2021 ◽  
Vol 19 (2) ◽  
pp. 1591-1608
Author(s):  
Ke Bi ◽  
◽  
Yue Tan ◽  
Ke Cheng ◽  
Qingfang Chen ◽  
...  
Keyword(s):  
Left Ventricle ◽  
Active Contour ◽  
Active Contour Model ◽  
Magnetic Resonance Images ◽  
Shape Similarity ◽  
The Novel ◽  
Mr Images ◽  
Cine Mr ◽  
Cardiac Cine ◽  
The Mean

<abstract> <p>Delineation of the boundaries of the Left Ventricle (LV) in cardiac Magnetic Resonance Images (MRI) is a hot topic due to its important diagnostic power. In this paper, an approach is proposed to extract the LV in a sequence of MR images. In the proposed paper, all images in the sequence are segmented simultaneously and the shape of the LV in each image is supposed to be similar to that of the LV in nearby images in the sequence. We coined the novel shape similarity constraint, and it is called sequential shape similarity (SSS in short). The proposed segmentation method takes the Active Contour Model as the base model and our previously proposed Gradient Vector Convolution (GVC) external force is also adopted. With the SSS constraint, the snake contour can accurately delineate the LV boundaries. We evaluate our method on two cardiac MRI datasets and the Mean Absolute Distance (MAD) metric and the Hausdorff Distance (HD) metric demonstrate that the proposed approach has good performance on segmenting the boundaries of the LV.</p> </abstract>

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