Automatic segmentation of the left ventricle in a cardiac MR short axis image using blind morphological operation

2018 ◽  
Vol 133 (4) ◽  
Author(s):  
Mehreen Irshad ◽  
Nazeer Muhammad ◽  
Muhammad Sharif ◽  
Mussarat Yasmeen
Keyword(s):  
Left Ventricle ◽  
Automatic Segmentation ◽  
Short Axis ◽  
Morphological Operation ◽  
Short Axis Image ◽  
Cardiac Mr

scholarly journals Fully automatic segmentation of right and left ventricle on short-axis cardiac MRI images

2020 ◽  
Vol 85 ◽  
pp. 101786
Author(s):  
Adam Budai ◽  
Ferenc I. Suhai ◽  
Kristof Csorba ◽  
Attila Toth ◽  
Liliana Szabo ◽  
...  
Keyword(s):  
Left Ventricle ◽  
Cardiac Mri ◽  
Automatic Segmentation ◽  
Short Axis ◽  
Fully Automatic

MDCT Determination of Volume and Function of the Left Ventricle: Are Short-Axis Image Reformations Necessary?

2006 ◽  
Vol 186 (6_supplement_2) ◽  
pp. S371-S378 ◽  
Author(s):  
Kai U. Juergens ◽  
Harald Seifarth ◽  
David Maintz ◽  
Matthias Grude ◽  
Murat Ozgun ◽  
...  
Keyword(s):  
Left Ventricle ◽  
Short Axis ◽  
Short Axis Image ◽  
And Function

scholarly journals P418Cine short-axis image quality optimisation on 3T cardiac MR

2019 ◽  
Vol 20 (Supplement_2) ◽  
Author(s):  
L Tribuna ◽  
A Clemente ◽  
T Teixeira ◽  
P Sa Couto ◽  
P Oliveira ◽  
...  
Keyword(s):  
Image Quality ◽  
Short Axis ◽  
Short Axis Image ◽  
Cardiac Mr ◽  
Quality Optimisation

3D Segmentation of the Left Ventricle Combining Long- and Short-axis MR Images

2009 ◽  
Vol 48 (04) ◽  
pp. 340-343 ◽  
Author(s):  
J. Relan ◽  
M. Groth ◽  
K. Müllerleile ◽  
H. Handels ◽  
D. Säring
Keyword(s):  
Left Ventricle ◽  
Automatic Segmentation ◽  
Surface Model ◽  
Short Axis ◽  
Segmentation Method ◽  
Cine Mr ◽  
Robust Segmentation ◽  
Lv Remodeling ◽  
Volume Properties ◽  
The Mean

Summary Objectives: Segmentation of the left ventricle (LV) is required to quantify LV remodeling after myocardial infarction. Therefore spatiotemporal cine MR sequences including long-axis and short-axis images are acquired. In this paper a new segmentation method for fast and robust segmentation of the left ventricle is presented. Methods: The new approach considers the position of the mitral valve and the apex as well as the long-axis contours to generate a 3D LV surface model. The segmentation result can be checked and adjusted in the short-axis images. Finally quantitative parameters were extracted. Results: For evaluation the LV was segmented in eight datasets of the same subject by two medical experts using a contour drawing tool and the new segmentation tool. The results of both methods were compared concerning interaction time and intra- and inter-observer variance. The presented segmentation method proved to be fast. The mean difference and standard deviation of all parameters are decreased. In case of intra-observer comparison e.g. the mean ESV difference is reduced from 8.8% to 0.5%. Conclusion: A semi-automatic LV segmentation method has been developed that combines long- and short-axis views. Using the presented approach the intra- and inter-observer difference as well as the time for the segmentation process are decreased. So the semi-automatic segmentation using long-and short-axis information proved to be fast and robust for the quantification of LV mass and volume properties.

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