Fully automated segmentation of left ventricle using dual dynamic programming in cardiac cine MR images

2016 ◽  
Author(s):  
Luan Jiang ◽  
Shan Ling ◽  
Qiang Li
Keyword(s):  
Dynamic Programming ◽  
Left Ventricle ◽  
Automated Segmentation ◽  
Mr Images ◽  
Cine Mr ◽  
Cardiac Cine ◽  
Dual Dynamic Programming

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>

scholarly journals Fully Automatic Left Ventricle Segmentation in Cardiac Cine MR Images Using Registration and Minimum Surfaces

2009 ◽  
Author(s):  
Marie-pierre Jolly
Keyword(s):  
Left Ventricle ◽  
Shortest Paths ◽  
Blood Pool ◽  
Grand Challenge ◽  
Mr Images ◽  
Cine Mr ◽  
Cardiac Cine ◽  
Cine Study ◽  
Fully Automatic ◽  
Ventricle Segmentation

This paper describes a fully automatic system to segment the left ventricle in all slices and all phases of a magnetic resonance cardiac cine study. After localizing the left ventricle blood pool using motion, thresholding and clustering, slices are segmented sequentially. For each slice, deformable registration is used to align all the phases, candidate contours are recovered in the average image using shortest paths, and a minimal surface is built to generate the final contours. The advantage of our method is that the resulting contours follow the edges in each phase and are consistent over time. As part of the MICCAI grand challenge on left ventricle segmentation, we demonstrate using 15 training datasets and 15 validation datasets that the results are very good with average errors around 2 mm and the method is ready for clinical routine.

scholarly journals A deep learning-based approach for automatic segmentation and quantification of the left ventricle from cardiac cine MR images

2020 ◽  
Vol 81 ◽  
pp. 101717 ◽  
Author(s):  
Hisham Abdeltawab ◽  
Fahmi Khalifa ◽  
Fatma Taher ◽  
Norah Saleh Alghamdi ◽  
Mohammed Ghazal ◽  
...  
Keyword(s):  
Deep Learning ◽  
Left Ventricle ◽  
Automatic Segmentation ◽  
Mr Images ◽  
Cine Mr ◽  
Cardiac Cine

An SPCNN-GVF-based approach for the automatic segmentation of left ventricle in cardiac cine MR images

2016 ◽  
Vol 11 (11) ◽  
pp. 1951-1964 ◽  
Author(s):  
Yurun Ma ◽  
Li Wang ◽  
Yide Ma ◽  
Min Dong ◽  
Shiqiang Du ◽  
...  
Keyword(s):  
Left Ventricle ◽  
Automatic Segmentation ◽  
Mr Images ◽  
Cine Mr ◽  
Cardiac Cine

scholarly journals An open, clinically-validated database of 3D+t cine-MR images of the left ventricle with associated manual and automated segmentation

2007 ◽  
Author(s):  
Laurent Najman ◽  
Jean Cousty ◽  
Michel Couprie ◽  
Hugues Talbot ◽  
Stéphanie Clément-Guinaudeau ◽  
...  
Keyword(s):  
Left Ventricle ◽  
Software Package ◽  
Point Of View ◽  
Clinical Validation ◽  
Automated Segmentation ◽  
Mr Images ◽  
Validation Process ◽  
Cine Mr ◽  
Clinical Point ◽  
Voxel Data

In this paper, we describe a database of cine-MR (3D+t) images of the left ventricle. This database contains the voxel data, one automated and two manual segmentations for each sequence of images. The segmentations are validated from a clinical point of view. We detail how the images were obtained, as well as how the associated segmentations were performed. We also provide the data clinical validation process.This database, including tools to compute quantitative measures and the software package used to obtain the automated segmentation, is freely available for research purposes.

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