Literature DB >> 26740057

Distance regularized two level sets for segmentation of left and right ventricles from cine-MRI.

Yu Liu1, Gabriella Captur2, James C Moon2, Shuxu Guo1, Xiaoping Yang3, Shaoxiang Zhang4, Chunming Li5.   

Abstract

This paper presents a new level set method for segmentation of cardiac left and right ventricles. We extend the edge based distance regularized level set evolution (DRLSE) model in Li et al. (2010) to a two-level-set formulation, with the 0-level set and k-level set representing the endocardium and epicardium, respectively. The extraction of endocardium and epicardium is obtained as a result of the interactive curve evolution of the 0 and k level sets derived from the proposed variational level set formulation. The initialization of the level set function in the proposed two-level-set DRLSE model is generated from roughly located endocardium, which can be performed by applying the original DRLSE model. Experimental results have demonstrated the effectiveness of the proposed two-level-set DRLSE model.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Left and right ventricles; MRI; Segmentation; Two-level-set

Mesh:

Year:  2015        PMID: 26740057     DOI: 10.1016/j.mri.2015.12.027

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  9 in total

1.  Myocardium segmentation from DE MRI with guided random walks and sparse shape representation.

Authors:  Jie Liu; Xiahai Zhuang; Hongzhi Xie; Shuyang Zhang; Lixu Gu
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-07-07       Impact factor: 2.924

2.  A deep Boltzmann machine-driven level set method for heart motion tracking using cine MRI images.

Authors:  Jian Wu; Thomas R Mazur; Su Ruan; Chunfeng Lian; Nalini Daniel; Hilary Lashmett; Laura Ochoa; Imran Zoberi; Mark A Anastasio; H Michael Gach; Sasa Mutic; Maria Thomas; Hua Li
Journal:  Med Image Anal       Date:  2018-04-06       Impact factor: 8.545

3.  An integrated multi-objective whale optimized support vector machine and local texture feature model for severity prediction in subjects with cardiovascular disorder.

Authors:  M Muthulakshmi; G Kavitha
Journal:  Int J Comput Assist Radiol Surg       Date:  2020-03-09       Impact factor: 2.924

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

Authors:  Hisham Abdeltawab; Fahmi Khalifa; Fatma Taher; Norah Saleh Alghamdi; Mohammed Ghazal; Garth Beache; Tamer Mohamed; Robert Keynton; Ayman El-Baz
Journal:  Comput Med Imaging Graph       Date:  2020-03-12       Impact factor: 4.790

5.  Real-Time Lung Tumor Tracking Using a CUDA Enabled Nonrigid Registration Algorithm for MRI.

Authors:  Nazanin Tahmasebi; Pierre Boulanger; Jihyun Yun; Gino Fallone; Michelle Noga; Kumaradevan Punithakumar
Journal:  IEEE J Transl Eng Health Med       Date:  2020-04-24       Impact factor: 3.316

6.  Segmentation of Left and Right Ventricles in Cardiac MRI Using Active Contours.

Authors:  Shafiullah Soomro; Farhan Akram; Asad Munir; Chang Ha Lee; Kwang Nam Choi
Journal:  Comput Math Methods Med       Date:  2017-08-08       Impact factor: 2.238

7.  A Deep Learning Segmentation Approach in Free-Breathing Real-Time Cardiac Magnetic Resonance Imaging.

Authors:  Fan Yang; Yan Zhang; Pinggui Lei; Lihui Wang; Yuehong Miao; Hong Xie; Zhu Zeng
Journal:  Biomed Res Int       Date:  2019-07-30       Impact factor: 3.411

8.  Automatic Left Ventricle Segmentation from Short-Axis Cardiac MRI Images Based on Fully Convolutional Neural Network.

Authors:  Zakarya Farea Shaaf; Muhammad Mahadi Abdul Jamil; Radzi Ambar; Ahmed Abdu Alattab; Anwar Ali Yahya; Yousef Asiri
Journal:  Diagnostics (Basel)       Date:  2022-02-05

9.  Intelligent Segmentation Algorithm for Diagnosis of Meniere's Disease in the Inner Auditory Canal Using MRI Images with Three-Dimensional Level Set.

Authors:  Ting Liu; Ying Xu; Yujuan An; Hongzhou Ge
Journal:  Contrast Media Mol Imaging       Date:  2021-07-20       Impact factor: 3.161

  9 in total

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