Literature DB >> 22119489

Detection of the whole myocardium in 2D-echocardiography for multiple orientations using a geometrically constrained level-set.

T Dietenbeck1, M Alessandrini, D Barbosa, J D'hooge, D Friboulet, O Bernard.   

Abstract

The segmentation of the myocardium in echocardiographic images is an important task for the diagnosis of heart disease. This task is difficult due to the inherent problems of echographic images (i.e. low contrast, speckle noise, signal dropout, presence of shadows). In this article, we propose a method to segment the whole myocardium (endocardial and epicardial contours) in 2D echographic images. This is achieved using a level-set model constrained by a new shape formulation that allows to model both contours. The novelty of this work also lays in the fact that our framework allows to segment the whole myocardium for the four main views used in clinical routine. The method is validated on a dataset of clinical images and compared with expert segmentation.
Copyright © 2011 Elsevier B.V. All rights reserved.

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Year:  2011        PMID: 22119489     DOI: 10.1016/j.media.2011.10.003

Source DB:  PubMed          Journal:  Med Image Anal        ISSN: 1361-8415            Impact factor:   8.545


  12 in total

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4.  Asynchronous changes of normal lung lobes during respiration based on quantitative computed tomography (CT).

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Journal:  Quant Imaging Med Surg       Date:  2022-03

5.  Left ventricle analysis in echocardiographic images using transfer learning.

Authors:  Hafida Belfilali; Frédéric Bousefsaf; Mahammed Messadi
Journal:  Phys Eng Sci Med       Date:  2022-09-21

6.  Automatic segmentation of right ventricular ultrasound images using sparse matrix transform and a level set.

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Journal:  Phys Med Biol       Date:  2013-10-10       Impact factor: 3.609

7.  Identifying radiotherapy target volumes in brain cancer by image analysis.

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Journal:  Healthc Technol Lett       Date:  2015-10-02

8.  Feature-based fuzzy connectedness segmentation of ultrasound images with an object completion step.

Authors:  Sylvia Rueda; Caroline L Knight; Aris T Papageorghiou; J Alison Noble
Journal:  Med Image Anal       Date:  2015-07-17       Impact factor: 8.545

9.  Evaluation of localized region-based segmentation algorithms for CT-based delineation of organs at risk in radiotherapy.

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Journal:  Phys Imaging Radiat Oncol       Date:  2018-03-05

10.  A Combined Fully Convolutional Networks and Deformable Model for Automatic Left Ventricle Segmentation Based on 3D Echocardiography.

Authors:  Suyu Dong; Gongning Luo; Kuanquan Wang; Shaodong Cao; Qince Li; Henggui Zhang
Journal:  Biomed Res Int       Date:  2018-09-10       Impact factor: 3.411

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