Literature DB >> 17354955

Automated detection of left ventricle in 4D MR images: experience from a large study.

Xiang Lin1, Brett R Cowan, Alistair A Young.   

Abstract

We present a fully automated method to estimate the location and orientation of the left ventricle (LV) in four-dimensional (4D) cardiac magnetic resonance (CMR) images without any user input. The method is based on low-level image processing techniques incorporating anatomical knowledge and is able to provide rapid, robust feedback for automated scan planning or further processing. The method relies on a novel combination of temporal Fourier analysis of image cines with simple contour detection to achieve a fast localization of the heart. Quantitative validation was performed using 4D CMR datasets from 330 patients (54024 images) with a range of cardiac and vascular disease by comparing manual location with the automatic results. The method failed on one case, and showed average bias and precision of under 5mm in apical, mid-ventricular and basal slices in the remaining 329. The errors in automatic orientation were similar to the errors in scan planning as performed by experienced technicians.

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Year:  2006        PMID: 17354955     DOI: 10.1007/11866565_89

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  7 in total

1.  Unsupervised Myocardial Segmentation for Cardiac BOLD.

Authors:  Ilkay Oksuz; Anirban Mukhopadhyay; Rohan Dharmakumar; Sotirios A Tsaftaris
Journal:  IEEE Trans Med Imaging       Date:  2017-07-12       Impact factor: 10.048

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

Authors:  Li Kuo Tan; Yih Miin Liew; Einly Lim; Yang Faridah Abdul Aziz; Kok Han Chee; Robert A McLaughlin
Journal:  Med Biol Eng Comput       Date:  2017-11-17       Impact factor: 2.602

3.  Automated T(2) * measurements using supplementary field mapping to assess cardiac iron content.

Authors:  Brian A Taylor; Ralf B Loeffler; Ruitian Song; Mary E McCarville; Jane S Hankins; Claudia M Hillenbrand
Journal:  J Magn Reson Imaging       Date:  2013-01-04       Impact factor: 4.813

Review 4.  Artificial intelligence in pediatric and adult congenital cardiac MRI: an unmet clinical need.

Authors:  Arghavan Arafati; Peng Hu; J Paul Finn; Carsten Rickers; Andrew L Cheng; Hamid Jafarkhani; Arash Kheradvar
Journal:  Cardiovasc Diagn Ther       Date:  2019-10

5.  Fully automatic segmentation of 4D MRI for cardiac functional measurements.

Authors:  Yan Wang; Yue Zhang; Wanling Xuan; Evan Kao; Peng Cao; Bing Tian; Karen Ordovas; David Saloner; Jing Liu
Journal:  Med Phys       Date:  2018-11-20       Impact factor: 4.071

6.  Automatic localization of the left ventricle from cardiac cine magnetic resonance imaging: a new spectrum-based computer-aided tool.

Authors:  Liang Zhong; Jun-Mei Zhang; Xiaodan Zhao; Ru San Tan; Min Wan
Journal:  PLoS One       Date:  2014-04-10       Impact factor: 3.240

Review 7.  Artificial intelligence and cardiovascular imaging: A win-win combination.

Authors:  Luigi P Badano; Daria M Keller; Denisa Muraru; Camilla Torlasco; Gianfranco Parati
Journal:  Anatol J Cardiol       Date:  2020-10       Impact factor: 1.596

  7 in total

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