Automatic localization of the left ventricle from cardiac cine magnetic resonance imaging: a new spectrum-based computer-aided tool.
Traditionally, cardiac image analysis is done manually. Automatic image processing can help with the repetitive tasks, and also deal with huge amounts of data, a task which would be humanly tedious. This study aims to develop a spectrum-based computer-aided tool to locate the left ventricle using im...
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2014-01-01
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doaj-891a3f7c8376424b803a7ffc8c5f1f0e2021-03-04T09:35:16ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0194e9238210.1371/journal.pone.0092382Automatic localization of the left ventricle from cardiac cine magnetic resonance imaging: a new spectrum-based computer-aided tool.Liang ZhongJun-Mei ZhangXiaodan ZhaoRu San TanMin WanTraditionally, cardiac image analysis is done manually. Automatic image processing can help with the repetitive tasks, and also deal with huge amounts of data, a task which would be humanly tedious. This study aims to develop a spectrum-based computer-aided tool to locate the left ventricle using images obtained via cardiac magnetic resonance imaging. Discrete Fourier Transform was conducted pixelwise on the image sequence. Harmonic images of all frequencies were analyzed visually and quantitatively to determine different patterns of the left and right ventricles on spectrum. The first and fifth harmonic images were selected to perform an anisotropic weighted circle Hough detection. This tool was then tested in ten volunteers. Our tool was able to locate the left ventricle in all cases and had a significantly higher cropping ratio of 0.165 than did earlier studies. In conclusion, a new spectrum-based computer aided tool has been proposed and developed for automatic left ventricle localization. The development of this technique, which will enable the automatic location and further segmentation of the left ventricle, will have a significant impact in research and in diagnostic settings. We envisage that this automated method could be used by radiographers and cardiologists to diagnose and assess ventricular function in patients with diverse heart diseases.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24722328/pdf/?tool=EBI |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Liang Zhong Jun-Mei Zhang Xiaodan Zhao Ru San Tan Min Wan |
spellingShingle |
Liang Zhong Jun-Mei Zhang Xiaodan Zhao Ru San Tan Min Wan Automatic localization of the left ventricle from cardiac cine magnetic resonance imaging: a new spectrum-based computer-aided tool. PLoS ONE |
author_facet |
Liang Zhong Jun-Mei Zhang Xiaodan Zhao Ru San Tan Min Wan |
author_sort |
Liang Zhong |
title |
Automatic localization of the left ventricle from cardiac cine magnetic resonance imaging: a new spectrum-based computer-aided tool. |
title_short |
Automatic localization of the left ventricle from cardiac cine magnetic resonance imaging: a new spectrum-based computer-aided tool. |
title_full |
Automatic localization of the left ventricle from cardiac cine magnetic resonance imaging: a new spectrum-based computer-aided tool. |
title_fullStr |
Automatic localization of the left ventricle from cardiac cine magnetic resonance imaging: a new spectrum-based computer-aided tool. |
title_full_unstemmed |
Automatic localization of the left ventricle from cardiac cine magnetic resonance imaging: a new spectrum-based computer-aided tool. |
title_sort |
automatic localization of the left ventricle from cardiac cine magnetic resonance imaging: a new spectrum-based computer-aided tool. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2014-01-01 |
description |
Traditionally, cardiac image analysis is done manually. Automatic image processing can help with the repetitive tasks, and also deal with huge amounts of data, a task which would be humanly tedious. This study aims to develop a spectrum-based computer-aided tool to locate the left ventricle using images obtained via cardiac magnetic resonance imaging. Discrete Fourier Transform was conducted pixelwise on the image sequence. Harmonic images of all frequencies were analyzed visually and quantitatively to determine different patterns of the left and right ventricles on spectrum. The first and fifth harmonic images were selected to perform an anisotropic weighted circle Hough detection. This tool was then tested in ten volunteers. Our tool was able to locate the left ventricle in all cases and had a significantly higher cropping ratio of 0.165 than did earlier studies. In conclusion, a new spectrum-based computer aided tool has been proposed and developed for automatic left ventricle localization. The development of this technique, which will enable the automatic location and further segmentation of the left ventricle, will have a significant impact in research and in diagnostic settings. We envisage that this automated method could be used by radiographers and cardiologists to diagnose and assess ventricular function in patients with diverse heart diseases. |
url |
https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24722328/pdf/?tool=EBI |
work_keys_str_mv |
AT liangzhong automaticlocalizationoftheleftventriclefromcardiaccinemagneticresonanceimaginganewspectrumbasedcomputeraidedtool AT junmeizhang automaticlocalizationoftheleftventriclefromcardiaccinemagneticresonanceimaginganewspectrumbasedcomputeraidedtool AT xiaodanzhao automaticlocalizationoftheleftventriclefromcardiaccinemagneticresonanceimaginganewspectrumbasedcomputeraidedtool AT rusantan automaticlocalizationoftheleftventriclefromcardiaccinemagneticresonanceimaginganewspectrumbasedcomputeraidedtool AT minwan automaticlocalizationoftheleftventriclefromcardiaccinemagneticresonanceimaginganewspectrumbasedcomputeraidedtool |
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