Comparison of Image Processing Techniques for Nonviable Tissue Quantification in Late Gadolinium Enhancement Cardiac Magnetic Resonance Images
The aim of this study was to compare the performance of quantitative methods, either semiautomated or automated, for left ventricular (LV) nonviable tissue analysis from cardiac magnetic resonance late gadolinium enhancement (CMR-LGE) images. The investigated segmentation techniques were: (i) n-stan...
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| Published in | Journal of thoracic imaging Vol. 31; no. 3; p. 168 |
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| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
01.05.2016
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0883-5993 1536-0237 1536-0237 |
| DOI | 10.1097/RTI.0000000000000206 |
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| Abstract | The aim of this study was to compare the performance of quantitative methods, either semiautomated or automated, for left ventricular (LV) nonviable tissue analysis from cardiac magnetic resonance late gadolinium enhancement (CMR-LGE) images.
The investigated segmentation techniques were: (i) n-standard deviations thresholding; (ii) full width at half maximum thresholding; (iii) Gaussian mixture model classification; and (iv) fuzzy c-means clustering. These algorithms were applied either in each short axis slice (single-slice approach) or globally considering the entire short-axis stack covering the LV (global approach). CMR-LGE images from 20 patients with ischemic cardiomyopathy were retrospectively selected, and results from each technique were assessed against manual tracing.
All methods provided comparable performance in terms of accuracy in scar detection, computation of local transmurality, and high correlation in scar mass compared with the manual technique. In general, no significant difference between single-slice and global approach was noted. The reproducibility of manual and investigated techniques was confirmed in all cases with slightly lower results for the nSD approach.
Automated techniques resulted in accurate and reproducible evaluation of LV scars from CMR-LGE in ischemic patients with performance similar to the manual technique. Their application could minimize user interaction and computational time, even when compared with semiautomated approaches. |
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| AbstractList | The aim of this study was to compare the performance of quantitative methods, either semiautomated or automated, for left ventricular (LV) nonviable tissue analysis from cardiac magnetic resonance late gadolinium enhancement (CMR-LGE) images.
The investigated segmentation techniques were: (i) n-standard deviations thresholding; (ii) full width at half maximum thresholding; (iii) Gaussian mixture model classification; and (iv) fuzzy c-means clustering. These algorithms were applied either in each short axis slice (single-slice approach) or globally considering the entire short-axis stack covering the LV (global approach). CMR-LGE images from 20 patients with ischemic cardiomyopathy were retrospectively selected, and results from each technique were assessed against manual tracing.
All methods provided comparable performance in terms of accuracy in scar detection, computation of local transmurality, and high correlation in scar mass compared with the manual technique. In general, no significant difference between single-slice and global approach was noted. The reproducibility of manual and investigated techniques was confirmed in all cases with slightly lower results for the nSD approach.
Automated techniques resulted in accurate and reproducible evaluation of LV scars from CMR-LGE in ischemic patients with performance similar to the manual technique. Their application could minimize user interaction and computational time, even when compared with semiautomated approaches. |
| Author | Carminati, M Chiara Caiani, Enrico G Boniotti, Cinzia Fusini, Laura Andreini, Daniele Pepi, Mauro Pontone, Gianluca |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/27043426$$D View this record in MEDLINE/PubMed |
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| Snippet | The aim of this study was to compare the performance of quantitative methods, either semiautomated or automated, for left ventricular (LV) nonviable tissue... |
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| SubjectTerms | Aged Algorithms Cicatrix - diagnostic imaging Contrast Media Female Heart Ventricles - diagnostic imaging Humans Image Enhancement - methods Image Processing, Computer-Assisted - methods Magnetic Resonance Imaging - methods Male Meglumine - analogs & derivatives Myocardial Infarction - diagnostic imaging Organometallic Compounds Reproducibility of Results |
| Title | Comparison of Image Processing Techniques for Nonviable Tissue Quantification in Late Gadolinium Enhancement Cardiac Magnetic Resonance Images |
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