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An improved segmentation algorithm for quantification of myocardial infarction in contrast enhanced CMR images - validated in ex-vivo studies
- Source :
- Journal of Cardiovascular Magnetic Resonance
- Publication Year :
- 2014
- Publisher :
- BioMed Central, 2014.
-
Abstract
- Background T1-weighted contrast enhanced CMR images of explanted hearts in experimental studies provide a high resolution reference standard for quantification of myocardial infarction. Manual delineation is considered the reference standard, however it is time consuming and observer dependent. Especially since a data set may consist of more than 150 images with a resolution of typically 0.5×0.5×0.5 mm. Previous studies have used an algorithm for infarct quantification based on a fix number of 8 standard deviations (SD) from remote with manual corrections if necessary [1]. This algorithm may fail if images have different contrast to noise ratio, and is time consuming as the user needs to draw regions of interest in each slice. Therefore, the aim of this study was to provide a fully automated segmentation algorithm for quantification of myocardial infarction in T1-weighted contrast enhanced high resolution ex-vivo images.
- Subjects :
- Medicine(all)
Radiological and Ultrasound Technology
business.industry
High resolution
medicine.disease
Left ventricular mass
Contrast-to-noise ratio
Fully automated
Poster Presentation
medicine
Radiology, Nuclear Medicine and imaging
Segmentation
Myocardial infarction
Cardiology and Cardiovascular Medicine
business
User needs
Algorithm
Reference standards
Subjects
Details
- Language :
- English
- ISSN :
- 1532429X and 10976647
- Volume :
- 16
- Issue :
- Suppl 1
- Database :
- OpenAIRE
- Journal :
- Journal of Cardiovascular Magnetic Resonance
- Accession number :
- edsair.doi.dedup.....13f0cde552177256a3bc11559ba697fd