## Abstract ## Purpose To develop a technique based on image noise distribution for automated endocardial border detection from cardiac magnetic resonance (CMR) images throughout the cardiac cycle, validate it, and test its clinical utility. ## Materials and Methods Images obtained in 36 patient
Multicenter trial of automated border detection in cardiac MR imaging
✍ Scribed by Steven R. Fleagle; Daniel R. Thedens; William Stanford; Roderic I. Pettigrew; Nathaniel Reichek; David J. Skorton
- Publisher
- John Wiley and Sons
- Year
- 1993
- Tongue
- English
- Weight
- 736 KB
- Volume
- 3
- Category
- Article
- ISSN
- 1053-1807
No coin nor oath required. For personal study only.
✦ Synopsis
Abstract
The purpose of the present study was to evaluate the robustness of a method of automated border detection in cardiac magnetic resonance (MR) imaging. Thirty‐seven short‐axis spin‐echo cardiac images were acquired from three medical centers, each with its own image‐acquisition protocol. Endo‐ and epicardial borders and areas were derived from these images with a graph‐searching‐based method of edge detection. Computer results were compared with observer‐traced borders. The method accurately defined myocardial borders in 36 of 37 images (97%), with excellent agreement between computer‐ and observer‐derived endocardial and epicardial areas (correlation coefficients,.94‐.99). The algorithm worked equally well for data from all three centers, despite differences in image‐acquisition protocols, MR systems, and field strengths. These data suggest that a method of computer‐assisted edge detection based on graphsearching principles yields endocardial and epicardial areas that correlate well with those derived by an independent observer.
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