ArticleThe international journal of cardiovascular imaging2018
Automatic regional analysis of myocardial native T1 values: left ventricle segmentation and AHA parcellations.
Article in The international journal of cardiovascular imaging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Automated Measurement of Native T1 and Extracellular Volume Fraction in Cardiac Magnetic Resonance Imaging Using a Commercially Available Deep Learning Algorithm.Korean journal of radiology · 2022Article
- Deep neural network ensemble for on-the-fly quality control-driven segmentation of cardiac MRI T1 mapping.Medical image analysis · 2021Article
- Reliable segmentation of 2D cardiac magnetic resonance perfusion image sequences using time as the 3rd dimension.European radiology · 2021Article
- Deep learning with attention supervision for automated motion artefact detection in quality control of cardiac T1-mapping.Artificial intelligence in medicine · 2020Article
- Cardiovascular imaging 2018 in the International Journal of Cardiovascular Imaging.The international journal of cardiovascular imaging · 2019Article
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Authors and funding
5 authors.
Funding
Abstract
Native T1 value is emerging as a reliable indicator of abnormal heart conditions related to myocardial fibrosis. Investigators have extensively used the standardized myocardial segmentation of the American Heart Association (AHA) to measure regional T1 values of the left ventricular (LV) walls. In this paper, we present a fully automatic system to analyze modified Look-Locker inversion recovery images and to report regional T1 values of AHA segments. Ten healthy individuals participated in the T1 mapping study with a 3.0 T scanner after providing informed consent. First, we obtained masks of an LV blood-pool region and LV walls by using an image synthesis method and a layer-growing method. Subsequently, the LV walls were divided into AHA segments by identifying the boundaries of the septal regions and by using a radial projection method. The layer-growing method significantly enhanced the accuracy of the derived myocardium mask. We compared the T1 values that were obtained using manual region of interest selections and those obtained using the automatic system. The average T1 difference of the calculated segments was 4.6 ± 1.5%. This study demonstrated a practical and robust method of obtaining native T1 values of AHA segments in LV walls.
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