{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Huang KC"],"funding":["Ministry of Science and Technology, Taiwan"],"pagination":["2274-2286"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11522271"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["37(5)"],"pubmed_abstract":["The left ventricular global longitudinal strain (LVGLS) is a crucial prognostic indicator. However, inconsistencies in measurements due to the speckle tracking algorithm and manual adjustments have hindered its standardization and democratization. To solve this issue, we proposed a fully automated strain measurement by artificial intelligence-assisted LV segmentation contours. The LV segmentation model was trained from echocardiograms of 368 adults (11,125 frames). We compared the registration-like effects of dynamic time warping (DTW) with speckle tracking on a synthetic echocardiographic dataset in experiment-1. In experiment-2, we enrolled 80 patients to compare the DTW method with commercially available software. In experiment-3, we combined the segmentation model and DTW method to cre"],"journal":["Journal of imaging informatics in medicine"],"pubmed_title":["Left Ventricular Segmentation, Warping, and Myocardial Registration for Automated Strain Measurement."],"pmcid":["PMC11522271"],"funding_grant_id":["MOST 111-2628-B-002-034-MY3","MOST 110-2314-B002-210-MY3"],"pubmed_authors":["Lee CK","Lin DS","Lin TT","Lin LY","Huang KC","Jeng GS","Lin LC"],"additional_accession":[]},"is_claimable":false,"name":"Left Ventricular Segmentation, Warping, and Myocardial Registration for Automated Strain Measurement.","description":"The left ventricular global longitudinal strain (LVGLS) is a crucial prognostic indicator. However, inconsistencies in measurements due to the speckle tracking algorithm and manual adjustments have hindered its standardization and democratization. To solve this issue, we proposed a fully automated strain measurement by artificial intelligence-assisted LV segmentation contours. The LV segmentation model was trained from echocardiograms of 368 adults (11,125 frames). We compared the registration-like effects of dynamic time warping (DTW) with speckle tracking on a synthetic echocardiographic dataset in experiment-1. In experiment-2, we enrolled 80 patients to compare the DTW method with commercially available software. In experiment-3, we combined the segmentation model and DTW method to cre","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Oct","modification":"2026-07-15T14:41:40.918Z","creation":"2025-04-06T15:23:47.431Z"},"accession":"S-EPMC11522271","cross_references":{"pubmed":["38639806"],"doi":["10.1007/s10278-024-01119-5"]}}