Figure - PMC

Skip to main content

An official website of the United States government

Here's how you know

Here's how you know

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

View full-text article in PMC

. 2024 Apr 18;14:8951. doi: 10.1038/s41598-024-59114-3

Search in PMC
Search in PubMed
View in NLM Catalog
Add to search

© The Author(s) 2024

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

PMC Copyright notice

Automated volume transient analysis. LV fully automated volume transient analysis pipeline (top-left), along with patient S692 sample case, consisting of the following steps: (1.I.) the SAx stack (image I) is pre-processed normalizing for intensity, resolution and orientation and cropped to the region of interest, following the prior detection of the heart; (1.II.) the LV myocardium is fine segmented in the SAx stack (image II); (1.III) a volumetric segmentation is synthesized (image III) and the LV volume transient derived; (2) the conventional metrics of the volume transient are estimated (top-right); and (3) PCA analysis is applied on the transients to facilitate the supervise learning of MACE occurrence related features (AI-derived transient metrics). The red circle landmarks on the representative volume transient (top-right) correspond to: a, end-diastole; b, systolic peak velocity; c, end-systole; d, passive filling peak velocity; e, beginning of diastasis; f, mid-diastasis; g, end-diastasis; and h, active filling peak velocity. This figure is available in video format (see Supplementary Video 1).