Automated 2-D and 3-D Left Atrial Volume Measurements Using Deep Learning.
Ultrasound Med Biol
; 50(1): 47-56, 2024 01.
Article
en En
| MEDLINE
| ID: mdl-37813702
ABSTRACT
OBJECTIVE:
Echocardiography, a critical tool for assessing left atrial (LA) volume, often relies on manual or semi-automated measurements. This study introduces a fully automated, real-time method for measuring LA volume in both 2-D and 3-D imaging, in the aim of offering accuracy comparable to that of expert assessments while saving time and reducing operator variability.METHODS:
We developed an automated pipeline comprising a network to identify the end-systole (ES) time point and robust 2-D and 3-D U-Nets for segmentation. We employed data sets of 789 2-D images and 286 3-D recordings and explored various training regimes, including recurrent networks and pseudo-labeling, to estimate volume curves.RESULTS:
Our baseline results revealed an average volume difference of 2.9 mL for 2-D and 7.8 mL for 3-D, respectively, compared with manual methods. The application of pseudo-labeling to all frames in the cine loop generally led to more robust volume curves and notably improved ES measurement in cases with limited data.CONCLUSION:
Our results highlight the potential of automated LA volume estimation in clinical practice. The proposed prototype application, capable of processing real-time data from a clinical ultrasound scanner, provides valuable temporal volume curve information in the echo lab.Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Aprendizaje Profundo
Tipo de estudio:
Guideline
Idioma:
En
Revista:
Ultrasound Med Biol
Año:
2024
Tipo del documento:
Article