Automatic multi-view pose estimation in focused cardiac ultrasound.
Med Image Anal
; 94: 103146, 2024 May.
Article
en En
| MEDLINE
| ID: mdl-38537416
ABSTRACT
Focused cardiac ultrasound (FoCUS) is a valuable point-of-care method for evaluating cardiovascular structures and function, but its scope is limited by equipment and operator's experience, resulting in primarily qualitative 2D exams. This study presents a novel framework to automatically estimate the 3D spatial relationship between standard FoCUS views. The proposed framework uses a multi-view U-Net-like fully convolutional neural network to regress line-based heatmaps representing the most likely areas of intersection between input images. The lines that best fit the regressed heatmaps are then extracted, and a system of nonlinear equations based on the intersection between view triplets is created and solved to determine the relative 3D pose between all input images. The feasibility and accuracy of the proposed pipeline were validated using a novel realistic in silico FoCUS dataset, demonstrating promising results. Interestingly, as shown in preliminary experiments, the estimation of the 2D images' relative poses enables the application of 3D image analysis methods and paves the way for 3D quantitative assessments in FoCUS examinations.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Redes Neurales de la Computación
/
Imagenología Tridimensional
Límite:
Humans
Idioma:
En
Revista:
Med Image Anal
Asunto de la revista:
DIAGNOSTICO POR IMAGEM
Año:
2024
Tipo del documento:
Article
País de afiliación:
Portugal