Your browser doesn't support javascript.
loading
Development and preliminary testing of a prior knowledge-based visual navigation system for cardiac ultrasound scanning.
Hao, Mingrui; Guo, Jun; Liu, Cuicui; Chen, Chen; Wang, Shuangyi.
Afiliación
  • Hao M; State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190 China.
  • Guo J; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100043 China.
  • Liu C; Hangtian Center Hospital, Beijing, 100049 China.
  • Chen C; Hangtian Center Hospital, Beijing, 100049 China.
  • Wang S; State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190 China.
Biomed Eng Lett ; 14(2): 307-316, 2024 Mar.
Article en En | MEDLINE | ID: mdl-38374906
ABSTRACT

Purpose:

Ultrasound is widely used to diagnose disease and guide surgery because it is versatile, inexpensive and radiation-free. However, image acquisition is dependent on the operation of a professional sonographer, which is a difficult skill to learn for a wider range of non-sonographers.

Methods:

We propose a prior knowledge-based visual navigation method to obtain three important standard ultrasound views of the heart, based on the sonographer's skill learning and augmented reality prompts. The key information about the probe movement was captured using vision-based tracking and normalisation methods on 14 volunteers, based on a professional sonographer's practice. An augmented reality-based navigation method was then proposed to guide operators with no ultrasound experience to find standard views of the heart in a second set of three volunteers.

Results:

Through quantitative analysis and qualitative scoring, the results showed that the proposed method can effectively guide non-sonographers to obtain standard views with diagnostic value.

Conclusion:

It is believed that the method proposed in this paper has clear application value in primary care, and expansion of the data will allow the accuracy of the navigation to be further improved.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Biomed Eng Lett Año: 2024 Tipo del documento: Article Pais de publicación: Alemania

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Biomed Eng Lett Año: 2024 Tipo del documento: Article Pais de publicación: Alemania