Robotic navigation with deep reinforcement learning in transthoracic echocardiography.

Journal: International journal of computer assisted radiology and surgery

PMID: 39304590

Abstract

PURPOSE: The search for heart components in robotic transthoracic echocardiography is a time-consuming process. This paper proposes an optimized robotic navigation system for heart components using deep reinforcement learning to achieve an efficient and effective search technique for heart components.

Authors

Yuuki Shida

Graduate School of Creative Science and Engineering, Waseda University, Tokyo, 169-8050, Japan. arares201@moegi.waseda.jp.
Souto Kumagai

Graduate School of Creative Science and Engineering, Waseda University, Tokyo, 169-8050, Japan.
Hiroyasu Iwata

Faculty of Science and Engineering, Waseda University, Tokyo, Japan.

Keywords

Algorithms Deep Learning Echocardiography Humans Mitral Valve Reinforcement Machine Learning Robotic Surgical Procedures Surgery, Computer-Assisted

External Resources

View on PubMed Access via DOI PubMed (39304590)

Robotic navigation with deep reinforcement learning in transthoracic echocardiography.

Abstract

Authors

Keywords

External Resources

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