Back to Search Start Over

Evolution of a surgical system using deep learning in minimally invasive surgery (Review).

Authors :
Sone, Kenbun
Tanimoto, Saki
Toyohara, Yusuke
Taguchi, Ayumi
Miyamoto, Yuichiro
Mori, Mayuyo
Iriyama, Takayuki
Wada-Hiraike, Osamu
Osuga, Yutaka
Source :
Biomedical Reports; Jul2023, Vol. 19 Issue 1, pN.PAG-N.PAG, 1p
Publication Year :
2023

Abstract

Recently, artificial intelligence (AI) has been applied in various fields due to the development of new learning methods, such as deep learning, and the marked progress in computational processing speed. AI is also being applied in the medical field for medical image recognition and omics analysis of genomes and other data. Recently, AI applications for videos of minimally invasive surgeries have also advanced, and studies on such applications are increasing. In the present review, studies that focused on the following topics were selected: i) Organ and anatomy identification, ii) instrument identification, iii) procedure and surgical phase recognition, iv) surgery-time prediction, v) identification of an appropriate incision line, and vi) surgical education. The development of autonomous surgical robots is also progressing, with the Smart Tissue Autonomous Robot (STAR) and RAVEN systems being the most reported developments. STAR, in particular, is currently being used in laparoscopic imaging to recognize the surgical site from laparoscopic images and is in the process of establishing an automated suturing system, albeit in animal experiments. The present review examined the possibility of fully autonomous surgical robots in the future. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20499434
Volume :
19
Issue :
1
Database :
Complementary Index
Journal :
Biomedical Reports
Publication Type :
Academic Journal
Accession number :
164581772
Full Text :
https://doi.org/10.3892/br.2023.1628