Surgical robotics beyond enhanced dexterity instrumentation: a survey of machine learning techniques and their role in intelligent and autonomous surgical actions

被引:152
作者
Kassahun, Yohannes [1 ]
Yu, Bingbin [2 ]
Tibebu, Abraham Temesgen [2 ]
Stoyanov, Danail [3 ]
Giannarou, Stamatia [4 ]
Metzen, Jan Hendrik [2 ]
Vander Poorten, Emmanuel [5 ]
机构
[1] German Res Ctr Artificial Intelligence, Robot Innovat Ctr, Robert Hooke Str 1, D-28359 Bremen, Germany
[2] Univ Bremen, Fac Math & Comp Sci 3, Robert Hooke Str 1, D-28359 Bremen, Germany
[3] UCL, Dept Comp Sci, Ctr Med Image Comp, London, England
[4] Univ London Imperial Coll Sci Technol & Med, Hamlyn Ctr Robot Surg, London, England
[5] Univ Leuven, Dept Mech Engn, Celestijnenlaan 300B, B-3001 Heverlee, Belgium
基金
英国工程与自然科学研究理事会;
关键词
Surgical robotics; Skill learning; Skill analysis; Learning to perceive; MINIMALLY INVASIVE SURGERY; RANDOMIZED CLINICAL-TRIAL; LAPAROSCOPIC SURGERY; HEART-SURGERY; SYSTEM; SKILLS; ASSISTANT; MOTION; SEGMENTATION; GUIDANCE;
D O I
10.1007/s11548-015-1305-z
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Advances in technology and computing play an increasingly important role in the evolution of modern surgical techniques and paradigms. This article reviews the current role of machine learning (ML) techniques in the context of surgery with a focus on surgical robotics (SR). Also, we provide a perspective on the future possibilities for enhancing the effectiveness of procedures by integrating ML in the operating room. The review is focused on ML techniques directly applied to surgery, surgical robotics, surgical training and assessment. The widespread use of ML methods in diagnosis and medical image computing is beyond the scope of the review. Searches were performed on PubMed and IEEE Explore using combinations of keywords: ML, surgery, robotics, surgical and medical robotics, skill learning, skill analysis and learning to perceive. Studies making use of ML methods in the context of surgery are increasingly being reported. In particular, there is an increasing interest in using ML for developing tools to understand and model surgical skill and competence or to extract surgical workflow. Many researchers begin to integrate this understanding into the control of recent surgical robots and devices. ML is an expanding field. It is popular as it allows efficient processing of vast amounts of data for interpreting and real-time decision making. Already widely used in imaging and diagnosis, it is believed that ML will also play an important role in surgery and interventional treatments. In particular, ML could become a game changer into the conception of cognitive surgical robots. Such robots endowed with cognitive skills would assist the surgical team also on a cognitive level, such as possibly lowering the mental load of the team. For example, ML could help extracting surgical skill, learned through demonstration by human experts, and could transfer this to robotic skills. Such intelligent surgical assistance would significantly surpass the state of the art in surgical robotics. Current devices possess no intelligence whatsoever and are merely advanced and expensive instruments.
引用
收藏
页码:553 / 568
页数:16
相关论文
共 159 条
[1]  
Abbeel, 2004, ICML 2004
[2]   Image-guided control of a robot for medical ultrasound [J].
Abolmaesumi, P ;
Salcudean, SE ;
Zhu, WH ;
Sirouspour, MR ;
DiMaio, SP .
IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION, 2002, 18 (01) :11-23
[3]   The cyberknife: A frameless robotic system for radiosurgery [J].
Adler, JR ;
Chang, SD ;
Murphy, MJ ;
Doty, J ;
Geis, P ;
Hancock, SL .
STEREOTACTIC AND FUNCTIONAL NEUROSURGERY, 1997, 69 (1-4) :124-128
[4]   Image-guided robotic radiosurgery [J].
Adler, JR ;
Murphy, MJ ;
Chang, SD ;
Hancock, SL .
NEUROSURGERY, 1999, 44 (06) :1299-1306
[5]  
Ahmadi SA, 2006, LECT NOTES COMPUT SC, V4190, P420
[6]   Observational tools for assessment of procedural skills: a systematic review [J].
Ahmed, Kamran ;
Miskovic, Danilo ;
Darzi, Ara ;
Athanasiou, Thanos ;
Hanna, George B. .
AMERICAN JOURNAL OF SURGERY, 2011, 202 (04) :469-U161
[7]  
[Anonymous], P SPIE MED IMAGING
[8]  
[Anonymous], 2008, P MICCAI WORKSH SYST
[9]  
[Anonymous], 2013, P 16 INT S ROB RES I
[10]  
ASADA H, 1991, 1991 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1-3, P2442, DOI 10.1109/ROBOT.1991.131990