TY - JOUR
AU - Vander Poorten, Emmanuel
AB - Int J CARS (2016) 11:553–568 DOI 10.1007/s11548-015-1305-z REVIEW ARTICLE Surgical robotics beyond enhanced dexterity instrumentation: a survey of machine learning techniques and their role in intelligent and autonomous surgical actions 1 2 2 Yohannes Kassahun · Bingbin Yu · Abraham Temesgen Tibebu · 3 4 2 Danail Stoyanov · Stamatia Giannarou · Jan Hendrik Metzen · Emmanuel Vander Poorten Received: 1 April 2015 / Accepted: 21 September 2015 / Published online: 8 October 2015 © CARS 2015 Abstract extract surgical workflow. Many researchers begin to inte- Purpose Advances in technology and computing play an grate this understanding into the control of recent surgical increasingly important role in the evolution of modern surgi- robots and devices. cal techniques and paradigms. This article reviews the current Conclusion ML is an expanding field. It is popular as it role of machine learning (ML) techniques in the context of allows efficient processing of vast amounts of data for inter- surgery with a focus on surgical robotics (SR). Also, we pro- preting and real-time decision making. Already widely used vide a perspective on the future possibilities for enhancing in imaging and diagnosis, it is believed that ML will also play the effectiveness of procedures 
TI - Surgical robotics beyond enhanced dexterity instrumentation: a survey of machine learning techniques and their role in intelligent and autonomous surgical actions
JF - International Journal of Computer Assisted Radiology and Surgery
DO - 10.1007/s11548-015-1305-z
DA - 2015-10-08
UR - https://www.deepdyve.com/lp/springer-journals/surgical-robotics-beyond-enhanced-dexterity-instrumentation-a-survey-1ct7H8wwRg
SP - 553
EP - 568
VL - 11
IS - 4
DP - DeepDyve
ER -