Literature DB >> 9080352

Automated instrument tracking in robotically assisted laparoscopic surgery.

D R Uecker1, C Lee, Y F Wang, Y Wang.   

Abstract

This paper describes a practical and reliable image analysis and tracking algorithm to achieve automated instrument localization and scope maneuvering in robotically assisted laparoscopic surgery. Laparoscopy is a minimally invasive surgical procedure that utilizes multiple small incisions on the patient's body through which the surgeon inserts tools and a videoscope in order to conduct an operation. The scope relays images of internal organs to a camera, and the images are displayed on a video screen. The surgeon performs the operation by viewing the scope images rather than performing the traditional "open" procedure, where a large incision is made on the patient's body for direct viewing. The current mode of laparoscopy employs an assistant to hold the scope and position it in response to the surgeon's verbal commands. However, this results in suboptimal visual feedback, because the scope is often aimed incorrectly and vibrates due to hand trembling. We have developed a robotic laparoscope positioner to replace the assistant. The surgeon commands the robotic positioner through a hand/foot controller interface. To further simplify the human-machine interface that controls the robotic scope positioner, we report here a novel scope-positioning scheme using automated image analysis and robotic visual servoing. The scheme enables the surgeon to control visual feedback and to perform surgery more efficiently without requiring additional use of the hands.

Entities:  

Mesh:

Year:  1995        PMID: 9080352     DOI: 10.1002/(SICI)1522-712X(1995)1:6<308::AID-IGS3>3.0.CO;2-E

Source DB:  PubMed          Journal:  J Image Guid Surg        ISSN: 1078-7844


  6 in total

1.  Intra-operative surgical instrument usage detection on a multi-sensor table.

Authors:  Bernhard Glaser; Stefan Dänzer; Thomas Neumuth
Journal:  Int J Comput Assist Radiol Surg       Date:  2014-05-15       Impact factor: 2.924

2.  Surgical and Interventional Robotics: Part III: Surgical Assistance Systems.

Authors:  Gregory D Hager; Allison M Okamura; Peter Kazanzides; Louis L Whitcomb; Gabor Fichtinger; Russell H Taylor
Journal:  IEEE Robot Autom Mag       Date:  2008-12-01       Impact factor: 5.143

3.  A Kalman-Filter-Based Common Algorithm Approach for Object Detection in Surgery Scene to Assist Surgeon's Situation Awareness in Robot-Assisted Laparoscopic Surgery.

Authors:  Jiwon Ryu; Youngjin Moon; Jaesoon Choi; Hee Chan Kim
Journal:  J Healthc Eng       Date:  2018-05-02       Impact factor: 2.682

4.  Patch-based adaptive weighting with segmentation and scale (PAWSS) for visual tracking in surgical video.

Authors:  Xiaofei Du; Maximilian Allan; Sebastian Bodenstedt; Lena Maier-Hein; Stefanie Speidel; Alessio Dore; Danail Stoyanov
Journal:  Med Image Anal       Date:  2019-07-04       Impact factor: 8.545

5.  Robotic Endoscope Control Via Autonomous Instrument Tracking.

Authors:  Caspar Gruijthuijsen; Luis C Garcia-Peraza-Herrera; Gianni Borghesan; Dominiek Reynaerts; Jan Deprest; Sebastien Ourselin; Tom Vercauteren; Emmanuel Vander Poorten
Journal:  Front Robot AI       Date:  2022-04-11

6.  Limited generalizability of single deep neural network for surgical instrument segmentation in different surgical environments.

Authors:  Daichi Kitaguchi; Toru Fujino; Nobuyoshi Takeshita; Hiro Hasegawa; Kensaku Mori; Masaaki Ito
Journal:  Sci Rep       Date:  2022-07-22       Impact factor: 4.996

  6 in total

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