GOAL: We present a novel "pick-up" ultrasound transducer for intraabdominal robot-assisted minimally invasive surgery. Such a "pick-up" ultrasound transducer is inserted through an abdominal incision at the beginning of the procedure and remains in the abdominal cavity throughout, eliminating the need for a dedicated port or a patient bedside surgical assistant. The transducer has a handle that can be grasped in a repeatable manner using a da Vinci Prograsp tool, allowing the transducer to be accurately manipulated by the surgeon using the da Vinci Robot. This is one way to enable 3-D tracking of the transducer, and, thus, mapping of the vasculature. The 3-D vascular images can be used to register preoperative CT to intraoperative camera images. METHODS: To demonstrate the feasibility of the approach, we use an ultrasound vessel phantom to register a CT surface model to extracted ultrasound vessel models. The 3-D vascular phantom images are generated by segmenting B-mode images and tracking the pick-up ultrasound transducer with the da Vinci kinematics, internal electromagnetic sensor, or visible fiducials suitable for camera tracking. RESULTS: Reconstruction results using da Vinci kinematics for tracking give a target registration error of 5.4 ± 1.7 mm.
GOAL: We present a novel "pick-up" ultrasound transducer for intraabdominal robot-assisted minimally invasive surgery. Such a "pick-up" ultrasound transducer is inserted through an abdominal incision at the beginning of the procedure and remains in the abdominal cavity throughout, eliminating the need for a dedicated port or a patient bedside surgical assistant. The transducer has a handle that can be grasped in a repeatable manner using a da Vinci Prograsp tool, allowing the transducer to be accurately manipulated by the surgeon using the da Vinci Robot. This is one way to enable 3-D tracking of the transducer, and, thus, mapping of the vasculature. The 3-D vascular images can be used to register preoperative CT to intraoperative camera images. METHODS: To demonstrate the feasibility of the approach, we use an ultrasound vessel phantom to register a CT surface model to extracted ultrasound vessel models. The 3-D vascular phantom images are generated by segmenting B-mode images and tracking the pick-up ultrasound transducer with the da Vinci kinematics, internal electromagnetic sensor, or visible fiducials suitable for camera tracking. RESULTS: Reconstruction results using da Vinci kinematics for tracking give a target registration error of 5.4 ± 1.7 mm.
Authors: Xinyang Liu; William Plishker; Timothy D Kane; David A Geller; Lung W Lau; Jun Tashiro; Karun Sharma; Raj Shekhar Journal: Int J Comput Assist Radiol Surg Date: 2020-04-22 Impact factor: 2.924
Authors: James M Ferguson; E Bryn Pitt; Andria A Remirez; Michael A Siebold; Alan Kuntz; Nicholas L Kavoussi; Eric J Barth; S Duke Herrell; Robert J Webster Journal: IEEE Trans Med Robot Bionics Date: 2020-05-01
Authors: James M Ferguson; Bryn Pitt; Alan Kuntz; Josephine Granna; Nicholas L Kavoussi; Naren Nimmagadda; Eric J Barth; Stanley Duke Herrell; Robert J Webster Journal: Int J Med Robot Date: 2020-09-01 Impact factor: 2.483
Authors: Philip Edgcumbe; Rohit Singla; Philip Pratt; Caitlin Schneider; Christopher Nguan; Robert Rohling Journal: J Med Imaging (Bellingham) Date: 2018-02-14