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Proceedings Paper

Visual servoing for automatic and uncalibrated percutaneous procedures
Author(s): Michael H. Loser; Nassir Navab; Benedicte Bascle; Russell H. Taylor
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Paper Abstract

Visual servoing is well established in the field of industrial robotics, when using CCD cameras. This paper describes one of the first medical implementations of uncalibrated visual servoing. To our knowledge, this is the first time that visual servoing is done using x-ray fluoroscopy. In this paper we present a new image based approach for semi-automatically guidance of a needle or surgical tool during percutaneous procedures and is based on a series of granted and pending US patent applications. It is a simple and accurate method which requires no prior calibration or registration. Therefore, no additional sensors, no stererotactic frame and no additional calibration phantom is needed. Our techniques provides accurate 3D alignment of the tool with respect to an anatomic target and estimates the required insertion depth. We implemented and verified this method with three different medical robots at the Computer Integrated Surgery (CIS) Lab at the Johns Hopkins University. First tests were performed using a CCD-camera and a mobile uniplanar x-ray fluoroscope as imaging modality. We used small metal balls of 4 mm in diameter as target points. These targets were placed 60 to 70 mm deep inside a test-phantom. Our method led to correct insertions with mean deviation of 0.20 mm with CCD camera and mean deviation of about 1.5 mm in clinical surrounding with an old x-ray imaging system, where the images were not of best quality. These promising results present this method as a serious alternative to other needle placement techniques, which require cumbersome and time consuming calibration procedures.

Paper Details

Date Published: 18 April 2000
PDF: 12 pages
Proc. SPIE 3976, Medical Imaging 2000: Image Display and Visualization, (18 April 2000); doi: 10.1117/12.383049
Show Author Affiliations
Michael H. Loser, Siemens AG (Germany)
Nassir Navab, Siemens Corporate Research, Inc. (United States)
Benedicte Bascle, Siemens Corporate Research, Inc. (United States)
Russell H. Taylor, Johns Hopkins Univ. (United States)

Published in SPIE Proceedings Vol. 3976:
Medical Imaging 2000: Image Display and Visualization
Seong Ki Mun, Editor(s)

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