This paper defines a simple protocol for competitive and quantified evaluation of electromagnetic tracking systems such as the NDI Aurora (A) and Ascension microBIRD with dipole transmitter (B). It establishes new methods and a new phantom design which assesses the reproducibility and allows comparability with different tracking systems in a consistent environment. A machined base plate was designed and manufactured in which a 50 mm grid of holes was precisely drilled for position measurements. In the center a circle of 32 equispaced holes enables the accurate measurement of rotation. The sensors can be clamped in a small mount which fits into pairs of grid holes on the base plate. Relative positional/orientational errors are found by subtracting the known distances/ rotations between the machined locations from the differences of the mean observed positions/ rotation. To measure the influence of metallic objects we inserted rods made of steel (SST 303, SST 416), aluminum, and bronze into the sensitive volume between sensor and emitter. We calculated the fiducial registration error and fiducial location error with a standard stylus calibration for both tracking systems and assessed two different methods of stylus calibration. The positional jitter amounted to 0.14 mm(A) and 0.08 mm(B). A relative positional error of 0.96 mm +/- 0.68 mm, range -0.06 mm; 2.23 mm(A) and 1.14 mm +/- 0.78 mm, range -3.72 mm; 1.57 mm(B) for a given distance of 50 mm was found. The relative rotation error was found to be 0.51 degrees (A)/0.04 degrees (B). The most relevant distortion caused by metallic objects results from SST 416. The maximum error 4.2 mm(A)/ > or = 100 mm(B) occurs when the rod is close to the sensor(20 mm). While (B) is more sensitive with respect to metallic objects, (A) is less accurate concerning orientation measurements. (B) showed a systematic error when distances are calculated.

Due to their high accuracy and robustness, the Tabletop FG and the Compact FG could eliminate the need for compensation of EM field distortions in certain CT-guided interventions.

Computer-aided surgery (CAS), the intraoperative application of biomedical visualization techniques, appears to be one of the most promising fields of application for augmented reality (AR), the display of additional computer-generated graphics over a real-world scene. Typically a device such as a head-mounted display (HMD) is used for AR. However, considerable technical problems connected with AR have limited the intraoperative application of HMDs up to now. One of the difficulties in using HMDs is the requirement for a common optical focal plane for both the realworld scene and the computer-generated image, and acceptance of the HMD by the user in a surgical environment. In order to increase the clinical acceptance of AR, we have adapted the Varioscope (Life Optics, Vienna), a miniature, cost-effective head-mounted operating binocular, for AR. In this paper, we present the basic design of the modified HMD, and the method and results of an extensive laboratory study for photogrammetric calibration of the Varioscope's computer displays to a real-world scene. In a series of 16 calibrations with varying zoom factors and object distances, mean calibration error was found to be 1.24 +/- 0.38 pixels or 0.12 +/- 0.05 mm for a 640 x 480 display. Maximum error accounted for 3.33 +/- 1.04 pixels or 0.33 +/- 0.12 mm. The location of a position measurement probe of an optical tracking system was transformed to the display with an error of less than 1 mm in the real world in 56% of all cases. For the remaining cases, error was below 2 mm. We conclude that the accuracy achieved in our experiments is sufficient for a wide range of CAS applications.

In this article, the authors evaluate a merit function for 2D/3D registration called stochastic rank correlation (SRC). SRC is characterized by the fact that differences in image intensity do not influence the registration result; it therefore combines the numerical advantages of cross correlation (CC)-type merit functions with the flexibility of mutual-information-type merit functions. The basic idea is that registration is achieved on a random subset of the image, which allows for an efficient computation of Spearman's rank correlation coefficient. This measure is, by nature, invariant to monotonic intensity transforms in the images under comparison, which renders it an ideal solution for intramodal images acquired at different energy levels as encountered in intrafractional kV imaging in image-guided radiotherapy. Initial evaluation was undertaken using a 2D/3D registration reference image dataset of a cadaver spine. Even with no radiometric calibration, SRC shows a significant improvement in robustness and stability compared to CC. Pattern intensity, another merit function that was evaluated for comparison, gave rather poor results due to its limited convergence range. The time required for SRC with 5% image content compares well to the other merit functions; increasing the image content does not significantly influence the algorithm accuracy. The authors conclude that SRC is a promising measure for 2D/3D registration in IGRT and image-guided therapy in general.