Fiducial markers are reference points used in the registration of image space(s) with physical (patient) space. As applied to interactive, image-guided surgery, the registration of image space with physical space allo...
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Fiducial markers are reference points used in the registration of image space(s) with physical (patient) space. As applied to interactive, image-guided surgery, the registration of image space with physical space allows the current location of a surgical tool to be indicated on a computer display of patient-specific preoperative images. This intrasurgical guidance information is particularly valuable in surgery within the brain, where visual feedback is limited. The accuracy of the mapping between physical and image space depends upon the accuracy with which the fiducial markers were located in each coordinate system. To effect accurate space registration for interactive, image-guided neurosurgery, the use of permanent fiducial markers implanted into the surface of the skull is proposed in this paper. These small cylindrical markers are composed of materials that make them visible in the image sets. The challenge lies in locating the subcutaneous markers in physical space, This paper presents an ultrasonic technique for transcutaneously detecting the location of these markers. The technique incorporates an algorithm based on detection of characteristic properties of the reflected A-mode ultrasonic waveform. The results demonstrate that ultrasound is an appropriate technique for accurate transcutaneous marker localization. The companion paper to this article describes an automatic, enhanced implementation of the marker-localization theory described in this article.
The integration (or fusion) of two or more detection-localization systems often results in performance improvement, especially if they are complementary to each other. On the other hand, the cost of integration in add...
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The integration (or fusion) of two or more detection-localization systems often results in performance improvement, especially if they are complementary to each other. On the other hand, the cost of integration in additional signal processing and overhead may be considerable. As a figure of merit for this tradeoff, we propose the dB-gain-to-cost ratio and illustrate its evaluation by using a simple example. The example consists of a pair of detection-localization systems which have complementary features. One has higher resolution that the other, but is more susceptible to random disturbances. We model the first as a system which detects a signal in multiplicative and additive random disturbances and additive white noise. Thus, one main result is the derivation of the maximum likelihood detector under these disturbances. In the second system, we assume the random disturbances to be negligible. Hence, the maximum likelihood detector is the matched filter. Input data to both systems are two-dimensional arrays of real numbers corresponding to the same physical area under observation where the second data array has a coarser grid than the first, thus yielding poorer resolution. The detection probabilities, in terms of which the dB-gains are computed, are evaluated by Monte Carlo simulation.
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