The integration of 3D-imaging functionality into C-arm systems combines advantages of interventional X-ray systems, e.g. good patient access and live fluoroscopy, with 3D imaging capabilities similar to those of a CT-scanner. To date 3D-imaging with a C-arm system has been mainly used to visualize high contrast objects. However, the advent of high quality flat panel detectors improves the low contrast imaging capabilities. We discuss the influence of scattered radiation, beam hardening, truncated projections, quantization and detector recording levels on the image quality.
Subsequently, we present algorithms and methods to correct these effects in order to achieve low contrast resolution. The performance of our pre- and post-reconstructive correction procedures is demonstrated by first clinical cases.
Breast cancer diagnosis may be improved by optical fluorescence imaging techniques in the near-infrared wavelength range. We have shown that the recently proposed space-space MUSIC (multiple signal classification) algorithm allows the 3-D localization of focal fluorophore-tagged lesions in a turbid medium from 2-D fluorescence data obtained from laser excitations at different positions. The data are assumed to be measured with two parallel planar sensor arrays on the top and bottom of the medium. The laser sources are integrated at different positions in one of the planes. The space-space data are arranged into an M×N matrix (M, number of sensors; N, number of excitation sources). A singular-value decomposition (SVD) of this matrix yields the detectable number of spot regions with linearly independent behavior with respect to the laser excitation positions and thus allows definition of a signal subspace. Matches between this signal subspace and data from model spots are tested at scanned points in a model medium viewed as the breast region under study. The locations of best matches are then considered the centers of gravity of focal lesions. The optical model used was unbounded and optically homogeneous. Nevertheless, simulated spots in bounded, inhomogeneous media modeling the breast could be localized accurately.
We present a novel method, space-space MUSIC (MUltiple SIgnal Classification), to localize three-dimensionally focal fluorophore-tagged lesions activated subsequently by different laser source posi-tions from multi-sensor fluorescence data obtained from a single measurement plane.
Matches between a signal subspace derived from the measured data and data from model spots allow 3D determination of the centers-of-gravity of fluorescence regions. Simulated spots in bounded, inho-mogeneous media could be localized accurately. The algorithm has shown to be robust against patient-dependent parameters, such as optical background parameters. The algorithm does also not consider medium boundaries.
This paper proposes three methods for reconstructing magnetic-source biocurrent distribution. These methods are more effective than the conventional pseudo-inversion-based reconstruction when the signal-to-noise ratio of measured data is low. First, a method of estimating magnetic- source-current covariance matrix using the measured-data covariance matrix is presented, and an averaged current squared-intensity distribution is reconstructed using the diagonal terms of the covariance matrix. The use of its off-diagonal terms leads to the second method that can separate magnetic-source activities correlated to each other from the uncorrelated activities. The third method is the Wiener reconstruction of current distributions based on the estimated source covariance matrix. Results of computer simulation demonstrate the effectiveness of those three methods.