In this paper we present two novel techniques, namely a local unwarping polynomial (LUP) and a hierarchical radial basis function (HRBF) network, to correct geometric distortions in XRII images. The two techniques have been implemented and compared, in terms of residual error measured at control and intermediate points, with local and global methods reported in the previous literature. In particular, LUP rests on a locally optimized 3rd degree polynomial applied within each quadrilateral cell on the rectilinear calibration grid of points. HRBF, based on a feed-forward neural network paradigm, is constituted by a set of hierarchical layers at increasing cut-off frequency, each characterized by a set of Gaussian functions. Extensive experiments have been performed both on simulated and real data. In simulation, we tested the effect of pincushion, sigmoidal and local distortions, along with the number of calibration points. Provided that a sufficient number of cells of the calibration grid is available, the obtained accuracy for both LUP and HRBF is comparable to or better than that of global polynomial technique. Tests on real data, carried out by using two different (12 in. and 16 in.) XRIIs, showed that the global polynomial accuracy (0.16+/-0.08 pixels) is slightly worse than that of LUP (0.07+/-0.05 pixels) and HRBF (0.08+/-0.04 pixels). The effects of the discontinuity at the border of the local areas and the decreased accuracy at intermediate points, typical of local techniques, have been proved to be smoothed for both LUP and HRBF.

A noninvasive eye tracking system based on infrared 3-D video-oculographic techniques is proposed for the automatic monitoring of eye position and orientation in external beam radiotherapy of ocular tumors. The presented method can be applied for the real-time estimation of lesion position and tumor-beam misalignments, allowing automatic patient setup and eye movement gated treatments. A prototypal eye tracker was developed and tested on five subjects, achieving gaze estimation errors of 0.5° and eye monitoring frequencies of 125 Hz. The proposed application can potentially improve quality and efficacy of ocular radiotherapy treatments, currently based on invasive, qualitative, and manual control procedures.

An x-ray image intensifier (XRII) has many applications in diagnostic imaging, especially in real time. Unfortunately the inherent and external distortions (pincushion, S-distortion and local distortion) hinder any quantitative analysis of an image. In this paper an automatic real-time local distortion correction method for improving the quality of digital linear tomography images is presented. Using a digital signal processing (DSP), this method can work for an image up to 1Kx1Kx12 bit at 30fps. A local correction method has been used because it allows distortions such as those caused by poor axial alignment between the X-Ray cone beam and the XRII input surface and local distortions to be resolved that are generally neglected by global methods.

Global polynomial (GP) methods have been widely used to correct geometric image distortion of small-size (up to 30 cm) X-ray image intensifiers (XRIIs). This work confirms that this kind of approach is suitable for 40 cm XRIIs (now increasingly used). Nonetheless, two local methods, namely 3rd-order local un-warping polynomials (LUPs) and hierarchical radial basis function (HRBF) networks are proposed as alternative solutions. Extensive experimental tests were carried out to compare these methods with classical low-order local polynomial and GP techniques, in terms of residual error (RMSE) measured at points not used for parameter estimation. Simulations showed that the LUP and HRBF methods had accuracies comparable with that attained using GP methods. In detail, the LUP method (0.353 microm) performed worse than HRBF (0.348 microm) only for small grid spacing (15 x 15 control points); the accuracy of both HRBF (0.157 microm) and LUP (0.160 microm) methods was little affected by local distortions (30 x 30 control points); weak local distortions made the GP method poorer (0.320 microm). Tests on real data showed that LUP and HRBF had accuracies comparable with that of GP for both 30 cm (GP: 0.238 microm; LUP: 0.240 microm; HRBF: 0.238 microm) and 40 cm (GP: 0.164 microm; LUP: 0.164 microm; HRBF: 0.164 microm) XRIIs. The LUP-based distortion correction was implemented in real time for image correction in digital tomography applications.