A method is proposed to determine the cone-beam x-ray acquisition geometry of an imaging system using a phantom consisting of discrete x-ray opaque markers defining two parallel rings sharing a common axis. The phantom generates an image of two ellipses which are fitted to an ellipse model. A phantom-centric coordinate system is used to simplify the equations describing the ellipse coefficients such that a solution describing the acquisition geometry can be obtained via numerical optimization of only three of the nine unknown variables. We perform simulations to show how errors in the fit of the ellipse coefficients affect estimates of the acquisition geometries. These simulations show that for ellipse projections sampled with 1200 markers, 25 microm errors in marker positions and a source-detector distance (SDD) of 1.6 m, we can measure angles describing detector rotation with a mean error of <0.002 degrees and a standard deviation (SD) of <0.03 degrees. The SDD has a mean error of 0.004 mm and SD = 0.24 mm. The largest error is associated with the determination of the point on the detector closest to the x-ray source (mean error = 0.05 mm, SD = 0.85 mm). A prototype phantom was built and results from x-ray experiments are presented.

Using fiber optic manufacturing techniques, it is possible to produce a radiographic grid that discriminates against scattered radiation in two dimensions. Such grids consist of septa composed of glass with a high lead content; the interspace material is air, so that approximately 80% of the grid area is open. In this way, effective high ratio grids can be produced with relatively low Bucky factors. The performance of samples of such grid material is characterized in terms of both scatter rejection and dose efficiency for application in digital mammography in both slot-beam and area-beam geometry. For area beams, five- to tenfold improved scatter rejection relative to conventional grids was observed. In slot configurations, such grids could provide improved SNR/dose performance and more effective utilization of the heat loading capability of the x-ray source.

Variable-density (VD) spiral k-space acquisitions are used to acquire high-resolution (0.78 mm), motion-compensated images of the coronary arteries. Unlike conventional methods, information for motion compensation is obtained directly from the coronary anatomy itself. Specifically, periods of minimal coronary distortion are identified by applying the correlation coefficient template matching algorithm to real-time images generated from the inner, high-density portions of the VD spirals. Combining the data associated with these images together, high-resolution, motion-compensated coronary images are generated. Because coronary motion is visualized directly, the need for cardiac-triggering, breath-holding, and navigator echoes is eliminated. The motion compensation capability of the technique is determined by the inner-spiral spatial and temporal resolution. Results indicate that the best performance is achieved using inner-spiral images with high spatial resolution (1.6 -2.9 mm), even though temporal resolution (four to six independent frames per second) suffers as a result. Image quality within the template region in healthy volunteers was found to be comparable to that achieved with cardiac-triggered breath-hold scans, although Key words: variable-density; template matching; coronary artery; motion compensation; real-time Diagnostic-quality MR coronary images must possess submillimeter spatial resolution. While the theoretical limits of MR do not preclude the attainment of such resolutions, respiratory-(1) and cardiac-(2) induced displacement and distortion (3) of the arteries can significantly degrade image quality. To counteract these effects, motion compensation schemes have been developed (4,5). With the evolution toward higher-resolution imaging, however, a number of concerns are arising with respect to their accuracy. Most of these approaches use indirect measures such as the position of bellows placed over the chest, ECG waveforms, and diaphragm position determined by navigator echoes to infer coronary motion. Recent studies have indicated that while indirect measures may correlate with coronary displacement, they do not give a precise characterization of the actual motion (1,6,7). Additionally, indirect measures generally do not give any indication of the degree of distortion associated with the coronary motion (3). Furthermore, arrhythmias and/or difficulties in breathholding, commonly found in patients with coronary disease, give rise to added difficulties in the application of these techniques (8).A technique that makes use of direct visualization of the coronary anatomy for motion compensation was developed recently by Hardy et al. (9). In this "adaptive averaging" technique, a series of interleaved high-resolution echo-planar images are acquired. From each of the individual interleaves, aliased "subimages" are formed. Since these subimages are generated from every interleaf, they provide real-time visualization of the coronary anatomy. Each subimage is used to evaluate the motion present during the...

In clinical computed tomography (CT) images, cortical bone features with sub-millimeter (sub-mm) thickness are substantially blurred, such that their thickness is overestimated and their intensity appears underestimated. Therefore, any inquiry of the geometry or the density of such bones based on these images is severely error prone. We present a model-based method for estimating the true thickness and intensity magnitude of cortical and trabecular bone layers at localized regions of complex shell bones down to 0.25 mm. The method also computes the width of the corresponding point spread function. This approach is applicable on any CT image data, and does not rely on any scanner-specific parameter inputs beyond what is inherently available in the images themselves. The method applied on CT intensity profiles of custom phantoms mimicking shell-bones produced average cortical thickness errors of 0.07 ± 0.04 mm versus an average error of 0.47 ± 0.29 mm in the untreated cases (t(55) = 10.92, p ≪ 0.001)). Similarly, the average error of intensity magnitude estimates of the method were 22 ± 2.2 HU versus an error of 445 ± 137 HU in the untreated cases (t(55) = 26.48, p ≪ 0.001)). The method was also used to correct the CT intensity profiles from a cadaveric specimen of the craniofacial skeleton (CFS) in 15 different regions. There was excellent agreement between the corrections and µCT intensity profiles of the same regions used as a 'gold standard' measure. These results set the groundwork towards restoring cortical bone geometry and intensity information in entire image data sets. This information is essential for the generation of finite element models of the CFS that can accurately describe the biomechanical behavior of its complex thin bone structures.