Imaging phantom

About: Imaging phantom is a research topic. Over the lifetime, 28170 publications have been published within this topic receiving 510003 citations. The topic is also known as: phantom.

Decoupled automated rotational and translational registration for functional MRI time series data: the DART registration algorithm.

Abstract: A rapid, in-plane image registration algorithm that accurately estimates and corrects for rotational and translational motion is described. This automated, one-pass method achieves its computational efficiency by decoupling the estimation of rotation and translation, allowing the application of rapid cross-correlation and cross-spectrum techniques for the determination of displacement parameters. k-space regridding and modulation techniques are used for image correction as alternatives to linear interpolation. The performance of this method was analyzed with simulations and echo-planar image data from both phantoms and human subjects. The processing time for image registration on a Hewlett-Packard 735/125 is 7.5 s for a 128 x 128 pixel image and 1.7 s for a 64 x 64 pixel image. Imaging phantom data demonstrate the accuracy of the method (mean rotational error, -0.09 degrees; standard deviation = 0.17 degrees; range, -0.44 degrees to +0.31 degrees; mean translational error = -0.035 pixels; standard deviation = 0.054 pixels; range, -0.16 to +0.06 pixels). Registered human functional imaging data demonstrate a significant reduction in motion artifacts such as linear trends in pixel time series and activation artifacts due to stimulus-correlated motion. The advantages of this technique are its noniterative one-pass nature, the reduction in image degradation as compared to previous methods, and the speed of computation.

3D Feature Constrained Reconstruction for Low-Dose CT Imaging

Abstract: Low-dose computed tomography (LDCT) images are often highly degraded by amplified mottle noise and streak artifacts. Maintaining image quality under low-dose scan protocols is a well-known challenge. Recently, sparse representation-based techniques have been shown to be efficient in improving such CT images. In this paper, we propose a 3D feature constrained reconstruction (3D-FCR) algorithm for LDCT image reconstruction. The feature information used in the 3D-FCR algorithm relies on a 3D feature dictionary constructed from available high quality standard-dose CT sample. The CT voxels and the sparse coefficients are sequentially updated using an alternating minimization scheme. The performance of the 3D-FCR algorithm was assessed through experiments conducted on phantom simulation data and clinical data. A comparison with previously reported solutions was also performed. Qualitative and quantitative results show that the proposed method can lead to a promising improvement of LDCT image quality.

The exponential edge-gradient effect in x-ray computed tomography.

Abstract: The exponential edge-gradient effect must arise in any x-ray transmission CT scanner whenever long sharp edges of high contrast are encountered. The effect is non-linear and is due to the interaction of the exponential law of x-ray attenuation and the finite width of the scanning beam in the x-y plane. The error induced in the projection values is proved to be always negative. While the most common effect is lucent streaks emerging from single straight edges, it is demonstrated that dense streaks from pairs of edges are possible. It is shown that an exact correction of the error is possible only under very special (and rather unrealistic) circumstances in which an infinite number of samples per beam width are available and all thin rays making up the beam can be considered parallel. As a practical matter, nevertheless, increased sample density is highly desirable in making good approximate corrections; this is demonstrated with simulated scans. Two classes of approximate correction algorithms are described and their effectiveness evaluated on simulated CT phantom scans. One such algorithm is also shown to work well with a real scan of a physical phantom on a machine that provides approximately four samples per beam width.

Registration of Three-Dimensional Left Atrial Computed Tomographic Images With Projection Images Obtained Using Fluoroscopy

Abstract: Background— Anatomic structures such as the left atrium and the pulmonary veins (PVs) are not delineated by fluoroscopy because there is no contrast differentiation between them and the surrounding anatomy. Representation of an anatomic structure via a 3D model obtained from computed tomography (CT) imaging and subsequent projection of these images over the fluoroscopy system may help in navigation of the mapping and ablation catheter to the appropriate sites during electrophysiology procedures. Methods and Results— In this feasibility study, in vitro experiments were performed with a plastic heart model (phantom) with 2 catheters or radiopaque platinum beads placed in the phantom at the time of CT imaging and fluoroscopy. Subsequently, 20 consecutive patients underwent contrast-enhanced, ECG-gated CT scanning. Left atrial volumes were generated from the reconstructed data at &75% of the R-R interval during the cardiac cycle. Similarly, the superior vena cava and the coronary sinus were also reconstructed from these images. During the electrophysiology procedure, digital records (cine sequences) were obtained. Using predetermined algorithms, both the phantom model and the patients’ 3D left atrial models derived from the CT were registered with projection images of fluoroscopy. Registration was performed with a transformation that linked the superior vena cava and the coronary sinus from the CT model with a catheter placed inside the coronary sinus via the superior vena cava. Registration was successfully accomplished with the plastic phantom and in all 20 patients. Registration accuracy was assessed in the phantom by assessing the overlapping beads seen both in the CT and the fluoroscopy images. The mean registration error was 1.4 mm (range 0.9 to 2.3 mm). Accuracy of the registered images was assessed in patients with recordings from a basket catheter placed sequentially in the superior PVs and by injecting contrast into the PVs to assess overlapping of contrast-filled PVs with the corresponding vessels on the registered images. The images could be calibrated quite accurately. Any rotational error, which was usually minor, could be corrected by rotating the images as needed. Conclusions— Registration of 3D models of the left atrium and PVs with fluoroscopic images of the same is feasible and could enable appropriate navigation and localization of the mapping and ablation catheter during procedures such as atrial fibrillation ablation. Received May 27, 2005; revision received July 20, 2005; accepted August 22, 2005.