Ilmar A. Hein

Feldkamp-based cone-beam reconstruction for gantry-tilted helical multislice CT

Depending on the clinical application, it is frequently necessary to tilt the gantry of an x-ray CT system with respect to the patient and couch. For single-slice fan-beam systems, tilting the gantry introduces no errors or artifacts. Most current systems, however, are helical multislice systems with up to 16 slices. The multislice helical reconstruction algorithms used to create CT images must be modified to account for tilting of the gantry. If they are not, the quality of reconstructed images will be poor with the presence of significant artifacts, such as smearing and double-imaging of anatomical structures. Current CT systems employ three primary types of reconstruction algorithms: helical fan-beam approximation, advanced single-slice rebinning, and Feldkamp-based algorithms. This paper presents a generalized helical cone-beam Feldkamp-based algorithm that is valid for both tilted and nontilted orientations of the gantry. Unlike some of the other algorithms, generalization of the Feldkamp algorithm to include gantry tilt is simple and straightforward with no significant increase in computational complexity. The effect of gantry tilt for helical Feldkamp reconstruction is to introduce a lateral shift in the isocenter of the reconstructed slice of interest, which is a function of the tilt, couch speed, and view angle. The lateral shift is easily calculated and incorporated into the helical Feldkamp backprojection algorithm. A tilt-generalized helical Feldkamp algorithm has been developed and incorporated into Aquilion 16-slice CT (Toshiba, Japan) scanners. This paper describes modifications necessary for the tilt generalization and its verification.

Double-centering method for increasing efficiency of cone-beam X-ray CT reconstruction

A method of increasing the efficiency of hardware-based circular and helical cone beam x-Ray CT reconstruction is presented. During reconstruction, an image slice at any arbitrary axial position is created by backprojecting reconstructed image pixels to corresponding positions on the detector array. This is computationally inefficient for cylindrical arrays because the backprojection equations for the channel and segment positions involve time-consuming arctangent calculations. Since the detector array matrix is smaller than the reconstruction matrix, backprojection speed can be increased if the system geometry is changed so that the arctangent calculations are performed on the detector array matrix rather than the reconstruction matrix. The most efficient configuration is where a row of reconstructed image pixels projects to a single row of detector channels with constant segment number and constant spacing along the channels. This configuration can be achieved by double centering; which consists of reprojecting the original cylindrical array projection data onto a flat virtual detector located in the xz plane. A double-centering algorithm with corresponding cone-beam reconstruction algorithm has been developed and implemented on a PC for the circular case. Cone-beam circular projection data from a ball phantom has been generated by simulation, double-centered, and reconstructed. The image quality of the double-centered reconstructions has been assessed, and the details and tradeoffs of practical implementation from an image quality standpoint are discussed.

Clinical usefulness of automatic phase selection in coronary CT angiography (CTA)

With high-speed multislice helical CT, the time needed to select the optimal cardiac phase accounts for a large percentage of the coronary CT angiography examination time because the scan time is short. To reduce the phase selection time, we have developed an automatic cardiac phase selection algorithm and implemented it in the Aquilion 64 scanner. This algorithm calculates the absolute sum of the differences between two raw data sets for subsequent cardiac phases (e.g., 4% and 0%) and generates a velocity curve representing the magnitude of cardiac motion velocity for the entire heart volume. Normally, the velocity curve has two local minimum slow-motion phases corresponding to end-systole and mid-diastole. By applying these local minimum phases in reconstruction, stationary cardiac images can be reconstructed automatically. In this report, the algorithm for generating the velocity curve and the processing time for selecting the optimal cardiac phase are discussed. The accuracy of this method is compared with that of the conventional manual method. In the manual method, a sample plane containing all four cardiac chambers was selected, reconstruction was performed for all phases at 2% intervals, and images were visually evaluated. Optimal phase selection required about 5 min/exam. With automatic phase selection, optimal phase selection required only about 1 min/exam, and the cardiac phases were close to those selected using the manual method. Automatic phase selection substantially reduces the time needed to select the optimal phase and increases patient throughput. Moreover, the influence of operator skill in selecting the optimal phase is minimized.

Up-sampling with Shift Method for Windmill Correction

We suggest a simple and efficient approach to reduce, and, in some cases, eliminate the windmill artifact. Our method does not require hardware changes. The idea is to improve the z-sampling by applying up-sampling in the detector row direction. One recent result show that the linear interpolation can be improved by shifting the samples by some small amount; we utilize this approach for our purposes. Evaluation shows that using some specified amount of the shift in interpolation, the proposed method provides a significant improvement of the windmill artifact with the clinical data, without a noticeable loss of z-resolution.

Tilted helical Feldkamp cone-beam reconstruction algorithm for multislice CT

In many clinical applications, it is necessary to tilt the gantry of an X-ray CT system with respect to the patient. Tilting the gantry introduces no complications for single-slice fan-beam systems; however, most systems today are helical multislice systems with up to 16 slices (and this number is sure to increase in the future). The image reconstruction algorithms used in multislice helical CT systems must be modified to compensate for the tilt. If they are not, the quality of reconstructed images will be poor with the presence of significant artifacts produced by the tilt. Practical helical multislice algorithms currently incorporated in today’s systems include helical fan-beam, ASSR (Advanced single-slice rebinning), and Feldkamp algorithms. This paper presents the modifications necessary to compensate for gantry tilt for the helical cone-beam Feldkamp algorithm implemented by Toshiba (referred to as TCOT for true cone-beam tomography). Unlike some of the other algorithms, gantry tilt compensation is simple and straightforward to implement with no significant increase in computational complexity. It will be shown that the effect of the gantry tilt is to introduce a lateral shift in the isocenter of the reconstructed slice of interest, which is a function of the tilt, couch speed, and view angle. This lateral shift is easily calculated and incorporated into the backprojection algorithm. The tilt-compensated algorithm is called T-TCOT. Experimental tilted-gantry data has been obtained with 8- and 16 slice Toshiba Aquilion systems, and examples of uncompensated and tilt compensated images are presented.

System optics in back projection and/or forward projection for model-based iterative reconstruction

Advantages of iterative reconstruction (IR) algorithms over standard filtered backprojection (FBP) algorithms include improved resolution and better noise performance, and many IR algorithms have been described in the literature. More recently model-based IR algorithms (MBIR) have been developed, which incorporate accurate system models into IR, resulting in better image quality than IR algorithms without a system model. This work investigates the resolution improvement achieved when a system optics model (SOM) has been included in a standard OS-SART algorithm. Three OS-SART algorithms have been compared: (1) “Pencil beam” (IR-P) with no system optics; (2) system optics included in forward projection (IR-SOM-FP), and (3) system optics included in both forward and backprojection (IRSOM-FPBP). Simulated reconstructions of a 0.2 mm bead show that IR-SOM-FPBP produced a FWHM resolution of 0.41 mm, considerably better than FBPJ (0.87 mm), IR-P (0.63 mm), and IR-SOM-FP (0.59 mm).