Evaluation of Origin Ensemble algorithm for image reconstruction for pixelated solid-state detectors with large number of channels

Improved iterative reconstruction method for Compton imaging using median filter

A Compton camera is a device for imaging a radio-source distribution without using a mechanical collimator. Ordered-subset expectation-maximization (OS-EM) is widely used to reconstruct Compton images. However, the OS-EM algorithm tends to over-concentrate and amplify noise in the reconstructed image. It is, thus, necessary to optimize the number of iterations to develop high-quality images, but this has not yet been achieved. In this paper, we apply a median filter to an OS-EM algorithm and introduce a median root prior expectation-maximization (MRP-EM) algorithm to overcome this problem. In MRP-EM, the median filter is used to update the image in each iteration. We evaluated the quality of images reconstructed by our proposed method and compared them with those reconstructed by conventional algorithms using mathematical phantoms. The spatial resolution was estimated using the images of two point sources. Reproducibility was evaluated on an ellipsoidal phantom by calculating the residual sum of squares, zero-mean normalized cross-correlation, and mutual information. In addition, we evaluated the semi-quantitative performance and uniformity on the ellipsoidal phantom. MRP-EM reduces the generated noise and is robust with respect to the number of iterations. An evaluation of the reconstructed image quality using some statistical indices shows that our proposed method delivers better results than conventional techniques.

Evaluation of Compton gamma camera prototype based on pixelated CdTe detectors

A proposed Compton camera prototype based on pixelated CdTe is simulated and evaluated in order to establish its feasibility and expected performance in real laboratory tests. The system is based on module units containing a 2×4 array of square CdTe detectors of 10×10 mm² area and 2 mm thickness. The detectors are pixelated and stacked forming a 3D detector with voxel sizes of 2 × 1 × 2 mm³. The camera performance is simulated with Geant4-based Architecture for Medicine-Oriented Simulations(GAMOS) and the Origin Ensemble(OE) algorithm is used for the image reconstruction. The simulation shows that the camera can operate with up to 10⁴ Bq source activities with equal efficiency and is completely saturated at 10⁹ Bq. The efficiency of the system is evaluated using a simulated ¹⁸F point source phantom in the center of the Field-of-View (FOV) achieving an intrinsic efficiency of 0.4 counts per second per kilobecquerel. The spatial resolution measured from the point spread function (PSF) shows a FWHM of 1.5 mm along the direction perpendicular to the scatterer, making it possible to distinguish two points at 3 mm separation with a peak-to-valley ratio of 8.

Evaluation of imaging systems using the posterior variance of emission counts

We investigate an approach to evaluation of emission-tomography (ET) imaging systems used for region-of-interest (ROI) estimation tasks. In the evaluation we employ the concept of "emission counts" (EC), which are the number of events per voxel emitted during a scan. We use the reduction in posterior variance of ROI EC, compared to the prior ROI EC variance, as the metric of primary interest, which we call the "posterior variance reduction index" (PVRI). Systems that achieve a higher PVRI are considered superior to systems with lower PVRI. The approach is independent of the reconstruction method and is applicable to all photon-limited data types including list-mode data. We analyzed this approach using a model of 2-D tomography, and compared our results to the classical theory of tomographic sampling. We found that performance evaluations using the PVRI index were consistent with the classical theory. System evaluation based on EC posterior variance is an intuitively appealing and physically meaningful method that is useful for evaluation of system performance in ROI quantitation tasks.