ABSTRACT: To experimentally investigate whether a computed tomography (CT) system based on CdZnTe (CZT) detectors in conjunction with a least-squares parameter estimation technique can be used to decompose four different materials.The material decomposition process was divided into a segmentation task and a quantification task. A least-squares minimization algorithm was used to decompose materials with five measurements of the energy dependent linear attenuation coefficients. A small field-of-view energy discriminating CT system was built. The CT system consisted of an x-ray tube, a rotational stage, and an array of CZT detectors. The CZT array was composed of 64 pixels, each of which is 0.8 x 0.8 x 3 mm. Images were acquired at 80 kVp in fluoroscopic mode at 50 ms per frame. The detector resolved the x-ray spectrum into energy bins of 22-32, 33-39, 40-46, 47-56, and 57-80 keV. Four phantoms were constructed from polymethylmethacrylate (PMMA), polyethylene, polyoxymethylene, hydroxyapatite, and iodine. Three phantoms were composed of three materials with embedded hydroxyapatite (50, 150, 250, and 350 mg/ml) and iodine (4, 8, 12, and 16 mg/ml) contrast elements. One phantom was composed of four materials with embedded hydroxyapatite (150 and 350 mg/ml) and iodine (8 and 16 mg/ml). Calibrations consisted of PMMA phantoms with either hydroxyapatite (100, 200, 300, 400, and 500 mg/ml) or iodine (5, 15, 25, 35, and 45 mg/ml) embedded. Filtered backprojection and a ramp filter were used to reconstruct images from each energy bin. Material segmentation and quantification were performed and compared between different phantoms.All phantoms were decomposed accurately, but some voxels in the base material regions were incorrectly identified. Average quantification errors of hydroxyapatite/iodine were 9.26/7.13%, 7.73/5.58%, and 12.93/8.23% for the three-material PMMA, polyethylene, and polyoxymethylene phantoms, respectively. The average errors for the four-material phantom were 15.62% and 2.76% for hydroxyapatite and iodine, respectively.The calibrated least-squares minimization technique of decomposition performed well in breast imaging tasks with an energy resolving detector. This method can provide material basis images containing concentrations of the relevant materials that can potentially be valuable in the diagnostic process.
