REAL PHANTOM DATASETS FOR THE EVALUATION OF RECONSTRUCTION ALGORITHMS AT VARIOUS DOSE CONDITIONS

ABSTRACT To reduce the radiation dose delivered to patients, a number of novel computed tomography (CT) reconstruction algorithms have been proposed to recover image s from the sparsely sampled datasets or the data sets from low dose exposure . However, the performanc e of these algorithms has not been quantitatively evaluated with realistic CT datasets in an easily reproducible fashion . Here, w e present four CT phantom datasets acquired from our bench -top micro -CT system. Such datasets can be used to provide the baseline for comparison among various CT reconstruction algorithms , in terms of noise level , contrast -to-noise ratio (C NR) , uniformity, spatial resolution and CT number accuracy . Index Terms ² CT Data sets , CT P han tom , Low Dose , Compressive Sensing , Iterative Reconstruction 1. INTRODUCTION The radiation harm induced by medical CT imaging motivates the development of low -dose imaging techniques . The radiation exposure delivered to the patients can be significantly reduced by utilizing low tube current , sparse ly sampled x-ray projection s, and advanced reconstruction algorithms . T he conventional analytic reconstruction methods are limited by high noise level , small angular sampling and artifacts from projection truncation . In contrary, the recent improvement on iterative reconstruction algorithms enables enhance d image quality using computer -simulated datasets or realistic medical datasets from commercial CT scanner s [1 -4] . Despite of many reported progresses on reconstruction algorithms , the related medical dataset s are proprietary and frequently not available to the public . The lack of raw datasets limits the reproducibility and dissemination of the advances in reconstruction algorithms. To address this limitation , here we provide four CT datasets collected from two in-house micro -CT phantom s and a rat specimen . Using the datasets, w e also demonstrate the evaluation on two frequently used reconstruction algorithms - filtered -back -projection ( FBP ) and compressed sensing (CS) based simultaneous -algebraic -reconstruction -technique (SART ). The se datasets can be used for evaluating the performance of reconstruction algorithms in terms of noise level, CNR , uniformity , spatial resolution and CT number accuracy . The organization of this paper is as follows. Firs t, data description is presented in section 2 . In section 3, we introduce the evaluation methods . In section 4, we demonstrate and evaluate the representative reconstruction algorithms . S ection 5 is the discussion and conclusion. 2. DATASETS DESCRIPTION 2.1 Data acquisition All datasets were collected from our bench -top micro -CT scanner . The micro -CT system (Figure 1) consists of a n Oxford micro -focus x -ray source ( focal spot size ~1 0µm ), a Hamamatsu flat panel x -ray detector , and a rotation stage . The detector has a n active area of 50.6mm by 50.6mm. It contains 1012 by 1012 active detector elements and each element is of 50µm by 50µm. The cone -beam circular trajectory was used for data acquisition. D uring the scan, the sample was rotated by the rotation stage, while the x -ray source and the detector were stationary. For each dataset , 720 or 360 projection s were collected over 360o . T wo datasets were collected from a water phantom (diameter : 25.5mm) , utilizing different scan parameters and imaging geometr ies. Due to the difference in radiation doses  WKH WZR GDWDVHWV ZHUH QDPHG DV ³KLJK -dose ´ DQG³ORZ -dose ´ UHVSHFWLYHO\ The third dataset was collected from a tungsten wire (diameter : 25 µm) phantom usi ng the same protocol and imaging geometry as the high -dose dataset. Both the water phantom and the wire phantom were made up with acrylic. The fourth dataset was collected from a rat specimen . In practice, due to imperfect system setup, the center of the detector is always slightly shifted within the detector plane (which is parallel to x -z plane ) (Figure 1). The center offset of detector for each dataset was measured along x -axis and z -axis. The sca n protocols and other parameters used in the acquisition of these datasets are shown in Table 1. 978-1-4673-1961-4/14/$31.00 ©2014 IEEE 65