The purpose of this study was to evaluate the performance of computer-aided diagnosis (CAD) system detecting pulmonary nodules for the various CT image qualities of the low dose CT cancer screening. Sixty three chest examinations with sixty-four pulmonary nodules consisting mainly ground-glass opacity (GGO) were used. All the CT images were acquired by using a multi-slice CT scanner Asteion with 4 detector rows system (Toshiba Medical Systems, Japan) with 0.75-second rotating time and 30mA. After the examination, CT image reconstructions were performed for every CT data set using seven reconstruction kernels and three sorts of slice thickness. Totally twenty-one data sets for a patient, namely 1323 data sets with about 60 thousands CT images which is 30.1GB data sets were investigated. Nodule detections were carried out using a computer-aided diagnosis system developed by Fujitsu Ltd, Japan. The mean nodule size was 0.69±0.28 (SD)[cm](range, 0.3-1.7cm). The CAD system identified 42 to 48 nodules out of the 64 nodules, in the slice thickness of 8mm for the seven reconstruction kernels, yielding a true-positive rate (TPR) of 65% to 75%. In the slice thickness of 5mm our CAD system indicates a TPR from 70% to 80%. In the slice thickness 10mm, TPR were resulted from 50% to 64%. Some kernel indicated relatively high TPR with high FP, other kernel showed high sensitivity with relatively low FP. CT image data sets with multi-reconstruction conditions is useful in assessing the robust characteristics of a CAD system detecting pulmonary nodule by multi-slice low dose CT screening.