Focusing on the traditional template matching Method for nodule detection

a 3D adaptive template matching algorithm for lung nodules detection has been proposed in this paper. First of all

3D lung parenchyma is segmented from the scanned CT images

and then

canny operator is employed for extracting 3D ROI which will be used as the candidate pulmonary nodule. Secondly

collect the main direction of the 3D ROI and locate the center slice

and expand the 3D adaptive template from the center slice trace along the main direction. At last

calculate the correlation coefficient between the 3D adaptive template and pulmonary nodule candidate image by applying Normal Cross Correlation (NCC) algorithm

and set a threshold value of NCC for marking the higher correlation coefficient regions as detection Results. Based on 66 clinical cases' experiment

the sensitivity reaches 95.29% and false positive is 12.90%. The experiment Results show that our Method has high sensitivity and accuracy and can help radiologists to detect nodules effectively.