The computered-aided diagnosis of solitary pulmonary nodule based on HDCT

ZHANG Ze-wen; ZHANG Cai-qing; WANG Guang-li; ZHANG Cheng-qi

Abstract：Objective In this paper ,we try to design a computered‐aided diagnostic system (CADS) of solitary pulmona‐ry nodule (SPN) based on high definition CT (HDCT ) images in order to improve the detection rate of malignant SPN and to make the diagnosis more objective and scientific .Methods 120 cases of SPN confirmed by pathology were collected ,in‐cluding malignant tumors ,benign tumors ,tuberculosis and inflammatory pseudotumors .60 cases were randomly selected as the experimental set ,60 cases as the validation set .We acquired five texture feature parameters from HDCT images of the experimental set by images preprocessed ,regions of interest (ROI) segmented by watershed algorithm based on the mark and texture feature parameters of ROI extracted .A statistical method was used to process the five texture feature pa‐rameters .The statistical results were applied in the CAD to differentiate malignant SPN from benign SPN and give messa‐ges .The HDCT images of the validation set were inputed in the CAD and we could evaluate the reliability of the CAD by comparing the forecasts of the CAD ,chief physicians and residencies .Results The results of t test of the five texture fea‐ture parameters were 0 .000 ,0 .002 ,0 .914 ,0 .295 ,0 .002 respectively .The benign ranges of the parameters were respec‐tively (903 ,2003) ,(2 .76 ,3 .48) ,(0 .01 ,1 .54) and the malignant ranges were (502 ,898) ,(3 .49 ,3 .71) ,(1.79 , 29.86) respectively .The sensitivity of the CAD was 83 .3% ,the false positive rate was 13 .3% and the correct rate was 85% .Conclusion The watershed algorithm based on the mark could better segment the nodules adjoined with the chest wall or mediastinum and the ground glass lesions .There was statistical significance in contrast ,correlation and energy .The CAD had higher sensitivity and accuracy and the lowest false positive .The CAD possessed certain clinical value in dif‐ferentiating malignant SPN from benign SPN and could assist clinicians .