[Research on Segmentation Method of Lung with Juxta-pleural Tumor Based on the Improved Active Shape Model]

Lung segmentation is the premise of the computer aided diagnosis of lung cancer.The traditional segmentation method based on local low-level features can not get the correct result when a tumor is connected with pleura due to their similar computed tomography(CT)values.Moreover,because the big size of tumor leads to the loss of a large part of lung area,the traditional segmentation methods of lung with juxta-pleural nodule whose diameter is less than 3cm are not suitable.Acitve shape model(ASM)combined with prior shape and low level features might be appropriate.But the search steps in conventional ASM is an optimization method based on the least square,which is sensitive to outlier marker points,and it makes profile update to the transition area of normal lung tissue and tumor rather than a true lung contour.To solve the problem,we proposed an improved ASM algorithm.Firstly,we identified these outlier marker points by distance,and then gave the different searching functions to the abnormal and normal marker points.And the search processing should be limited in volume of interesting(VOI).We selected 30 lung images with juxta-pleural tumors,and got the overlap rate with the gold standard as 93.6%.The experimental results showed that the improved ASM could get good segmentation results for the lungs with juxta-pleural tumors,and the running time of the algorithm could be tolerated in clinical.