Study For Pulmonary Nodule Segmentation Methods Based On Active Contour Model

Lung cancer is the leading casue of death in many countries of the world. The clinicalevidence verifies that early detection and diagnosis of lung cancer can significantly improvethe survival rate of patients. Pulmonary nodule is the representation form of early stage oflung cancer. A main factor in determining a nodules malignancy status is the change in thenodule size and shape information. Pricise nodule segmentation is a prerequisite for obtainingthe change in the nodule and shape information, so pricise nodule segmentation is criticalstage. With the development of medical imaging equipment, the computer-aided diagnosis(CAD) system has been rapid development. In the CAD system of pulmonary noduledetection, the researches are mainly aimed to solid pulmonary nodules, but without moreresearches on the research of ground glass opacity (GGO) pulmonary nodules andjuxta-vascular (JV) pulmonary nodules. Studies have shown that GGO pulmonary noduleshave higher risks of being malignant than solid pulmonary nodules. Additionally, JVpulmonary nodules account for the largest typology of lung nodules. So GGO pulmonarynodules and JV pulmonary nodules are research objects in this dissertation. Recently, theactive contour models have been extensively applied to lung image segmentation. There aretwo reasons:(1) the active contour models can be easily formulated;(2) the active contourmodels can provide smooth and closed contour as segmentation results.In this dissertation, to segment GGO pulmonary nodules and JV pulmonary nodules,some improved active contour models are proposed and those models are studied intensively.The main contents and innovation are as follows.Firstly, the fuzzy speed function-based active contour model for segmentation ofpulmonary nodules is proposed. At present, the segmentation algorithm of pulmonary nodulesusing the edge-based active contour model and the region-based active contour model maycause boundary leakage. In order to avoid this phenomenon, a new segmentation algorithm ofpulmonary nodules using active contour model based on fuzzy speed function is proposed.This active contour model can accurately segment GGO pulmonary nodules, which havefuzzy boundary, and JV pulmonary nodules, which have the similar intensity as vessel. First,the two-dimensional vectors, which use gray feature and local shape feature, are constructedand three fuzzy speed functions are calculated using those two-dimensional vectors. Second,the three fuzzy speed functions are incorporated into the active contour model. At theboundary of pulmonary nodules, the three fuzzy speed functions equal to zero and theevolution of the contour curve stops, so that the accurate segmentation of pulmonary nodules in completed.Secondly, the segmentation of GGO pulmonary nodules using active contour modelbased on posterior probability and wavelet energy is proposed. Due to the fuzzy boundary,low contrast and intensity inhomogeneity of GGO pulmonary nodules, it’s really hard toaccurately segment them with the local region-based active contour models. To accuratlysegment GGO pulmonary nodules, a novel active contour model based on posteriorprobability and wavelet energy is proposed. First, the wavelet energy is incorporated into theactive contour model. The wavelet energy can enhance the dissimilarity between pulmonarynodule with background, and the local region information is considered, so the proposedactive contour model can segment low contrast GGO pulmonary nodules and those withintensity inhomogeneity. Second, the speed function based on posterior probability isincorporated into the active contour model. At the boundary of GGO pulmonary nodules, thespeed function of evolution equals to zero, so the active contour model can segment GGOpulmonary nodules with fuzzy boundary. Third, the initial contour is set near the boundary ofthe GGO pulmonary nodules using posterior probability, so the evolution curve may obtain aglobal minimum.Thirdly, the segmentation of GGO pulmonary nodules using active contour model basedon based on local and global membership is proposed. In order to segment GGO pulmonarynodules, another novel active contour model based on local and global membership isproposed. First, an edge stopping function based on the global membership is formulated. Theedge stopping function equals to zero at the boundary of GGO pulmonary nodules, so theproposed active contour model can accurately segment GGO pulmonary nodules with fuzzyboundary. Second, the data compoment of active contour model is calculated by using localmembership. The local membership can enhance the dissimilarity between pulmonary nodulewith background, and the local region information is considered, so the proposed activecontour model can segment low contrast GGO pulmonary nodules and those with intensityinhomogeneity. Third, the initial contour is set near the boundary of the GGO pulmonarynodules using global membership, so the evolution curve may obtain a global minimum.Finally, the juxta-vascular pulmonary nodules segmentation using active contour modelbased on fuzzy speed function and Bahattachary distance is proposed. Because of similarintensity in adjacent regions and intensity inhomogeneity, JV pulmonary nodules are notaccurately segmented by using the local region-based active contour models and theshape-based active contour models. For JV pulmonary nodules segmentation, a novel activecontour model based on fuzzy speed function and Bahattachary distance is proposed. First, the edge stopping function base on the fuzzy speed is incorporated into the regularizationcomponent of active contour model. The edge stopping function equals to zero at the placebetween JV pulmonary nodules and vessel, so the proposed active contour model canaccurately segment JV pulmonary nodules. Second, the data component of tha active contourmodel is formulated according to the shape-intensity joint Bhattacharya distance. TheBhattacharya distance can enhance the dissimilarity between JV pulmonary nodules andvessels, and the local region information is considered, so the proposed active contour modelcan segment JV pulmonary nodules with intensity inhomogeneity.