The Research On Lung Segmentation Algorithm Based On Thoracic Ct Image

The application of many kinds of medical image technology improves the speed and quantity of clinical diagnosis and medical research it has been given more and more attention by researchers. The image of computerized tomographic scanning technology (CT) become one of the most important technology because the character of high resolution and clear relationship between organizations. It is also high light that there is few heart to the patient in the process of image acquisition.Clinical image segmentation is the basis of the following process it takes a important place in clinical image process technology. In the clinical diagnosis process the result of lung segmentation make the CAD design the detection of lung nodules the evaluation of lung function and the rebuild of 3D lung image possible. It is every important to get a exact lung image to provide the clinical diagnosis and research a reliable basis.The aim of this research is to segment the lung field from the background. To divide the connected right and left lung which are coursed by pathology. There are many nodules lie near the lung boundary. This kind of nodules will be set to background pixel in the threshold process and the useful information will loose. It is un-expectant. This paper adds a lung boundary repair process to solve the problem to get a more accurate lung boundary for the following steps.Aiming at the problems above the following work has been scheduled and a segmentation strategy based on compositive arithmetic has been approved.(1) The threshold method is base on the gray value information it is easier and more efficient to segment the lung field from the around issue because the high contrast between the two parts. But the method is easy to be impacted by noise so a filter has been used before threshold method to improve the quality of the initial image.(2) Apply the optimal threshold to get the segmentation after the research on several thresholds. (3) To segment the air-way which rely in the lung field through a region growing method in which the seed can be selected automatically.(4) To introduce the connective region labeling method into the estimate of the status of connection of left and right lung region. The results of estimate provide a range of the following process.(5) Design an iteratively morphological multi-operation to separate the right and left lung to get a more accurate result of segmentation.(6) Provide a extreme point detection method to repair the gap of lung boundary.The results have been tested by processing the clinical image sets by emulator. We compare the result of the method in this paper to the result of manual method by image analyst. The result indicates the method in this paper can be used to segment the lung region from background and get the right and left lung separately. The gap on the lung boundary can be repaired by this method to get a result which is similar with the result of manual method can be used in the following research and process.