3D Visualization and Reconstruction of Lung Cancer Images using Marching Cubes Algorithm

The lungs are organs of the body in the form of a pair of thoracic round pockets, located in the chest cavity. Lung doctors usually only see images of Computer Tomography (CT) with the naked eye to detect, and know lung cancer. This procedure is of course less effective, because it takes a long time to diagnose lung cancer as a whole with the need for many images from several sides. Therefore, in this study aims to solve these problems by developing a system of 3D visualization and reconstruction of lung cancer images.. By using the HSV method, erosion, dilation, and closing can be done preprocessing to get the desired image shape and can reduce noise from lung images and Findcontour it can be used in the segmentation process to get a cancerous area from the lung image. Then, the extraction of information used as the basis of data in the reconstruction process using an algorithm called Marching Cubes (MC). The algorithm used is a standard MC with 15 combinations of the cube. The system can visualize and reconstruct 3D of lung cancer in two different patients.