@article{1777,
  author = {Shuqin Liu, Jinye Peng},
  title = {Optimization of Reconstruction of 2D Medical Images Based on Computer 3D Reconstruction Technology},
  journal = {Journal of Digital Information Management},
  year = {2015},
  volume = {13},
  number = {3},
  doi = {},
  url = {http://dline.info/fpaper/jdim/v13i3/v13i3_2.pdf},
  abstract = {Computer 3D reconstruction consisting of
reconstruction of 3D point clouds and images plays an important role in computer graphics, computer image processing and computer vision research. Image based 3D reconstruction includes reconstruction of single image and
multiple images. Compared to obtain 3D mode by modeling software or scan tester traditionally, image-based 3D reconstruction is featured by strong sense of reality, low cost,
vivid image and broader market demand. Moreover, image based 3D reconstruction is practically an inverse problem of
computer graphics. In medical field, 3D reconstruction of medical images is to create 3D information based on a 2D
image and then form a vivid 3D image. It transforms 2D fault data sequence obtained from Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) into 3D data, which
is valuable in demonstrating tissues and organs of human body. 3D reconstruction technology concerning medicine is widely applied in medical diagnosis, surgical planning,
analog simulation and plastic surgery. Therefore, computer 3D reconstruction technology is of important academic and
practical value to reconstruction of 2D medical images. Research of 3D reconstruction of medical images focuses on preprocessing of medical images, such as filtering and
interpolation, and segmentation and extraction of tissue and organ. This study analyzes design concept and method of cross-platform medical image 3D reconstruction system, development status, market demand and prospect of computer 3D reconstruction technology, medical volume data visualization technology, acquisition of medical images and several kinds of medical image preprocessing technologies. In the study, region growing algorithm is used to segment
liver tissues. Volume rendering technology provides 3D special description for 2D medical fault images, to make its internal 3D structure become clearer. Principles and application scope of marching cubes based surface
rendering algorithm is emphatically introduced. Based on traditional edge extraction theory, a new edge measurement and calculation method is designed, which makes edge smoother.},
}