Research On Techniques Of 3D Reconstruction In Computer-Aided Tissue Engineering

3D reconstruction from medical images is a hot topic in the field of Computer-Aided Tissue Engineering. It has been widely used in diagnostic, surgery planning and simulating, plastic and artificial limb surgery, radiotherapy planning, and teaching in anatomy. Study on 3D reconstruction from medical images has important significance on science and worthiness in practical application.The medical image processing method is studied. The main steps include defining the threshold values after analyzing the gray-level histograms of slice images, binarizing the images, processing the images using properly mathematical morphology operation according to the feature of tissues or regions to be extracted, and filling the regions using seed fill algorithm.This dissertation uses the classical algorithm of iso-surface rendering named Marching Cubes (MC) to reconstruct the surface model of tissues or organs. Aim at overcoming the shortcomings of the classic MC algorithm, an improved MC algorithm is presented. It can integrate image segmentation and MC algorithm. The improved MC algorithm can be described as follows: First, The segmentation result (binary image data) is used as the input of MC algorithm to generate iso-surface. Second, an intersection index table is designed to solve the ambiguous problem in MC. Third, a method of rapidly searching the boundary cube is developed to avoid detecting certain empty cubes. Fourth, using the middle point method, the vertex of triangle can be calculated easily for reducing the computation.A medical images reconstruction system based on the improved MC algorithm is developed, which includes medical image pre-processing, segmenting and reconstructing modules. Examples of 3D reconstruction can keep the topology coherence, and represent the tissues or organs in realistically as well.