Research Of Rapid Prototyping In Tissue Engineering Bone Repair

Tissue engineering is an edge subject, which synthesizes fundamental and technology of life sciences and engineering, with synthetic or natural biological material as a carrier, Integrates separating seed cell, constructs a pre-implant lives in vitro, then implants in vivo to repair tissue and organ replacement or reconstruction of the structure to maintain or improve the function of organs. Tissue engineering research includes tissue engineering bracket material, cell biology, bio-medical evaluation of performance and safety aspects.In this thesis, image processing technology of tissue engineering and rapid prototyping, involved analysis of image detection, image segmentation and image surface reconstruction etc., completed analysis of the morphology of the cells, with Objectivity and reproducible, accurate quantitative characteristics. Also, for the repair and regeneration of tissues and organs, three-dimensional CT image reconstruction sequences combined with rapid prototyping to producet three-dimensional organizational model.The research and innovation points are following:1. Segmentation of Tissue cellsThe cultured cells are separated by the three different methods for different applications.(1) Propose an algorithm of Clipping technology, Introduce a different approach with the traditional image segmentation of image processing methods, the threshold technology used in clear and full cell granules with good results. This method of binary image achieves regional segmentation image by various logic operations. Experiment shows that the technology to remove background region attaches around to cells and isolate from the various inter-cell adhesion is a very effective.(2) Propose a segmentation approach based on integration for fuzzy boundary and no clear particles of cells. Canny edge detection integrated with Multiwavelets to improve the accuracy of the edge detection. First apply the Mallat wavelet transform modulus maxima scale independent edge detection method to get simple edges, then data fusion method combine Marr and Canny operator and the use of different weights to the final image of cell segmentation. The method is to the not clear edge of the cell segmentation with good results.(3) Propose snake active contour based on fixed points. On the basis of semiautomatic obtain initial contour, determine Image points can be used to accelerate the contour convergence rate, the speed and accuracy achieved good results. First apply scale-independence edge detecting based on Mallat wavlet modular maxium to get simple boundary, then adopt morphology and Spline fitting method to get single pixel boundary as initial contour of snake algorithm, finally, perform iterating with external restrict power which link to image fixed point to make contour convergence to the final borders.2. Sequence image segmentationDiscusse the CT image sequence segmentation method, in particular bone CT image slices. Propose an image segmentation algorithm based active contour with images of neighbors and similarity. On the basis of using c-v method based on Mumfold-Shah model to obtain first slice exact boundary, parameters Snake model deformation used in the biopsy sequence automatic segmentation and accelerating the speed of convergence contour.Against the "leak" of segmentation, the use of image slices activity contour similar to accelerate the convergence, define a contour Similarity to decide whether or not to Initialize re-contour. The method can achieve a good semi-automatic segmentation of the image sequence, make full use of the advantage of geometric and parameters active contour deformation to raise the contour of the convergence rate. Utilize geometric strong expand features to ensure initial contour accuracy, use deformation parameters to speed up the convergence, thereby reduce the maximum extent artificial participation.3. 3D Visualization based on the segmentationPropose a NMC* (New Marching Cubes) algorithms based on two-dimensional segmentation to achieve data sets Volume Visualization. The standard MC algorithm can only limit to thresholding segmentation, so while introduce of a variety of segmentation, pay attention to the algorithm to reduce the running time and data storage space. Make use of the intersection with the isosurface cube information, which preserved at data detection in sequence segmentation, for surface tracking, reduce duplication of testing data, effectively shortening the running time of the algorithm. Meanwhile, simplify and share the public edges between triangulated surfaces, such as redundancy, save the data storage space, improve the efficiency of the algorithm. The approach takes a very good job of combining segmentation and 3D reconstruction, researches and improves deeply redundancy and testing time.4. Rapid prototypingResearch Rapid Prototyping and organs reconstruction, especially for bone tissue engineering. Discusse STL files optimizing, how to use three-dimensional reconstruction to produce the defect organs structure of tissue engineered, provide entity model for the repair of tissues and organs. Finally display of a skull repair example, based on Repaired parts of STL file, Constructed a skull defect entities by rapid equipment.Image processing technology, which this article related to, play an important role in tissue engineering, cover almost all stages of tissue engineering. Discuss computer-aided tissue engineering research and the prospects for the application, with some guidance and forward-looking.