三维图像重构2

2009 International Conference on Measuring Technology and Mechatronics Automation

THREE-DIMENSIONAL MEDICAL CT IMAGE RECONSTRUCTION

Wang Hongjian

Chongqing Engeering Technology Research Center for Information Management in Development, Chongqing

Technology and Business University,Chongqing,400067,China.

e-mail: whj_cqu@http://www.mianfeiwendang.com

Abstract—In this paper, it is provided to reconstruct three dimensional(3D) models of human body by using CT slices and digital images and precisely finding locations of pathological formations such as tumours.3D image CT reconstruction is an attractive field generally in digital image processing techniques, especially in biomedical imaging. It has been strongly developed and practically implemented in almost every modern tomographical modalities but there are many problems which still remain unresolved or can be improved. A project in such area has been alternatively developed in order to master mentioned technology and to develop domestic products partially substituted for very expensive imported facilities and softwares. This paper introduces the implementing fundamental problems in 3D medical image reconstruction for medical imaging such as Marching Cubes MC algorithms, usual rendering technique, etc. and designing a software for reconstructing 3D image from a set of CT images, which was built on VTK (Visualization Toolkit) and Visual C++. The result show that the reconstruction program can help to reconstruct series of 2D segmented binary images and display the 3D image of the target object.

Keywords-CT Image; Marching Cubes; 3D-reconstructio; VTK.

with MC algorithms on PC, which are very necessary tools for medical image processing.

II. FUNDAMENTAL THEORY

A common approach to stereo reconstruction is the optimization of a cost function, computed by solving the correspondence problem between the set of input images. The matching problem involves establishing correspondences between the views available and is usually solved by setting up a matching functional for which one then tries to find the extrema. By identifying the matching pixels in the two images as being the projection of the same scene point, the 3D point can then be reconstructed by triangulation, intersecting the corresponding optical rays. Our proposed method differs from this approach by projecting all the images into a common space prior to analysing the correspondence between the images. The matching problem is then solved not as a correspondence problem between images, but as a matching functional, computed for each voxel in the volume. This functional is optimised through segmentation to recover the 3D structure of the scene.

A. Medical images and 3D reconstruction

All recent medical 3D image reconstruction techniques create 3D images from sets of 2D slices, which can be recorded by various equipments such as CT, MRI, ultrasound etc. Each type of scanner has his own characteristics due to physical principles of image recording, e.g. images of CT scanner are often parallel slices with high contrast, images of ultrasound scanner are either parallel or divergent slices with low contrast etc. Thus there are different 3D reconstruction techniques for each type of data (fig. 1).

Generally, the general principle of 3D reconstruction is composed of following two steps:

Step 1: 2D data slices need to be read and arranged exactly with the real spatial positions, the result is a data volume, which is saved in memory of computer.

Step 2: use rendering techniques to visualize data volume as 3D image. Usual rendering techniques for medical image are multiplanar rendering (MPR), surface rendering (SR) and volume rendering (VR). B. Rendering techniques

1) MPR technique. MPR does not require too many calculations. So it could run on some low configuration computers. This technique can be used to reslice structure, i.e. with axial slices we can use MPR technique to reslice

I. INTRODUCTION

Medical Imaging techniques are used for diagnosing and treatment of many diseases as well as surgical operations. CT and MR imaging techniques are the mostly used ones[1-2]. Reconstruction of 3D volume and surface models of the tissues, by using 2D image slices, provides many advantages to medical doctors. For a long time, 3D models have being used in medical applications in many countries, which are used just at some high quality hospitals and medical centers. These equipments have been indispensably for doctors’ diagnosis assisted by information technology, which need strong computers with dedicated software. At present, such high-tech equipments are unable to be manufactured with domestic technology, but feasible developing supporting accessories and software can enhance their utilization effectivity and reduce the dependence on foreign maintenance system with high cost. On the other hand, medical information system does not shape clearly; medical units in national health care system have not united yet in any standard process to operate image diagnostic equipments or to manage patient data. Therefore, a project making facilities for medical information system in general and for medical imaging in particular has been alternatively developed in order to master mentioned technology and to develop domestic products partially taken place of very expensive imported facilities and soft wares[3-4]. This paper introduces our building 3D image reconstruction software

Word文档免费下载Word文档免费下载:三维图像重构2 (共4页,当前第1页)

三维图像重构2相关文档

最新文档

返回顶部