An Efficient 3D Shape Reconstruction Technique for CT Images Using Volume Definition Tools

摘要

The definition of structures and the extraction of organ's shape are essential parts of medical imaging applications. These might be applications like diagnostic imaging, image guided surgery or radiation therapy. The aim of the volume definition process is to delineate a specific shape of an organ on a digital image as accurate as possible especially for 3D rendering, radiation therapy, and surgery planning. This can be done, either by manual user interaction or applying imaging processing techniques for the automatic detection of specific structures in the image. In this work we present a set of tools that are implemented on several computer based medical application. Central focus of this work, are techniques used to improve time and interaction needed for a user when defining one or more structures. These techniques involve interpolation methods for the manual volume definition and methods for the semi-automatic organ shape extraction. Finally different segmentation techniques would be proposed for the particular organs of interests (lungs, skin and spine canal) and a 3D shape reconstruction of these regions would be illustrate the efficiency of the segmentation techniques. Finally, the proposed technique would be compared with the manual segmentation obtained from the doctor experts using quantitative (shape matching measures) and qualitative (visual comparison) measures.