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Liver Segmentation and 3D Modeling Based on Multilayer Spiral CT Image

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10637)

Abstract

The 3D reconstruction can facilitate the diagnosis of liver disease by making the target easier to identify and revealing the volume and shape much better than 2D imaging. In this paper, in order to realize 3D reconstruction of liver parenchyma, a series of pretreatments are carried out, including windowing conversion, filtering and liver parenchyma extraction. Furthermore, three kinds of modeling methods were researched to reconstruct the liver parenchyma containing surface rending, volume rendering and point rendering. The MC (marching cubes) algorithm based on 3D region growth is proposed to overcome the existence of a large number of voids and long modeling time for the contours of traditional MC algorithms. Simulation results of the three modeling methods show different advantages and disadvantages. The surface rendering can intuitively image on the liver surface modeling, but it cannot reflect the inside information of the liver. The volume rendering can reflect the internal information of the liver, but it requires a higher computer performance. The point rendering modeling speed is quickly compared to the surface rendering and the volume rendering, whereas the modeling effect is rough. Therefore, we can draw a conclusion that different modeling methods should be selected for different requirements.

Keywords

Liver CT image Liver segmentation 3D modeling MC algorithm 

Notes

Acknowledgments

This research is supported by Jilin Province Nature Science Foundation (No. 20130102082JC), Jilin Province Development and Innovation Committee’s High and New Technology Projects (No. JF2012C006-6).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.College of SoftwareJilin UniversityChangchunChina
  2. 2.College of Computer Science and TechnologyJilin UniversityChangchunChina

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