Article

GSTF Journal on Computing (JoC)

, 3:25

First online:

Open Access This content is freely available online to anyone, anywhere at any time.

An Accelerating 3D Image Reconstruction System Based on the Level-of-Detail Algorithm

  • Tsung-Yu LeeAffiliated withDepartment of electronic engineering, National Taipei University of Technology
  • , Ren-Guey LeeAffiliated withDepartment of electronic engineering, National Taipei University of TechnologyDepartment of Electrical Engineering, National Chen Kung University (NCKU)
  • , Sheng-Chung TienAffiliated withDepartment of electronic engineering, National Taipei University of TechnologyInstitute of computer and communication engineering, National Taipei University of Technology
  • , Robert LinAffiliated withDepartment of Lunghwa, University of Science and TechnologyElectronic engineering, Chung Yuan Christian University
  • , Wei-Hua SuAffiliated withInstitute of computer and communication engineering, National Taipei University of TechnologyDepartment of computer science, Tamkang University

Abstract

This paper proposes a research of An Accelerating 3D Image Reconstruction System Based on the Level-of-Detail Algorithm and combines 3D graphic application interfaces, such as DirectX3D and OpenCV to reconstruct the 3D imaging system for Magnetic Resonance Imaging (MRI), and adds Level of Detail (LOD) algorithm to the system. The system uses the volume rendering method to perform 3D reconstruction for brain imaging. The process, which is based on the level of detail algorithm that converts and formulates functions from differing levels of detail and scope, significantly reduces the complexity of required processing and computation, under the premises of maintaining drawing quality. To validate the system’s efficiency enhancement on brain imaging reconstruction, this study operates the system on various computer platforms, and uses multiple sets of data to perform rendering and 3D object imaging reconstruction, the results of which are then verified and compared.

Keywords:

Level of Detail GPU 3D Reconstruction