Int. J. Computational Vision and Robotics, Vol. 9, No. 3, 2019 293 Copyright © 2019 Inderscience Enterprises Ltd. 3D image reconstruction from different image formats using marching cubes technique Abdou Shalaby Information Systems Department, Faculty of Computers and Information, Mansoura University, Egypt Email: abdou_r2004@hotmail.com Mohammed Elmogy* Information Technology Department, Faculty of Computers and Information, Mansoura University, Egypt Email: melmogy@mans.edu.eg *Corresponding author Ahmed Abo Elfetouh Information Systems Department, Faculty of Computers and Information, Mansoura University, Egypt Email: elfetouh@ mans.edu.eg Abstract: Structure from motion (SFM) is the problem of reconstructing the 3D image from 2D images. The main problem of 3D reconstruction is the quality of the 3D image that depends on the number of 2D slices input to the system. A large number of 2D slices may lead to high processing time. This paper introduces a new model to reconstruct the 3D image from any 2D image by using marching cubes algorithm. We use the LabVIEW program to build the system and use the Biomedical Toolkit to read and registered any 2D images. Our main goal is to implement the 3D reconstruction system to produce a high- quality 3D image with a minimum number of 2D slices and to decrease the execution time as possible. We apply our system on two datasets; all the experimental results have proved the efficiency and effectiveness of this system in 3D image reconstruction from any 2D image type. As shown in results, changing iso_value, image type and a number of images, affects the quality of 3D image reconstruction, and the processing time. Keywords: 3D image reconstruction; marching cubes; LabVIEW; 2D image registration; computed tomography; CT; magnetic resonance; MR; single-photon emission computed tomography; SPECT. Reference to this paper should be made as follows: Shalaby, A., Elmogy, M. and Elfetouh, A.A. (2019) ‘3D image reconstruction from different image formats using marching cubes technique’, Int. J. Computational Vision and Robotics, Vol. 9, No. 3, pp.293–309.