JSE_V5_N4_RP2 Mohammed Goryawala Magno R. Guillen Armando Barreto Ruchir Bhatt Seza Gulec Tushar Barot Rekha Suthar Anthony McGoron Malek Adjouadi Journal on Software Engineering 2230 – 7168 5 4 12 27 MatLab, HPC, Parallel Computing, Distributed Computing, Performance Metrics, 3-D Reconstruction 3D reconstruction is a task that exerts a heavy computational load. This study describes the performance results obtained on testing the MatLab parallel processing toolbox to execute a three-dimensional (3-D) liver reconstruction. The FFT algorithm was tested using the parallel processing tool box, by changing system platform, number of workers,image size and number of images. A second set was executed keeping the hardware fixed and changing the operating system to obtain unbiased results. The third experiment set was to assess the effect of parallelization applied to a newly developed 3-D liver reconstruction algorithm. Results showed a reduction of processing time from 4.5 hours to almost 1 hour, yielding a 78% (3.5 hours) savings in computational time due to the multicore deployment. The results show that the leveraging of multicore platforms can speed up considerably the processing of medical images through the use of parallel computing tools in MatLab. April - June 2011 Copyright © 2011 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=1444