3D EM/MPM Medical image segmentation using an FPGA embedded design implementation

Chao Liu, Purdue University

Abstract

This thesis presents a Field Programmable Gate Array (FPGA) based embedded system which is used to achieve high speed segmentation of 3D images. Segmentation is performed using Expectation-Maximization with Maximization of Posterior Marginals (EM/MPM) Bayesian algorithm. In this system, the embedded processor controls a custom circuit which performs the MPM and portions of the EM algorithm. The embedded processor completes the EM algorithm and also controls image data transmission between host computer and on-board memory. The whole system has been implemented on Xilinx Virtex 6 FPGA and achieved over 100 times improvement compared to standard desktop computing hardware.

Degree

M.S.E.C.E.

Advisors

Christopher, Purdue University.

Subject Area

Computer Engineering|Electrical engineering

COinS