Analysis and Implementation of the Maximum Likelihood Expectation Maximization Algorithm for FIND

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors

Angus Boyd Jameson, University of New HampshireFollow

Abstract

This thesis presents an organized explanation and breakdown of the Maximum Likelihood Expectation Maximization image reconstruction algorithm. This background research was used to develop a means of implementing the algorithm into the imaging code for UNH's Field Deployable Imaging Neutron Detector to improve its ability to resolve complex neutron sources. This thesis provides an overview for this implementation scheme, and include the results of a couple of reconstruction tests for the algorithm. A discussion is given on the current state of the algorithm and its integration with the neutron detector system, and suggestions are given for how the work and results of this project could be continued and expanded upon.

Department

Department of Physics

Date of Publication or Presentation

Fall 12-22-2020

Project Type

Undergraduate Research Project

College or School

CEPS

First Advisor

Mark McConnell

Second Advisor

Karl Slifer

Recommended Citation

Jameson, Angus Boyd, "Analysis and Implementation of the Maximum Likelihood Expectation Maximization Algorithm for FIND" (2020). Student Research Projects. 24.
https://scholars.unh.edu/student_research/24