Document Type

Thesis

Date of Degree

Summer 2013

Degree Name

MS (Master of Science)

Degree In

Biomedical Engineering

First Advisor

Joseph M. Reinhardt

Abstract

Image registration is a useful technique to measure the change between two or more images. Lung CT image registration is widely used an non-invasive method to measure the lung function changes. Non-invasive lung function measurement accuracy highly depends on lung CT image registration accuracy. Improving the registration accuracy is an important issue.

In this thesis, we propose incorporating information of the anatomical structure of the lung (fissures) as an additional cost function of the lung CT image registration. The intensity-based similarity measurement method (sum of the squared tissue volume differences) is also used to complement lung tissue information matching. However, since fissures are hard to segment, a sheet-likeness filter is applied to detect fissure-like structures. Sheet-likeness is used as an additional cost function of the intensity-based registration. The registration accuracy is verified by the visual assessment and landmark error measurement. The landmark error measurement can show an improvement of the proposed algorithm.

Keywords

CT, Image, Lung, Registration

Pages

ix, 68 pages

Bibliography

Includes bibliographical references (pages 65-68).

Copyright

Copyright 2013 Yang Wook Kim

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