Medical image registration: A review of existing methods and preliminary numerical results
Registration of medical images has become an important area of research. In particular, registration of computed tomography (CT) lung images is of great interest to radiation oncologists planning radiation treatment for patients with lung cancer. A review of existing image registration methods, as w...
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ndltd-RICE-oai-scholarship.rice.edu-1911-178672013-10-23T04:11:46ZMedical image registration: A review of existing methods and preliminary numerical resultsCastillo, EdwardMathematicsRegistration of medical images has become an important area of research. In particular, registration of computed tomography (CT) lung images is of great interest to radiation oncologists planning radiation treatment for patients with lung cancer. A review of existing image registration methods, as well as preliminary numerical results, indicate that methods based on a constant pixel intensity assumption, such as traditional optical flow methods, cannot be expected to produce accurate registration of lung CT images. Nonlinear methods allowing variations in pixel intensities, though more costly than linear methods, promise to be more accurate for this application.Zhang, Yin2009-06-04T06:57:49Z2009-06-04T06:57:49Z2005ThesisText48 p.application/pdfhttp://hdl.handle.net/1911/17867eng |
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Mathematics Castillo, Edward Medical image registration: A review of existing methods and preliminary numerical results |
description |
Registration of medical images has become an important area of research. In particular, registration of computed tomography (CT) lung images is of great interest to radiation oncologists planning radiation treatment for patients with lung cancer.
A review of existing image registration methods, as well as preliminary numerical results, indicate that methods based on a constant pixel intensity assumption, such as traditional optical flow methods, cannot be expected to produce accurate registration of lung CT images. Nonlinear methods allowing variations in pixel intensities, though more costly than linear methods, promise to be more accurate for this application. |
author2 |
Zhang, Yin |
author_facet |
Zhang, Yin Castillo, Edward |
author |
Castillo, Edward |
author_sort |
Castillo, Edward |
title |
Medical image registration: A review of existing methods and preliminary numerical results |
title_short |
Medical image registration: A review of existing methods and preliminary numerical results |
title_full |
Medical image registration: A review of existing methods and preliminary numerical results |
title_fullStr |
Medical image registration: A review of existing methods and preliminary numerical results |
title_full_unstemmed |
Medical image registration: A review of existing methods and preliminary numerical results |
title_sort |
medical image registration: a review of existing methods and preliminary numerical results |
publishDate |
2009 |
url |
http://hdl.handle.net/1911/17867 |
work_keys_str_mv |
AT castilloedward medicalimageregistrationareviewofexistingmethodsandpreliminarynumericalresults |
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