Medical image registration: A review of existing methods and preliminary numerical results

dc.contributor.advisorZhang, Yinen_US
dc.creatorCastillo, Edwarden_US
dc.date.accessioned2009-06-04T06:57:49Zen_US
dc.date.available2009-06-04T06:57:49Zen_US
dc.date.issued2005en_US
dc.description.abstractRegistration 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.en_US
dc.format.extent48 p.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.callnoTHESIS MATH.SCI. 2006 CASTILLOen_US
dc.identifier.citationCastillo, Edward. "Medical image registration: A review of existing methods and preliminary numerical results." (2005) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/17867">https://hdl.handle.net/1911/17867</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/17867en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectMathematicsen_US
dc.titleMedical image registration: A review of existing methods and preliminary numerical resultsen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentMathematical Sciencesen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Artsen_US
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