PET and CT image registration of the rat brain and skull using the air algorithm

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dc.contributor.author Vaquero López, Juan José
dc.contributor.author Desco Menéndez, Manuel
dc.contributor.author Pascau González Garzón, Javier
dc.contributor.author Santos, Andrés
dc.contributor.author Lee, I. J.
dc.contributor.author Seidel, J.
dc.contributor.author Green, M. V.
dc.date.accessioned 2011-09-26T10:51:30Z
dc.date.available 2011-09-26T10:51:30Z
dc.date.issued 2000-10
dc.identifier.bibliographicCitation 2000 IEEE Nuclear Science Symposium Conference Record, Oct. 2000, vol. 3, p. 16/22 - 16/23
dc.identifier.isbn 0-7803-6503-8
dc.identifier.issn 1082-3654
dc.identifier.uri http://hdl.handle.net/10016/12184
dc.description Proceeding of: 2000 IEEE Nuclear Science Symposium Conference Record, Lyon, France, October 15 - 20, 2000
dc.description.abstract Spatially registered PET and CT images of the same small animal offer at .least three potential advantages .over PET alone. First, the CT images should' alIow accurate, nearly noise-free correction of the PET image data for attenuation. Second, the CT images snould permit more certain identification of structures evident in the PET images and third, the CT images provide a priori anatomical information that may be of use with resolution-improving image reconstruction algorithms that model the PET imaging process. Thus far, howeyer, image registration algorithms effective in human studies have not been characterized in the small animal setting. Accordingly,'we evaluated the ability of the AIR algorithm to accurately register PET F-18 fluoride and F-18 FDG images of the rat skull and brain, respectively, to CT images acquired following each PET imaging session. The AIR algorithm was able to register the bone-to-bone images with a maximum error of less than 1.0 mm. The registration error for the brain-to-brain study, however, was greater (2.4 mm) and required additional steps and. user.intervention to segment the brail1 from the head in both data sets before registration. These preliminary results suggest that the AIR algorithm can accurately combine PET and CT images in small animals when the data sets are nearly homologous, but may require additional segmentation steps with increased mis-registration errors when registering disparate, low contrast soft tissue structures.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher IEEE
dc.rights © IEEE
dc.title PET and CT image registration of the rat brain and skull using the air algorithm
dc.type article
dc.type conferenceObject
dc.relation.publisherversion http://dx.doi.org/10.1109/NSSMIC.2000.949168
dc.subject.eciencia Biología y Biomedicina
dc.identifier.doi 10.1109/NSSMIC.2000.949168
dc.rights.accessRights openAccess
dc.type.version acceptedVersion
dc.relation.eventdate October 15 - 20, 2000
dc.relation.eventplace Lyon, France
dc.relation.eventtitle 2000 IEEE Nuclear Science Symposium Conference Record
dc.relation.eventtype Proceeding
dc.identifier.publicationfirstpage 16/22
dc.identifier.publicationlastpage 16/23
dc.identifier.publicationtitle 2000 IEEE Nuclear Science Symposium Conference Record, October 2000
dc.identifier.publicationvolume 3
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