HEAL DSpace

A comparative study of surface- and volume-based techniques for the automatic registration between CT and SPECT brain images

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dc.contributor.author Kagadis, GC en
dc.contributor.author Delibasis, KK en
dc.contributor.author Matsopoulos, GK en
dc.contributor.author Mouravliansky, NA en
dc.contributor.author Asvestas, PA en
dc.contributor.author Nikiforidis, GC en
dc.date.accessioned 2014-03-01T01:17:20Z
dc.date.available 2014-03-01T01:17:20Z
dc.date.issued 2002 en
dc.identifier.issn 0094-2405 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/14470
dc.subject Average surface distance en
dc.subject CT en
dc.subject Image registration en
dc.subject Mutual information en
dc.subject SPECT en
dc.subject.classification Radiology, Nuclear Medicine & Medical Imaging en
dc.subject.other accuracy en
dc.subject.other algorithm en
dc.subject.other article en
dc.subject.other comparative study en
dc.subject.other computer assisted tomography en
dc.subject.other human en
dc.subject.other nuclear magnetic resonance imaging en
dc.subject.other priority journal en
dc.subject.other reliability en
dc.subject.other single photon emission computer tomography en
dc.subject.other three dimensional imaging en
dc.subject.other Algorithms en
dc.subject.other Brain en
dc.subject.other Brain Neoplasms en
dc.subject.other Humans en
dc.subject.other Models, Statistical en
dc.subject.other Tomography, Emission-Computed, Single-Photon en
dc.subject.other Tomography, X-Ray Computed en
dc.title A comparative study of surface- and volume-based techniques for the automatic registration between CT and SPECT brain images en
heal.type journalArticle en
heal.identifier.primary 10.1118/1.1445412 en
heal.identifier.secondary http://dx.doi.org/10.1118/1.1445412 en
heal.language English en
heal.publicationDate 2002 en
heal.abstract Image registration of multimodality images is an essential task in numerous applications in three-dimensional medical image processing. Medical diagnosis can benefit from the complementary information in different modality images. Surface-based registration techniques, while still widely used, were succeeded by volume-based registration algorithms that appear to be theoretically advantageous in terms of reliability and accuracy. Several applications of such algorithms for the registration of CT-MRI, CT-PET, MRI-PET, and SPECT-MRI images have emerged in the literature, using local optimization techniques for the matching of images. Our purpose in this work is the development of automatic techniques for the registration of real CT and SPECT images, based on either surface- or volume-based algorithms. Optimization is achieved using genetic algorithms that are known for their robustness. The two techniques are compared against a well-established method, the Iterative Closest Point - ICP. The correlation coefficient was employed as an independent measure of spatial match, to produce unbiased results. The repeated measures ANOVA indicates the significant impact of the choice of registration method on the magnitude of the correlation (F = 4.968, p = 0.0396). The volume-based method achieves an average correlation coefficient value of 0.454 with a standard deviation of 0.0395, as opposed to an average of 0.380 with a standard deviation of 0.0603 achieved by the surface-based method and an average of 0.396 with a standard deviation equal to 0.0353 achieved by ICP. The volume-based technique performs significantly better compared to both ICP (p < 0.05, Neuman-Keuls test) and the surface-based technique (p < 0.05, Neuman-Keuls test). Surface-based registration and ICP do not differ significantly in performance. © 2002 American Association of Physicists in Medicine. en
heal.publisher AMER ASSOC PHYSICISTS MEDICINE AMER INST PHYSICS en
heal.journalName Medical Physics en
dc.identifier.doi 10.1118/1.1445412 en
dc.identifier.isi ISI:000173856900009 en
dc.identifier.volume 29 en
dc.identifier.issue 2 en
dc.identifier.spage 201 en
dc.identifier.epage 213 en


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