Evaluation of registration of ictal SPECT/MRI data using statistical similarity methods
Lecture Notes in Computer Science, ISSN: 0302-9743, Vol: 3216, Issue: PART 1, Page: 687-695
2004
- 5Citations
- 4Captures
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Conference Paper Description
In this study, we evaluated SPECT/MRI registration of ictal data, using similarity based registration methods. An absolute gold standard for registration evaluation was obtained by considering realistic normal and ictal SPECT simulations deduced from a high resolution T1-weighted MRI data set. Those simulations were also used to study the impact of photon attenuation and Compton scatter corrections on registration accuracy. Evaluation of registration was also performed using inconsistency measurements for six patients with temporo-mesial epilepsy. For these data, as no Gold Standard was available, registration accuracy was assessed using inconsistency measurements involving a registration loop between inter-ictal SPECT, ictal SPECT and MRI data. Five registration methods based on statistical similarity measurements were compared, namely: mutual information (MI), normalized mutual information (NMI), L1 and L2 norm-based correlation ratios (CR) and correlation coefficient (CC). It was found that the simulation context had more influence on registration accuracy than the choice of the similarity criterion. Ictal SPECT as well as correction for uniform attenuation clearly decreased SPECT/MRI registration accuracy. © Springer-Verlag Berlin Heidelberg 2004.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=20344392701&origin=inward; http://dx.doi.org/10.1007/978-3-540-30135-6_84; http://link.springer.com/10.1007/978-3-540-30135-6_84; http://link.springer.com/content/pdf/10.1007/978-3-540-30135-6_84.pdf; http://www.springerlink.com/index/10.1007/978-3-540-30135-6_84; http://www.springerlink.com/index/pdf/10.1007/978-3-540-30135-6_84; https://dx.doi.org/10.1007/978-3-540-30135-6_84; https://link.springer.com/chapter/10.1007/978-3-540-30135-6_84
Springer Science and Business Media LLC
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