Abstract
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.
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Keywords
- Mutual Information
- Attenuation Correction
- Scatter Correction
- Registration Method
- Normalize Mutual Information
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Grova, C., Jannin, P., Buvat, I., Benali, H., Gibaud, B. (2004). Evaluation of Registration of Ictal SPECT/MRI Data Using Statistical Similarity Methods. In: Barillot, C., Haynor, D.R., Hellier, P. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004. MICCAI 2004. Lecture Notes in Computer Science, vol 3216. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30135-6_84
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DOI: https://doi.org/10.1007/978-3-540-30135-6_84
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