Iterative principal axes registration: A new algorithm for retrospective correlation of MR-PET brain images

Autor:	Atam P. Dhawan, Louis K. Arata
Rok vydání:	1992
Předmět:	Correlation medicine.diagnostic_test business.industry Computer science medicine Computer vision Magnetic resonance imaging Artificial intelligence Nuclear medicine business Principal axis theorem
Zdroj:	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
DOI:	10.1109/iembs.1992.5761684
Popis:	Registration of Magnetic Resonance (MR) and Positron Emission Tomographic (PET) images is a crucial step in multi-modality brain image analysis. We have developed a technique which we call iterative principal axes registration (IPAR). Using this method, partial volumes of PET images can be accurately registered with complete MR scans. We will present qualitative and quantitative results of the new method. These results show that IPAR is accurate and practical as a registration method for MR-PET correlation studies.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::e32a025cde418564ea87217844e17f1a https://doi.org/10.1109/iembs.1992.5761684 Zobrazit plný text záznamu