Abstract #3746

A Multicomponent Image Registration Technique for Largely Deformed Ventricles in Mouse Brain After Stroke

Warda T. Syeda¹, Vanessa Brait², Alex Oman², Charlotte Ermine ², Jess Nithianantharajah ², Lachlan Thompson², Leigh A. Johnston^3,4, David K. Wright⁵, and Amy Brodtmann²

¹Melbourne Neuropsychiatry Centre, The University of Melbourne, Parkville, Australia, ²The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia, ³Department of Biomedical Engineering, The University of Melbourne, Melbourne, Australia, ⁴Melbourne Brain Centre Imaging Unit, The University of Melbourne, Parkville, Australia, ⁵Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia

A multicomponent registration technique has been proposed to perform image normalization in the presence of largely deformed ventricles in the mouse brain. By employing multicomponent similarity metrics, the proposed technique combines information from multiple filtered and contrast-enhanced copies of the original images in the optimization process. We apply the proposed method to a mouse brain dataset with enlarged ventricles after focal ischaemic stroke, and compare the performance with single-component registration.

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