Abstract #1443

Optimization of 2D registration using minctracc on myelin stained brain slices

Max Prihoda^1,2, Simon Hametner³, Andreas Deistung⁴, Verena Endmayr³, Andrew Janke⁵, Claude Lepage⁶, Thomas Haider⁷, Simon Daniel Robinson⁸, Xiang Feng⁴, Hans Lassmann³, Jürgen Reichenbach⁴, Evelin Haimburger¹, Christian Menard⁹, Hannes Traxler¹⁰, Siegfried Trattnig⁸, and Günther Grabner^1,2,8

¹Department of Radiologic Technology, Carinthia University of Applied Sciences, Klagenfurt, Austria, ²Institute for Applied Research on Ageing, Carinthia University of Applied Sciences, Klagenfurt, Austria, ³Center for Brain Research, Medical University of Vienna, Vienna, Austria, ⁴Medical Physics Group, Institute for Diagnostic and Interventional Radiology, Jena University Hospital – Friedrich Schiller-University, Jena, Germany, ⁵Centre for Advanced Imaging, University of Queensland, Brisbane, Australia, ⁶Montreal Neurological Institute, McGill University, Montreal, Canada, ⁷University Clinic for Trauma Surgery, Medical University Vienna, Vienna, Austria, ⁸High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria, ⁹Department of Medical Engineering, Carinthia University of Applied Sciences, Klagenfurt, Austria, ¹⁰Center of Anatomy and Cell Biology, Medical University Vienna, Vienna, Austria

Histological analyses are important for a wide spectrum of in vivo and in vitro imaging projects. But unlike MRI or CT, histological analyses are typically performed in two dimensions. Nonlinear tissue deformation and ruptures of brain tissue are often common, making analysis in slice direction more difficult. In this work, we optimized a hierarchical, nonlinear fitting pipeline on the basis of two high resolution, myelin stained brain sections using mintracc.

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