Abstract #1906

Automated multi-parametric segmentation of brain veins from GRE acquisition

Serena Monti^1,2, Pasquale Borrelli¹, Sirio Cocozza³, Sina Straubb⁴, Mark Ladd⁴, Marco Salvatore¹, Enrico Tedeschi³, and Giuseppe Palma⁵

¹IRCCS SDN, Naples, Italy, ²Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy, ³Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy, ⁴Department of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, ⁵Institute of Biostructure and Bioimaging, National Research Council, Naples, Italy

A new fully automated algorithm, based on structural, morphological and relaxometric information, is proposed to segment the entire brain deep venous system from MR images. The method is tested on brain datasets at different magnetic fields and its inter-scan reproducibility is also assessed. The proposed segmentation algorithm shows good accuracy and reproducibility, outperforming previous methods and becoming a promising candidate for the characterization of venous tree topology.

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