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Abstract #1906

Automated multi-parametric segmentation of brain veins from GRE acquisition

Serena Monti1,2, 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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