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Abstract #3832

Interleaved White Marker Contrast with bSSFP Real-Time Imaging for Deep Learning based Needle Localization in MR-Guided Percutaneous Interventions

Jonathan Weine1,2, Rainer Schneider1, Urte K├Ągebein3, Bennet Hensen3, Frank Wacker3, and Florian Maier1

1Siemens Healthcare, Erlangen, Germany, 2TU Dortmund, Dortmund, Germany, 3Hannover Medical School, Hannover, Germany

Automatic localization of needles in real-time images can facilitate MR-guided percutaneous interventions. It enables automatic slice repositioning and targeting support and, thus, allows for faster workflows. The improvement of deep learning based passive needle tracking by using both, anatomical and positive contrast images as input was investigated. A prototype bSSFP sequence for interleaved acquisition of k-space lines for conventional and positive contrast with Cartesian readout was implemented and evaluated ex-vivo and in-vivo. The U-Net segmentation algorithm showed superior performance when using both contrasts. In conclusion, this method is a promising approach for robust needle localization in real-time interventional workflows.

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