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Abstract #1225

3D MRI-US multimodal alignment for real-time intervention - a tradeoff between accuracy and computation time

Jhimli Mitra1, Chitresh Bhushan1, Soumya Ghose1, David Mills1, Heather Chan1, Matthew Tarasek1, Shane Wells2, Sydney Jupitz3, Chris Brace4, Bryan Bednarz3, Thomas Foo1, James Holmes5, and Desmond Yeo1
1GE Research, Niskayuna, NY, United States, 2Depts. of Radiology and Urology, University of Wisconsin-Madison, Madison, WI, United States, 3Dept. of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, 4Depts. of Radiology and Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States, 5Dept. of Radiology, University of Iowa, Iowa City, IA, United States

Synopsis

Keywords: Liver, Multimodal, Real-time multimodal alignment, image-guided intervention, MRI-US deformable fusionMultimodal MRI-US image fusion in image-guided therapy such as liver microwave ablation aids in correct placement of the applicator device. Significant tissue deformation due to breathing motion requires alignment of pre-interventional MRI on real-time interventional US to compensate for the motion. In this work, we present a hybrid framework (conventional and deep learning) for multimodal deformable registration to provide higher accuracy and retain the low latency required for real-time interventions.

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Keywords