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Abstract #1302

3D DUAL RECURSIVE REFINER NETWORK FOR ROBUST SEGMENTATION: APPLICATION TO BRAIN EXTRACTION

Maxime Bertrait1, Pascal Ceccaldi1, Boris Mailhé1, Youngjin Yoo1, and Mariappan S. Nadar1
1Digital Technology and Innovation, Siemens Healthineers, Princeton, NJ, United States

In Magnetic Resonance Imaging, acquisition protocol may varies from one clinical task to another affecting the resulting reconstructed scan in terms of field of view and resolution. In research, 3D acquired MRI scans are widely available providing high quality isotropic medical images but is far from what can exist in clinical environment such as 2D multi-slices with thick slices acquisition that can provide anisotropic medical images. We then present a framework, through a brain extraction task, called Dual Recursive Refiner able to work with both acquisitions. The presented framework outperforms baseline architectures for segmentation on both isotropic and anisotropic data.

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