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Abstract #4528

Intelligent volume rendering of ZTE MR Bone images

Vineet Mehta1, Deepthi Sundaran1, Jignesh Dholakia1, Maggie Fung2, and Michael Carl3
1GE Healthcare, Bengaluru, India, 2GE Healthcare, New York City, NY, United States, 3GE Healthcare, San Diego, CA, United States

Synopsis

Keywords: Bone, Visualization, Volume RenderingThis study presents a new Deep-Learning (DL) based processing pipeline to enable one-click volume rendering of MR Bone Zero TE (ZTE) images. It comprises of DL based background subtraction followed by histogram adjustment. A comparison with existing algorithms demonstrates that the proposed method prevails in accuracy of background subtraction (DICE = 0.97) and eliminates the tedious, error-prone manual steps of segmentation and histogram adjustment required to prepare the data for usable volume rendering. It can also be used universally across anatomies as opposed to other methods requiring anatomy-specific tuning.

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Keywords