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Abstract #4052

Deep-Learning Based Image Reconstruction for Lumbar Spine MRI at 3T: Clinical Feasibility

Emma Bahroos1, Misung Han1, Cynthia Chin1, David Shin2, Javier Villanueva-Meyer1, Thomas Link1, Valentina Pedoia1, and Sharmila Majumdar1
1Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States, 2Applications and Workflow, GE Healthcare, Menlo Park, CA, United States

Lower back pain is one of the most common health problems, for which MRI is extensively used. Standard clinical, and fast acquisition images of lumbar spine were acquired for 18 patients. A (DL)-based image reconstruction was applied to the raw data of the fast images, with 25%, 50%, and 75% noise reduction factors. Evaluation of fast images with DL algorithm, for image quality, diagnostic capability, and SNR to standard images was conducted by three experienced radiologists. Our results show SNR improvement with higher noise reduction factor without a severe degradation in the ability to discern anatomical structures.

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