Deep Learning–Generated Synthetic MR Imaging STIR Spine Images Are Superior in Image Quality and Diagnostically Equivalent to Conventional STIR: A Multicenter, Multireader Trial

L.N. Tanenbaum; S.C. Bash; G. Zaharchuk; A. Shankaranarayanan; R. Chamberlain; M. Wintermark; C. Beaulieu; M. Novick; L. Wang

doi:10.3174/ajnr.A7920

Research ArticleSpine

Deep Learning–Generated Synthetic MR Imaging STIR Spine Images Are Superior in Image Quality and Diagnostically Equivalent to Conventional STIR: A Multicenter, Multireader Trial

L.N. Tanenbaum, S.C. Bash, G. Zaharchuk, A. Shankaranarayanan, R. Chamberlain, M. Wintermark, C. Beaulieu, M. Novick and L. Wang

American Journal of Neuroradiology August 2023, 44 (8) 987-993; DOI: https://doi.org/10.3174/ajnr.A7920

L.N. Tanenbaum

aFrom RadNet (L.N.T., S.C.B.), New York, New York

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S.C. Bash

aFrom RadNet (L.N.T., S.C.B.), New York, New York

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G. Zaharchuk

bStanford University Medical Center (G.Z., C.B.), Stanford, California

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A. Shankaranarayanan

cSubtle Medical (A.S., R.C., L.W.), Menlo Park, California

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R. Chamberlain

cSubtle Medical (A.S., R.C., L.W.), Menlo Park, California

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M. Wintermark

dMD Anderson Cancer Center (M.W.), University of Texas, Houston, Texas

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C. Beaulieu

bStanford University Medical Center (G.Z., C.B.), Stanford, California

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M. Novick

eAll-American Teleradiology (M.N.), Bay Village, Ohio

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L. Wang

cSubtle Medical (A.S., R.C., L.W.), Menlo Park, California

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L.N. Tanenbaum, S.C. Bash, G. Zaharchuk, A. Shankaranarayanan, R. Chamberlain, M. Wintermark, C. Beaulieu, M. Novick, L. Wang

Deep Learning–Generated Synthetic MR Imaging STIR Spine Images Are Superior in Image Quality and Diagnostically Equivalent to Conventional STIR: A Multicenter, Multireader Trial

American Journal of Neuroradiology Aug 2023, 44 (8) 987-993; DOI: 10.3174/ajnr.A7920

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Deep Learning for STIR Spine MRI Quality

L.N. Tanenbaum, S.C. Bash, G. Zaharchuk, A. Shankaranarayanan, R. Chamberlain, M. Wintermark, C. Beaulieu, M. Novick, L. Wang

American Journal of Neuroradiology Aug 2023, 44 (8) 987-993; DOI: 10.3174/ajnr.A7920

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