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Editorial
. 2023 Sep;308(3):e232344.
doi: 10.1148/radiol.232344.

The Potential for Deep Learning Reconstruction to Improve the Quality of T2-weighted Prostate MRI

Baris Turkbey  1
Affiliations
Editorial

The Potential for Deep Learning Reconstruction to Improve the Quality of T2-weighted Prostate MRI

Baris Turkbey. Radiology. 2023 Sep.
No abstract available

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Conflict of interest statement

Disclosures of conflicts of interest: B.T. Cooperative research and development agreements with NVIDIA and Philips; royalties from the National Institutes of Health; patents in the field of artificial intelligence.

Figures

Dr Baris Turkbey is a senior clinician at the Molecular Imaging Branch of the National Cancer Institute at the National Institutes of Health, where he currently serves as the head of MRI and the Artificial Intelligence Resource. He is a fellow of the Society of Abdominal Radiology and serves as a member of the PI-RADS Steering Committee. His main research areas include cancer imaging (MRI, PET/CT), quantitative imaging biomarkers, and translational AI.
Dr Baris Turkbey is a senior clinician at the Molecular Imaging Branch of the National Cancer Institute at the National Institutes of Health, where he currently serves as the head of MRI and the Artificial Intelligence Resource. He is a fellow of the Society of Abdominal Radiology and serves as a member of the PI-RADS Steering Committee. His main research areas include cancer imaging (MRI, PET/CT), quantitative imaging biomarkers, and translational AI.
See this image and copyright information in PMC

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References

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