Creating High Fidelity Synthetic Pelvis Radiographs Using Generative Adversarial Networks: Unlocking the Potential of Deep Learning Models Without Patient Privacy Concerns

In this work, we applied and validated an artificial intelligence technique known as generative adversarial networks (GANs) to create large volumes of high-fidelity synthetic anteroposterior (AP) pelvis radiographs that can enable deep learning (DL)-based image analyses, while ensuring patient priva...

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Veröffentlicht in:	The Journal of arthroplasty 2023-10, Vol.38 (10), p.2037-2043.e1
Hauptverfasser:	Khosravi, Bardia, Rouzrokh, Pouria, Mickley, John P., Faghani, Shahriar, Larson, A. Noelle, Garner, Hillary W., Howe, Benjamin M., Erickson, Bradley J., Taunton, Michael J., Wyles, Cody C.
Format:	Artikel
Sprache:	eng
Schlagworte:	artificial intelligence deep learning generative adversarial networks patient privacy pelvis radiographs synthetic imaging
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