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Author

Maximilian Schmid

2 papers indexed here

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Open access Aug 2026

Eliminating registration bias in synthetic CT generation using a physics-based simulation framework for pelvic anatomy

Objective. Supervised synthetic computed tomography (sCT) generation from cone-beam computed tomography (CBCT) requires spatially registered training pairs, yet perfect registration between separately acquired scans is unattainable. This registration bias propagates into trained models and corrupts intensity-based eval...

L. Zimmermann, Michael Rauter, Martin Buschmann et al. · 0 citations
Open access Aug 2026

Eliminating Registration Bias in Synthetic CT Generation using a physics-based simulation framework for pelvic anatomy.

OBJECTIVE Supervised synthetic computed tomography (sCT) generation from cone-beam CT (CBCT) requires spatially registered training pairs, yet perfect registration between separately acquired scans is unattainable. This registration bias propagates into trained models and corrupts intensity-based evaluation, so higher...

L. Zimmermann, Michael Rauter, Martin Buschmann et al. · 0 citations

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