Derek M. Wells, PhD

To compare the reproducibility of radiomics features between deep learning (DL) and adaptive statistical iterative reconstruction (ASIR) CT images under systematic acquisition parameter variations using the GE Revolution Apex scanner.

To demonstrate an automated workflow for fiducial marker tracking using online daily CBCT data and to characterize the geometric limitations of utilizing offline CT-sim fiducial centroids for the Varian TrueBeam triggered-imaging system.

To evaluate the reproducibility and electron density sensitivity of CT radiomics features across spectral image types and deep learning reconstruction levels using a tissue-equivalent phantom.