Author profile
Mayo Clinic
To develop a super-resolution convolutional neural network to generate high-resolution temporal bone images beyond the resolution limitation of a commercial photon-counting-detector (PCD) CT.
Deep learning-based image reconstruction and noise reduction (DLR) techniques are increasingly adopted in clinical CT to improve image quality at reduced radiation doses. While prior studies have demonstrated benefits for lesion detection, DLR performance in...
Photon-counting-detector (PCD) CT acquires multi-energy data in a single scan, enabling quantitation of electron density (ρe) and effective atomic number (Zeff). This study assessed the performance of PCD-CT for ρe and Zeff mapping across different phantom si...
To enhance spatial resolution in all three dimensions (x, y, z) of coronary CT angiography (cCTA) acquired with conventional energy-integrating detector (EID)-based CT systems, using a protocol-aware multi-slice deep learning model trained with resolution-mat...
Stopping-power ratio (SPR) is used in proton therapy to calculate the radiation dose distributions. SPR depends on tissue composition and can be calculated using multi-energy CT. This study compares the accuracy of SPR calculated using energy-integrating dete...
Lung tumors are poorly visible on conventional on-board 2D X-ray imaging due to limited soft-tissue contrast and overlapping anatomy, posing a challenge for patient setup on proton therapy systems equipped with 2D X-ray imaging. Our goal is to develop a novel...
Photon-counting detector CT (PCD-CT) is one of the most significant advances in CT over the past decade. As PCD-CT enters routine practice, evidence of benefit across cardiothoracic, neuro, and oncologic applications continues to grow. Realizing its full valu...
IM-CT