Mridul Bhattarai, PhD

Building physics-informed AI frameworks for reliable clinical imaging.

Photon Counting CT Engine

Developing a validated, customizable framework for photon-counting CT that enables efficient large-scale synthetic multi-energy data generation across detector materials, geometries, and acquisition protocols for developmental, pre-clinical, and clinical scanners.

Modeling Photon-Counting CT Scanners
A simulation framework (Monte Carlo + analytical) of customizable photon-counting CT scanners (DukeCounter).
Utility of Virtual DukeCounter Scanners
Simulated CT images of voxelized digital phantoms – including ACR, a digital human model with COPD, and a digital human model with liver parenchymal lesions – acquired using virtual photon-counting CT systems with CdTe, CZT, Si, and GaAs detectors. All data were generated using the DukeCounter simulation framework.

Example datasets: axial cross-sectional 3D CT images of a digital human phantom with COPD, generated using DukeCounter photon-counting CT scanners

Images from CdTe-based DukeCounter Scanner
Images from CZT-based DukeCounter Scanner
Images from GaAs-based DukeCounter Scanner
Images from Si-based DukeCounter Scanner
Medical Physics – 2025 – Development of a customizable model for spectral photon‐counting detector CTDownload
Citation

Bhattarai M, Panta RK, Segars WP, Abadi E, Samei E. Development of a customizable model for spectral photon-counting detector CT. Med Phys. 2025; 52:e70195. https://doi.org/10.1002/mp.70195