@inproceedings{06cd80ddbc3548d5ba3d0e73bb611a1b,
title = "Feasibility of X-ray Fluorescence Computed Tomography (XFCT) Imaging of Human Lung Tumors loaded with Gold Nanoparticles: A Monte Carlo Study",
abstract = "We present a novel Monte Carlo model of x-ray fluorescence (XRF) computed tomography (XFCT) imaging of human lung tumors loaded with gold nanoparticles (GNPs). In this model, the lung phantom derived from CT images was excited using a fan/cone beam of x-rays and the XRF/Scatter photons were detected using linear array detectors coupled with parallel-hole collimators. Whereas 1 wt. % GNP regions located at ~4-5 centimeter depths within the phantom could be detected reliably under the current conditions, it became challenging to detect such GNP regions present at deeper depths. Nevertheless, this study opened up the possibility to apply XFCT techniques for human lung cancer detection in conjunction with GNPs.",
keywords = "Gold Nanoparticles, Lung cancer, Monte Carlo, X-ray Fluorescence Computed Tomography",
author = "Ahmed, {Md Foiez} and Sandun Jayarathna and Cho, {Sang Hyun}",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 12th IEEE International Conference on Nano/Molecular Medicine and Engineering, NANOMED 2018 ; Conference date: 02-12-2018 Through 05-12-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/NANOMED.2018.8641551",
language = "English (US)",
series = "IEEE International Conference on Nano/Molecular Medicine and Engineering, NANOMED",
publisher = "IEEE Computer Society",
pages = "250--254",
booktitle = "Proceedings of the 12th IEEE International Conference on Nano/Molecular Medicine and Engineering, NANOMED 2018",
}