Real-time, acquisition parameter-free voxel-wise patient-specific Monte Carlo dose reconstruction in whole-body CT scanning using deep neural networks.

Journal: European radiology

Published Date: Jun 27, 2023

OBJECTIVE: We propose a deep learning-guided approach to generate voxel-based absorbed dose maps from whole-body CT acquisitions.

Yazdan Salimi

Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva, Switzerland.
Azadeh Akhavanallaf

Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva, Switzerland.
Zahra Mansouri

Department of Biomedical Engineering and Medical Physics, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Isaac Shiri

Biomedical and Health Informatics, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran.
Habib Zaidi

Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva 4, Switzerland. habib.zaidi@hcuge.ch.

Humans Monte Carlo Method Neural Networks, Computer Phantoms, Imaging Radiation Dosage Tomography, X-Ray Computed Whole Body Imaging

View on PubMed Access via DOI PubMed (37368113)