Purpose: To experimentally validate the Fastcat cone beam CT (CBCT) simulator against kV and MV CBCT images acquired with a Varian Truebeam linac. Methods: of Catphan 504 phantom were using 100 kVp on-board imager (OBI) 6 treatment electronic portal imaging device (EPID), respectively. The simulation was performed detailed models x-ray source, bowtie filter, high resolution voxelized virtual ph...

Purpose: We describe the creation of computational models lung pathologies indicative COVID-19 disease. The are intended for use in virtual clinical trials (VCT) task-specific optimization chest x-ray (CXR) imaging. Approach: Images patients confirmed by computed tomography were used to segment areas increased attenuation lungs, all compatible with ground glass opacities and consolidations. Usi...

Correction for rigid object motion in helical CT can be achieved by reconstructing from a modified source-detector orbit, determined by the object motion during the scan. This ensures that all projections are consistent, but it does not guarantee that the projections are complete in the sense of being sufficient for exact reconstruction. We have previously shown with phantom measurements that m...

This study is designed to accurately simulate a helical CT-scanner for the purpose of estimating radiation dose and to perform validation experiments involving several dose profile and ionization chamber measurements. To accomplish this we have modified a general purpose Monte Carlo transport code (MCNP4B) as the framework for simulating the x-ray source and its movement, photon transport and r...

Introduction: We aimed to investigate the effect of variation of beam angle and field of view (FOV) on organs’ and effective doses for patients undergoing interventional cardiology examinations by using Monte Carlo simulations and ICRP110 phantom.   Materials and Methods: Simulations were done for energies obtained from experimental measurements on the left...

3D convolutional neural networks (3D-CNN) have been used for object recognition based on the voxelized shape of an object. In this paper, we present a 3D-CNN based method to learn distinct local geometric features of interest within an object. In this context, the voxelized representation may not be sufficient to capture the distinguishing information about such local features. To enable effici...

The dramatically increasing size of polygonal models resulting from 3D scanning devices and advanced modeling techniques requires new approaches to reduce the load of geometry transfer and processing. In order to supplement methods like polygon reduction or geometry compression we suggest to exploit the processing power and functionality of the rasterization and texture subsystem of advanced gr...