CENTER FOR VIRTUAL IMAGING TRIALS
A virtual platform for evaluating medical imaging technologies from design to use


CVIT is a National Center for Biomedical Imaging and Bioengineering supported by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) and operated at Duke University.
CVIT is heading to ATS 2023 International Conference in Washington, DC
A New Methodology
We offer an efficient methodology for evaluating imaging technologies and applications in silico using computational models simulating the patient, the imaging system, and the image reader.
These models comprise our three technology, research, and development (TR&D) endeavors, where we continue to provide realistic computational models of human anatomy (virtual patients), state-of-the-art CT scanners (virtual scanners), and clinically relevant image analysis (virtual readers).
The TR&Ds work synergistically to offer comprehensive resources and essential training to partners through our various collaborative and service projects as well as training and dissemination efforts.
Recently Shared Software
TransMorph: Transformer for Unsupervised Medical Image Registration
Novel hybrid Transformer-ConvNet model designed for 3D medical image registration.CVIT Observer Models
Toolbox for mathematical observer model calculations, designed to produce image quality figures of merit from simulated image data from CVIT.
Recently Shared Data
Library of Organ Dose Coefficients in Tomosynthesis Imaging
Library of dose coefficients for organ dosimetry in tomosynthesis imaging of adults and pediatrics across diverse protocols.200 Anatomically Variable Adult Voxelized Phantoms
Anatomically variable chest and abdomen phantoms, each based on CT data and modeling either COPD or lung or liver abnormalities.
News
CVIT is heading to ATS 2023 International Conference in Washington, DC
CVIT member Saman Sotoudeh-Paima received finalist for the Robert F. Wagner award at SPIE Medical Imaging conference
Virtual Imaging Trials in Medicine – International Summit
Important Metrics

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