RESOURCES
Putting resources into the hands of scientists, developers, and clinicians
To encourage innovation through the broad engagement of the biomedical community, CVIT shares user-friendly, well-documented, and easily accessible resources for virtual trials in medical imaging.
These resources, continuously updated, include virtual human models, the formation of digital twins, simulations of varying pathologies, simulation of imaging processes, and modeling of human and machine reading of virtual data.
Software
iTrialSpace: Programmable Virtual Lung Lesion Trials
Programmable virtual lesion trial framework that enables controlled, auditable evaluation of chest CT AI models by systematically varying lesion, anatomy, and imaging factors.AI in Lung Health: Benchmarking Detection and Diagnostic Models
A public, reproducible benchmark for evaluating AI models for lung nodule detection and malignancy classification across multiple datasets using standardized training, validation, and external testing protocols.DukeSeg Automated CT Segmentation Framework
Automated framework for automated segmentation of up to 140 organs and structures in whole body CT.Graphical User Interface (GUI) for DukeSim
DukeSim GUI v1.0 is a webpage-based graphical user interface (GUI) to run the DukeSim CT simulator. The GUI allows users to select phantom models, scanner models, and imaging parameters to generate simulated CT images.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.Pysarfe Radiomics Pipeline
Pipeline includes eleven unsupervised binary segmentation methods and a feature extraction module to calculate various radiomics features for an image and its binary segmentation pair.DukeSim v1.2
DukeSim v1.2 is a GPU-based CT simulator that generates CT projection and reconstruction images of a given voxelized computational phantom.XCAT Phantom Program
Highly detailed male and female anatomies for subjects that are 50th percentile in terms of height/weight and organ volumes (thousands of defined structures including muscles and blood vessels).
Data
Duke Lung Cancer Screening (DLCS) Dataset
Large-scale low-dose chest CT screening dataset with nodule annotations based on modern lung cancer screening practices.XCAT 3.0 Personalized Phantom Library
A large-scale library of over 2,500 anatomically detailed computational phantoms generated from automated CT segmentation for virtual imaging trials and AI evaluation.Virtual Lung Screening Trial (VLST)
An in silico emulation of the National Lung Screening Trial using virtual patients, simulated CT/CXR imaging, and AI-based virtual readers for lung cancer detection.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.RAD-ChestCT Dataset
Large database of chest CT scans from unique patients. Each CT volume is annotated with a matrix of 84 abnormality labels x 52 location labels.2D Numerical Mouse Phantom for Dynamic Photoacoustic Tomography Studies
Anatomically realistic spatiotemporal maps of optical absorption coefficient and photoacoustically induced pressure distribution for virtual imaging studies of dynamic photoacoustic tomography of small animal models.Multimodal Ground Truth Datasets for Abdominal Medical Image Registration
Synthesized multimodal images (T1-weighted MRI, CT, and cone beam CT) as ground truth for image segmentation and registration.Database for Benchmarking Organ Dose Estimates and Uncertainties in CT
CT patient images and associated verified Monte Carlo based estimates of organ doses that may be used for benchmarking different organ dose estimation techniques against a reference standard.
