This reference pipeline is designed to infer the probability of COVID-19 infection with the lung CT scan of a patient. A 3D lung segmentation model as well as a 3D classification model are used in this pipeline. The pipeline input is a single axial DICOM series from a chest CT, and the final output is a probability of COVID-19 and non-COVID-19 in csv format.
Once the DICOM instances are received, the pipeline is triggered to first convert the DICOM instances to a volume image in MetaImage format. This image is then used as the input to the lung segmentation operator which performas inference using the segmentation AI model, and generates a labeled segmentation as a binary mask on each slice of the volume, with the lung labeled as 1, and the background labeled as 0. In the next step, the original volume image along with the labeled segmentation image are used by the COVID-19 classification operator to infer the probabilities of COVID-19 using the COVID-19 classification model.
Probability of COVID-19 infection from a patient’s chest CT to inform subsequent research.
DICOM chest CT.
The Software is for Research Use Only. Software’s recommendation should not be solely or primarily relied upon to diagnose or treat COVID-19 by a Healthcare Professional. This research use only software has not been cleared or approved by FDA or any regulatory agency.
This inference pipeline was developed by NVIDIA. It is based on a segmentation and classification model developed by NVIDIA researchers in conjunction with the NIH. This training and inference pipeline is licensed for research and development only. It is not approved by any regulatory agency, and is not intended for clinical use.
Information on training data
The models in this pipeline were based on a database of more than 3,000 CT images from the U.S., Italy, China and Japan. The data set included more than 2,000 images from confirmed Covid-19 cases.
Model performance metrics
The model accuracy is above 90%
Model available on Arterys.
NVIDIA’s (NASDAQ: NVDA) invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. More information at .