Skip to main content
Browse by:
GROUP

Effective March 10, 2020, all Duke-sponsored events over 50 people have been cancelled, rescheduled, postponed or virtualized.
Please check with the event contact regarding event status. For more information, please see https://coronavirus.duke.edu/events

COVID+DS: Analysis of chest CT imaging data and connection to COVID diagnosis

Event Image
Icon calendar
Tuesday, July 28, 2020
Icon time
4:00 pm - 5:00 pm
Icon location
Icon speaker
Rachel Draelos
Icon series
COVID+DS

Medical image analysis with machine learning holds immense promise for accelerating the radiology workflow and benefiting patient care. Chest computed tomography (CT) is a medical imaging technique that produces a high-resolution volumetric image of the heart and lungs. Chest CT can be used to diagnose a wide variety of conditions including cancer, fractures, and infections like COVID-19. However, interpreting a chest CT scan requires over 12 years of postsecondary education and painstaking manual inspection of hundreds of 2D slices. There is thus significant interest in developing machine learning models that can automatically interpret chest CT images. In this session, a variety of machine learning models for automated chest CT interpretation are introduced, including slice and volume-based convolutional neural networks. Furthermore, recent literature proposing automatic COVID-19 diagnosis from chest CT scans is reviewed and analyzed.

This session is part of the Duke+Data Science (+DS) program virtual series on COVID-19 + Data Science. Please join us for a 8-week series on data science methods with direct applications to the COVID-19 pandemic. Learn from Duke experts about the state-of-the-art in these 1-hour virtual sessions. For more information, please visit https://plus.datascience.duke.edu