Abnormality Detection
Convolutional neural networks (CNNs) provide an alternative path to computer vision problems by learning the features of interest automatically when trained with large amounts of labeled data. The NLST data is an ideal dataset for training CNNs because of the consistency and quality of the labeled data.
This project will investigate the ability of CNNs to automatically identify areas of a thoracic CT that a Radiologist would have identified an abnormality.
SA 1: Build a framework for training a CNN on NLST data
SA 2: Determine the sensitivity and specificity of a variety of CNN architectures in identifying abnormalities in NLST images
Jeremy Friese, MD, Invenshure