Artificial neural network for pulmonary nodule detection: Preliminary human observer comparison

A single-layer artificial neural network was developed to detect synthetic pulmonary nodules of approximately the same size in patient chest radiographs. The identical detection task was given to human observers with varying degrees of radiological training (board-certified radiologists, residents, and a medical swdent). The network and human observers were presented five patient radiographs each with 12 marked locations. The human observers estimated the probability that a nodule was present at each of these locations. The network evaluated the same locations for the presence of a nodule. Using Receiver Operating Characteristic (ROC) analysis, we found that the performance of the artificial neural network was comparable to that of human observers. The areas under the curve for the neural network and human observers were 0.93 and 0.92, respectively.

Duke Scholars

Author Carl Eric Ravin Radiology, Cardiothoracic Imaging