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

Seema Garg; Carey E. Floyd Jr.; Carl E. Ravin

doi:10.1117/12.175098

11 May 1994 Artificial neural network for pulmonary nodule detection: preliminary human observer comparison

Seema Garg, Carey E. Floyd Jr., Carl E. Ravin

Proceedings Volume 2167, Medical Imaging 1994: Image Processing; (1994) https://doi.org/10.1117/12.175098
Event: Medical Imaging 1994, 1994, Newport Beach, CA, United States

Abstract

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 student). 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 Reciever Operating Characteristic (ROC) analysis, we found that the performance of the artificial neural network was comparable to that of human observer. The areas under the curve for the neural network and human observers were 0.93 and 0.92, repectively.

Citation Download Citation

Seema Garg, Carey E. Floyd Jr., and Carl E. Ravin "Artificial neural network for pulmonary nodule detection: preliminary human observer comparison", Proc. SPIE 2167, Medical Imaging 1994: Image Processing, (11 May 1994); https://doi.org/10.1117/12.175098

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