Design, Tuning and Performance Evaluation of an Automated Pulmonary Nodule Detection System

摘要

Radiologists miss approximately 25-30% of all pulmonary nodules smaller than 1.0 cm. in mass screenings. This paper describes a system for the automated detection of pulmonary nodules. It aids the radiologist by indicating the sites in the radiograph most likely to be nodules. Procedurally-driven image experts that respond to specific types of anatomic features are incorporated in a pattern recognizer which uses linear discriminant analysis to classify the candidate nodule sites. Sites not classified as nodules are eliminated from the list of sites presented to the radiologist for inspection. This system has been tested on 43 chest radiographs, and has demonstrated that pattern recognition techniques and procedurally-driven image experts are capable of reducing the number of sites that a radiologist for inspection. This system has been tested on 43 chest radiographs, and has demonstrated that pattern recognition techniques and procedurally-driven image experts are capable of reducing the number of sites that a radiologist must inspect from at most 17 to at most 3 in order to be 99% confident of having inspected any nodule detected by the system that is trained with 37 films.