Automated detection of lung nodules from multi-slice CT image data

摘要

An automated method and system for detecting lung nodules from thoracic CT images employs an image processing algorithm (22) consisting of two main modules: a detection module (24) that detects nodule candidates from a given lung CT image dataset, and a classifier module (26), which classifies the nodule candidates as either true or false to reject false positives amongst the candidates. The detection module (24) employs a curvature analysis technique, preferably based on a polynomial fit, that enables accurate calculation of lung border curvature to facilitate identification of juxta-pleural lung nodule candidates, while the classification module (26) employs a minimal number of image features (e.g., 3) in conjunction with a Bayesian classifier to identify false positives among the candidates.