Computer aided diagnostic system incorporating appearance analysis for diagnosing malignant lung nodules

摘要

A computer aided diagnostic system and automated method diagnose lung cancer through modeling and analyzing the visual appearance of pulmonary nodules. A learned appearance model used in such analysis describes the appearance of pulmonary nodules in terms of voxel-wise conditional Gibbs energies for a generic rotation and translation invariant second-order Markov-Gibbs random field (MGRF) model of malignant nodules with analytically estimated characteristic voxel neighborhoods and potentials.

主权项

1. A method of classifying a pulmonary nodule, the method comprising:
receiving image data associated with a chest scan; segmenting image data associated with lung tissue from the image data associated with the chest scan; equalizing the segmented image data; segmenting image data associated with a pulmonary nodule from the equalized and segmented image data; and classifying the pulmonary nodule as benign or malignant by applying a learned appearance model to pulmonary nodule image data for the pulmonary nodule from the segmented image data associated with the pulmonary nodule, wherein the learned appearance model is based upon visual appearances of a plurality of known pulmonary nodules and models voxel-wise conditional Gibbs energies, wherein classifying the pulmonary nodule as benign or malignant includes determining an intensity variation between voxels within the pulmonary nodule image data, and classifying the pulmonary nodule as benign or malignant based at least in part on the determined intensity variation.